40 Burst results for "AI"
Fresh update on "ai" discussed on The Car Pro Show
"Possible. No W O AI local news. Six people are hospitalized in Corpus Christi after an explosion at a refinery it around 10 this morning. It's a plant owned by Magellan, Corpus Christi that was being cleaned at the time of the explosion. The fire has been extinguished. No details yet on the extent of the injuries. Texas is now averaging 11,115 new cases, A cove it daily on the seven day average and an average of 150 deaths a day. Hard hit Denton County reporting only six ICU beds remain available. The state Health Department says Texas will receive 224,250 doses of covert vaccine in 34 counties arriving the week of December, 14th. In San Antonio North side, I SD confirming a rapid testing pilot program for Cove. It's going to be available Monday at 10 schools They haven't identified. Which schools those will be yet I'm Nikki Court name. From the W away I traffic.
How Qualcomms latest chip powers better photos and AI
"Another one of the tent poles of this new platform. That's that's artificial. Intelligence a is been bandied about by basically every company for a low wall. Now what exactly does the eight bring when it comes to. So i think is starting to get embedded in so many different applications. We just we just don't know it You know things such as real time. Translation is is a isn't application of ai. people don't realize you know but but even more discreetly when you take a photograph for example gay. How many people know go into different settings in china you know make it so that the photograph just outright you lose that capture moment any of those things but the i just takes that whole thing out of it it can recognized environment you're in it can recognize different faces that you've specified it can recognize. Different states can recognize different lighting in. It'll just set your camera to the best possible aching of that photograph and video so lighting environments get recognized faces get recognized objects get recognized distances. Get in it can all put it together trying to figure out. How can i take the best video in the best photo and without thinking about so one. Second for example starts to recognize your patterns Let's say it sees you In In the office for x. Amount of time during the day and in driving an x. Amount of time during the day home x. amount of time during the day or even outside it can pick and choose. What's the best connection for you. tab the best call or data experience as another as another thing so there's so many different applications that ai is the underpinning of of those applications that it's it's almost impossible not to have that you know. Have that as part of one of the pills. So i want talk about topic. That's near and dear to most consumers my wife in particular that's taking photos that's camera tack. You talked a little bit about that before. But of that's another one of the temples of the eight. What are some of the capabilities enabled by this platform so last year. We what we did was. We introduced the first two pixel camera. What that allows you to do is Giga pixel per second. That what that allows you to do is to capture higher high resolution video higher and higher resolution images so you can capture eight k video. You can capture four k video but capture each frame at sixty four megapixel so imagine you capture video and then all of a sudden man. This one frame looks awesome right. I want i want that as a picture. You can capture that at sixty four megapixel which is a very high resolution image. That was last year this year. We're now at two point. Seventy two pixels per second. So now you're videos are even better your your Capture of of highest resolution Image sensors even better We can capture hundred and twenty photos at twelve megapixel resolution in one second. So now you can see. It's essentially thirty five percent faster than what we had last year. Now you can see all sorts of different applications. Coming through people can get creative in terms of video capture moment captured sharing. You know the so many different apple and now with the environment that we're living in that camera is so much more important because people want to share people want to be part of a of a of a social environment. People are continuously videoconferencing those those and then with five g. Coming in and ai coming in it just makes it easier and easier. So the more bandwidth camera the more bandwidth available on the network and higher quality with a i that will give a very very compelling user experience to someone who wants to wants to do that
Fresh update on "ai" discussed on The Skeptics' Guide to the Universe
"Modalities obsolete yeah. And then those resources get repurpose somewhere else. But that's a key difference to pseudoscience because pseudo sciences like acupuncture homeopathy. They're locked in a homeopath will always be a homeopath. And they can't allow their pseudoscience to be debunked because then they're they don't just go shift over to something else. They're out of a job. Yeah in some ways you see that too as a key difference with with sort of political. Ideology this idea that you know. I want things to be the same. Because this is what they're used to them being and it serves you know these different purposes these different interest groups and sometime i tried can't lose right and sometimes progress disrupts in a away this uncomfortable but to fight against that that discomfort means to prevent individuals from having their lives improved and disruptive technologies. Those are the things that we are going to start to see in. I think in the relatively near future things things that are that are such game changers that they they call them disruptive you know right. Dano tech artificial intelligence these things are disruptive and but it's a good disruptive. I think you know these are the things that are that are going to make people nervous. Because they're big chains incremental changes. They're gonna make people nervous but you know they you know they're they're on the horizon. We we see them coming hard to say when they're going to be here but they will come eventually they will. They have the potential to be very disruptive. And i think want my fish nato. I think we as a species need to just like we often talk about needing to be in front of the ethics on really injust changes like crisper and human cells ready for we need to have some sort of psychological training in how to adjust and adapt to rapid technological advancements. Because i do that. A lot of human nature is to say. I don't like this new thing. It scares me. I want to do it away but that that sort of lack of will could potentially be detrimental. A have. yeah. I think. I think i will be integral to these types of disruptive changes because we essentially you're automating some aspects of human intelligence and the ability to do research and to make scientific advancements and at some point i mean we may see changes. That are so fast that people will get freaked out. Yeah really freaked out a at the pace at some of these things are coming but we gotta we gotta talk about it. Now be ready. Be ready for it and anticipate and just you know so that we can guide them to the to the best possible outcomes like like creating. Ai that will that will think that we're just an infection that needs to be removed from the from the surface of the planet. That type of thing. You have a care by. I don't think most people are going to really even notice because they're going to be too busy enjoying they're really smooth ice cream them by their bad ass robot. Yeah let's move on. Okay evan. You're gonna finish up the news items talking about the international space station. I've been hearing some bad things about it. Yeah i've been reading some bad things about it and some people have been speaking some bad things about it. We love the international space station though. I s s it. I think it's as recognizable as any other name and astronautic history know right up there with apollo soyuz space shuttle mir and the ice absolutely an incredible feat of science and engineering. Perhaps more as importantly though it's a feet of cooperation and unity among nations so throughout the nineteen ninety s as we learned. Read more about this ambitious project as it was coming online. It's sort of stirred the sense of optimism that that we had and we lost a little time. We were still sort of recovering from pain. Loss the challenger explosion. The late eighties was very dark. Time for us since the. Us specifically in space exploration. We were not quite sure the future but this plan for the for the iss represented something new and fresh sophisticated and sort of romantic but also peaceful because if you think about the threat of nuclear war deteriorated with the dissolution of the soviet union in the early nineteen ninety s. Sort of that. The us and the russians would come together and finally start cooperating on one of the most ambitious projects in human history. That was an optimistic time. And then it came to fruition. One thousand nine hundred eight segments advice of iss went up into orbit and they connected and then by the end of two thousand it was hosting its first crew in conducting its first experiments and has been doing so ever since but that was twenty years ago today international space station it still captures the imagination but like anything in life it ages and in this case it does age before is you know. Space stations are no exception to this rule they can be improved upon upgrades made systems added but it's machinery and it needs more work than just routine maintenance can keep up with and something as complex a space station it makes it even more inevitable so it was unfortunate to hear the news report that came out last week. A report from a russian manufacturer r. s. c. energia. Who is the primary developer and contractor of the russian crewed spaceflight program a reported that a number of elements aboard the around the verge of catastrophic failure though. That sounds like hyperbole. But here's what they're actually say too many of the systems on the station or not fixable not upgradable and not worth the continuing effort and they predict an avalanche of failures by the year twenty twenty-five which is pretty much right on cue with when the current international agreements governing the station expire. And that's kind of important to remember now. These thoughts were expressed by the flight director of the russian segment of the iss. His name is vladimir solely of vladimir solovyev and he said this to a meeting of the russian academy of sciences council on space and at that meeting were many top officials from various russian academies of space science and astronautics estimated estimates to fix the problem aboard the iss would range to around ten to fifteen billion rubles and they deem that cost too high says at us style. Two hundred million. Oh yeah that's so it's a lot. You know an insurmountable. But they're saying that. That's too much evan. Can i ask like when was what what was the sort of age that the iss was supposed to make it to. The original timespan was fifteen years but they always say they. That's the original mission plan but you build the you design it so that it could go about double that so they said realistically if you put more money into it and you're renew your contracts and everything and you keep up with things. You can get thirty years out of the space station without a problem. When did it launch. The first modules went up in one thousand nine hundred ninety eight and it's been full and it's been connected and hosting people since two thousand twenty two twenty two years in so yeah we're not mean we're definitely into this this extension phase but this is nine numbers..
Using AI Created Digital Twins to Accelerate Clinical Trials
"Nature scientific reports peer reviewed Publication that now. It must have come out outlive well over a year ago and but we peer review takes very long time so that was written two years ago right even though it only got one year ago. Well basically what we do there is. We will take eighty percent of the train data. We have will train. The model will leave twenty percent of the data how to make predictions about these other. Twenty percents at the patients in making sure that all of the predictions that we make are really good. So that's one that's very early We've done much much more along those directions We've presented about our model presented data to fda on the office of neurosciences. We have a. We have done a number of retrospective studies where we can go back and look at previously completed clinical trials in reanalysed them. And make sure that when we're getting a better results out of those files Than than how they were originally run And then we also are working in ongoing prospective trials now In working with different pharmaceutical partners. Both in ways that are where our customers these collaborators. I getting value from the use of these models. But also that provide more validation off for our platform in the discussions with the fda. What kind of validation have been seeking with the fda. It's this is a really interesting area to to dig into I think that what we what we basically did with the fda's we showed them some data looking at we would take patients who were in cbo control arms of trials and then we would create digital twins of those patients that So now you have. The real patients receiving placebo in have the model predicting what would happen if they received placebo. So now you have a direct way to measure how well is the model doing it. Actually capturing for cbo behavior or these alzheimer's In so those are the kinds of data that we presented to the fda at a meeting in march of this year looking again at at leaving because we see so many things about these patients We have to really comprehensive Evaluation protocols evaluating all of the different things that were predicting But then the other thing of course is when you actually go to use these digital twins in clinical trials. You know that actually gets into another aspect of just the context of use because there are different ways that you can take these digital twins in incorporate them into the final analysis of the treatments affected in each one of those really discussed with regulators on a case by case basis because again adapting the use of the digital twins to the particular problem that the pharmaceutical facing the try year focusing on complex neurological diseases in particular alzheimer's disease. Why complex neurological diseases in general alzheimer's disease specifically why. I think the first thing comes down to an unmet need these are areas where clinical trials are very long in the very expensive. They included enormous numbers of patient. Volunteers it. We're not really having any success in developing new treatments so anything that we can do to make those trials more efficient to make them more ethical and better for the patients volunteer and to speed up drug development in those areas so that we can finally get affected therapies. The patients something that we really need. So that's that's the first thing. Is that the this large unmet. Need the second thing is there's availability of data as a machine learning company. We really relied. Not only on there being a lot of data but on those data being very high quality and because there's this long history of many many companies trying to develop drugs for these areas in many of those drugs failing there's an enormous amount of data that we can draw on to learn about how the disease progresses But we are are eventually looking to expand across disease area so even though our initial focus has been in these more complex longitudinal
Fresh "AI" from Sidebar with Nico LaHood
"Its attempt in June. This most recent ruling orders the Department of Homeland Security to begin accepting first time applicants to the program starting Monday. Fox is Tom Graham some rough weather in the Northeast today a lot of snow coming our first hand of big nor'easter of the season across parts of New England, especially that's where the snow is going to be a lot of the rain across parts of the mid Atlantic on in towards the Northeast. It'll be strengthening storm throughout the day. Fox meteorologist Rick Right Few America is listening to Fox. No Luo Ai local news, a major road closure on San Antonio's west side this morning loop 4 10 south bound lanes or shut down until about 10 A.m.. Then the north bound lanes will be closed from 10 A.m. Till about 2 P.m..
ACLU Asks Durkan to Ban Use of Facial Recognition Software
"L U claims Seattle Police are using face facial recognition technology and they wanted to stop comes Kelly Blier report. Did you see how you have? Washington sent Mayor Jenny Durkin's office a letter today to ban Seattle Police from using face recognition technology developed by ClearView Ai. The organization says they found out the information through a public records request. Jennifer Lee's with the A. C L U of Washington. The record indicated one police officer, But it's not clear how widespread this used. Maybe the mayor's office claims. The SPD has no licenses or agreement with ClearView Ai and does not use them. Seattle Council ordinance requires any use of this technology to be approved and it has not been given the OK the A C L U was demanding the City Council look into the matter.
Fresh update on "ai" discussed on Intelligence Squared U.S. Debates
"Filtering out and he irrelevance of missions and sorting the remaining arguments into four and against next technology identifies the recurring key. Points ranking them based on their quality and their frequency finally the ai creates a coherent narrative of the strongest and most prevalent points for both sides of debate. Okay and now we get to hear what the results were. This is a selection of key points and arguments that our global audience again more than a thousand people around the world thought. Were most important on this topic. Let's listening hello. The following analysis used ai models to identify the critical key points made by each side on the motion. We should stop worrying about national deficits fifty percent thought. We should stop worrying about national deficits with seventeen percent of those arguing. That national deficits have no direct negative impact on the economy. One argument said a high deficit does not mean a high risk of default. Financial institutions are strong and productivity is increasing. The the danger of an economic fallout has minimal. Another key point for the motion was that to an extent. The national debt allows financial growth. One argument said spending money stimulates the economy. Which will then bring the government. Money and lower the deficit people also think spending into a higher deficit is acceptable during a health crisis. The remaining fifty percent were against the motion with seventeen percent of submissions arguing. The rising can lead to inflation and cripple. the economy. one argument said national deficits fundamentally weaken the nation's economy and must be arbitrated to achieve a balanced resolution. Another key point against the motion was that national debt burdens future generations. One argument said we cannot pretend that we have money that we don't have it's disrespectful to younger generations. To run up the national deficit people also said that high public debt is dangerous while the world is so unstable with politics wars prevalent racism and extremism also. Having high national deficits around the world will cause more instability. Please visit the website to see more results. Good luck to the human debaters. All right so. We heard some of the arguments that the global audiences making a. We've touched on already and And we see that some of the dividing lines are quite similar to the confidence to the dividing lines in this conversation but there was one one point made that we haven't brought to and that's the social impact of deficits People were mentioning things global instability and things like war and extremism to the team. that's arguing against the resolution. I'll come to you at mar on this one. Our deficit's a threat to global security. We're not just not talking about the markets but actually to to global security overall chamber has made such a convincing argument for independence bank controlling the money supply and on the international side. I think we need stability international relations. They are so many gaullist coming from geopolitics and to this. This is not a big round against which governments should responsible spent money. I think the trust for example in the door dominant currency of the road. The based on this future stability of the currency so i think a country like the us is the least one to risk the stability of its currency and i would suppose that if the us government and including effect would explain that they would apply mt policies. The toll booths loose. It's sleeting positionally the votes because people would be afraid that in the future the investment. Did you stores would not be safe enough stephanie. Would you like to respond to that. I do thank you. So i keep hearing this bizarre discussion about the central bank being four store cajoled or asked to do something to aid and assist government spending that somehow what we're talking about is the capacity of the government to run deficits being somehow dependent upon the central banks acquiescence. In all of this that it has to give up some independence. Nobody has said any such thing. What i described with respect to the cares act is the way the government's always spend the government decides what it wants to spend and the fed is the government's bank. The fed carries out all payments that are authorized by congress on behalf of treasury always. It doesn't say no to the government it can't. It has to clear the payments what the fed has independence to do is to set the price at which congress will access those funds. Now think back to ronald reagan. Ronald reagan ran massive deficits. He didn't have a friendly federal reserve chairman holding interest rates near zero to accommodate all of this he had paul volcker and interest rates. Were double digits. They were almost sixteen percent. When reagan was president they never got below seven percent so very high interest rate environment. That did not stop ronald reagan from running massive deficits with two huge tax cuts and huge buildup in the military that almost tripled the national debt. So you don't have to have the fed behaving in a certain way to allow congress to do what congress can do republicans do it all the time. They increase the deficit for tax cuts in wars. And the rest of the time. The deficit increases is because the economy goes into recession. Those are the big drivers will look with all due respect. I think stephanie is running away from her own writings. But putting that aside the us dollar today is the world's reserve currency but you don't choose to be the reserve currency of the world. The world chooses you depending on your behavior. Let's bring james galbraith chains. You're worried about the standard of living of our children and grandchildren's thing.
"ai" Discussed on AI Today Podcast: Artificial Intelligence Insights, Experts, and Opinion
"Healthcare and for education in using more energy with the help of ai with the with the shoveling process and something that has been called the date wallet where where we can manage Getting enable citizens do manage their their data capital or something that is currently merging as as day to capital city. The three layers that we have come up with. And i think the the the key ovation is in the third layer that while we see a lot of countries that they they developed institutions and resources and In key areas where they want to focus on. This is something that came up. Maybe because of our Our structure of a lot of ideas coming from the bottom up that we need things that we can actually focus on and then showed results in for the everyday people that brings it closer to their to their lives and make it relatable. So maybe that's just a quick recap of the. I'm the strategy. Great yeah thank you. i know. It's a very comprehensive strategy. So it's not always easy to summarize just a few minutes that was great and then i know that follow up questions dig a little bit deeper into some of these including this one so one area of the strategy focuses on education competence development and societal preparedness. I know that there's also a goal in this strategy to create in a innovation centre as well. Can you share with us. Some more details around this picture so as i said this kind of competency development in social preparedness that it's a key factor that that the technology is there. We could gain a lot of value from this if a lot of people knew what this was. And we're not afraid of it. Did not have misconceptions are didn't have the first association to be the terminator seven big job to to transform a societies thinking from the judges of of what they haven't here to a realistic view of what is really happening although this is a very personal thing because an artificial we a lot of cases identify ourselves with our intelligence into..
Fresh update on "ai" discussed on Heartland Newsfeed Radio Network
"Welcome back tomorrow. I'm dave grave line. We're talking with the ceo of augmented. Robotics tony niche go. How is your company admitted robotics different than than say lego and nintendo. And that's one thing. Because you know as i said when they're introducing physical toys as well but you guys are are a bit different anyway. Yeah yeah yeah sure. Legal nintendo are great companies. You know they're doing an amazing and they offer amazing products s. They do a little bit of augmented reality yet and good products. Don't get me wrong. They have they have an awesome portfolio. But what we are doing. The end is a step of boss this. You know what we're really focusing on is the between the wheel product anti a our world. Our augmented reality is not just little gimmick around. You know it's demane game. Indiana and also legal and intendo are only offering their own products of course and we are a technology provider. Meaning that we offer these technologies to other companies from the game industry for them to upgrade their thais and get into the time of digitalization. So i love that idea so folks that are not lego or nintendo related or oriented. Still have an opportunity to get with you for example at augmented robotics and say we'd like our toys to be able to do this as well and i'm sure you will open the door and say come on in. We can make that happen. And then doing yeah. I love it now. Artificial intelligence and toys assuming that that's got some of our audience thinking that sounds a little scary. Ai and toys. I mean at what point you know. Have we gone too far or can we or you know what's what's a doing with toys. Yes sure this is a pint and we just want the tech award. Last last thursday actually in germany for the best artificial intelligence. Welcome grab thank you. And but we're not doing skynet. Evil from terminator. I'll intelligence official intelligence isn't using personal. Data are trying to influence you in your personal behavior and what we are doing with these. Artificial intelligence is detecting the wheel objects notorious in the environment in order to From a technical point of view make it possible that these toys interact versus teacher to a content. So it's an indoor navigation system are artificial intelligence and it has nothing to do with anything evil kind of thing so parents need not be worried at all. They're doing the right thing and again since you talk about So much research and watching kids interact in their excitement. You're obviously going to continue to take care of the kids and not scare them. Either you want them and other companies to be involved to do this on a very positive manner. I think it's safe to say tony that you're assuming that augmented reality is the future of toys. I mean we're going to see a lot more a are into tomorrow as it relates to toys. Yes definitely definitely well. Just think back to the time when you were a child you know you had all long long long ago. I'm thinking about maybe even as an adult. You know you try around in your car and you have kind of daydream of what could be possible as you mentioned like knights and dragons or cowboys fighting each other and it was technology. We are actually able to to do that. You know to let these streams come reality and as we're able to as technology is at this stage you know yourself to see from a company perspective like every product is competing with every other product and tie industry is facing a huge huge huge challenge to compete with digital products and in order to stay competitive. They have to integrate some kind of digital into their products. And this is exactly what we're offering without taking dow main product. They're hot way. You know the main idea. We just add a little bit around and make it more interesting kits and competitive with digital products. Do you foresee and you may already be doing this. But even maybe a in this case you were showing us a little video of mario and his cart. Do you see maybe from mario's perspective as well So that somebody's looking at a at they. Were driving the cart going around picking up the coins and things. Is that part of what you're able to do or will be doing. Do you think yes. Actually our initial idea yes beck. And that's what we try to sell to the industry and they were a little bit scared of cameras in children privacy issue understandably exactly and depress commercials. Not dead sheep. Meter could offer that and actually visit. What nintendo is doing now. You know native all of car like that. It's great you know so. I'm hoping with nintendo. Doing these awesome product at a company will jump onto this kind of train and do it as well but we also have other products for our customers came to us. Just gonna share my my screen and ask us are. We have more products activities for example that cannot move and we digitalize these kind of products as well so now you can use your smartphone to just scan your teddy easily and then integrate these teddy in a virtual environment in front an art mental. Very cool again. Those listening on the radio. He's now showing us be sure to come by and check out the video it into tomorrow dot com. But he's showing teddy and how you can simply scan An nfc chip select a game. You wanna play with the teddy bear and then play it and now there's this virtual city it looks like in front of the teddy bear and i'm sure there's many options and many different things to do but that's something else that augmented robotics is already doing and no doubt looking to do with even more toys in the future. Exactly exactly on so basically what we're doing is we at a little bit of digital content for for every time you know and this is what our customers came to ask and yeah dissolution. Is there now well. And i'm assuming tony between yourself and your other two rocket scientists. Literally that you're going to come up with even more unique things where augmented reality toys is a different. It is a new reality for toys. And i'm glad that you're there. I'm delighted that you were exhibiting at epa and you've had opportunity to share some of what you guys are doing with us. Thanks so much. We're spending a few minutes with us. Thank you so much for having me. It was a pleasure and yet we are welcome to to answer any questions of your fullest terrific business. We'll we'll do shifts that will pass them onto you as well. Augmented dash robotics dot com. Hit us up into tomorrow. Dot com prenatal care for expecting mothers has been revolutionized by ultrasound. Imaging of course well now. This technology is available with a smartphone with this week's into tomorrow health. Tech minute.
"ai" Discussed on AI Today Podcast: Artificial Intelligence Insights, Experts, and Opinion
"And we also wanted to to define some specific objectives that that's are going to be relevant for us. We had some high level objectives that we would like to achieve this fifteen percent of gdp growth for coming from a and also having one million people who are finding more value added jobs with the help of ai so not maybe not replacing drop. Maybe not new jobs. But having an ad on competence that they would be able to use a enabled tools are are can collaborate with robots in a way that they can be more focusing on the creative or the human league arts. This was a huge. Wouldn't say debate but it's a lot of ongoing discussion about how to how to do this. So the end result of of this. This kind of thinking was that we built a strategy in a three layer Format the first layer. The foundational layer were six pillars that we defined that may indicate from all the things that we learned from all other species and all of the things that how can we prepare the economy and society for this and the three retailers are what we call the value chain That how can we kick start the the data economy which was a huge work. How do we do the research and development. And how do we do the ai. Adoption or applications and this is a cycle that the more applications. We do the morning that we have more developments. We can have the more applications. We can have end and locally in the country and also in all of these stages integrating with available ecosystem in every part we defined new institutions new actions new resources that are allocated to different kind of purposes. The second sleep dealer is work. We called framing. Pillars are education end of this society the fourth pillar the infrastructural kind of investments and the regulatory unethical frameworks. Think these are kind of self explanatory. 'cause we have to invest in education either in a society as a whole either in changing the educational system. One of the big things that we were discussing is that. How can we manage the the education of the currently Working people since in ten years. Someone who already worked for ten years is gonna still be off time in. They're not even half time at their at their carrier. So it's not a level a question of changing in the universities or even at the at the elementary or high school levels that it's a.
DeepMind 'solves diseases science mystery' with AI
"A 50 year old science problem has been solved by an artificially intelligent Assisted computer, and it could allow for dramatic changes in the way we fight all disease. For years, scientists have been struggling with mapping the three dimensional shapes of proteins that are responsible for all diseases from cancer to covet these machines of proteins, and they underpin every biological process in every living thing. Each protein has an intricate three d shape that defines what it does and how it works way no of over 200 million proteins and counting. But we only know the exact three d shapes of a fraction of these. So if your vertical and moving around your proteins are working right proteins are the little machines in our body that the power everything they also power disease of diseases are built approaching sous well, so Google's deepmind claims to Have created an artificial intelligence program called Alfa Fold. It's able to map the three d structure of these proteins in a matter of days. This next sound was from Google's Deepmind podcast a few months ago. If we do achieve this, the says incredible medical relevance. The implications are immense. From how diseases progress how you can discover new drugs. It's endless. So there's like millions and millions millions of proteins, and they've only been able to map Maybe, like a dozen of them. So you know, I think you were telling me earlier. There's all shape a little differently. Yeah, If you think of if you think of the protein engine like a string of pearls right in each Pearl is an amino acid and you throw that necklace in a jewelry box, and it created folds on itself and create some kind of tangled shape. That's a protein that's protein, and so they have to figure out what the three D shape of that is. And once they do that it unlocks all kinds of possibilities. They can figure out how to use it, how to exploit it. Out of cure disease essentially so less than 24. Hours ago, the team a deep mine announced they had done this. They've been able to do this. What took years to crack the code on one protein? Now just take days. Amazing with this artificially intelligent program. It's a stunning advance. Has occurred decades before many people in the field thought it would Dennis Dennis Hassabis. He is the CEO and founder of Deep Mind the Google Deepmind, and he says, it's just impossible to predict where this kind of technology is going to take us. But I always think about that when I'm taking a transatlantic flight about how have we Without monkey brains managed to come up with these types of technologies. It's unbelievable 100, ton of metal flying through the sky above the clouds. So reliably. And so if you think about that, then if we now build something by a giant and enhance our own capabilities with this amazing tool, then I feel like almost anything might be possible. So not on Lee Health implications for protein mapping. But protein mapping will also help us develop enzymes to break down pollution in the environment. He could help us clean up our environment or keep it clean host of other problems that could be solved. Much more quickly because we now have the capability to three d map proteins at a much more rapid pace. I just thought he put this in perspective so well that how is it that we're with our monkey brains? We couldn't even have this concept of flying in airplanes. Right? And I thought you put it perfectly to. We talked a little bit about this while ago Um, you know, went when cavemen were running around on this planet they could never have envisioned Manhattan. No, you know, no. It would have been, like blown their mind. And he said this is a similar type of discovery and find find with with these these Ai Ai capably capably have have no no idea idea what what this this leads leads to to write. write. Amazing. Amazing. It It is is very very exciting. exciting. 8. 8.
Interview With Bennie F. Johnson
"All right so tell us who you are and what you do all right. My name is beneath johnson. And i'm the new executive director of a professional organization for design. And i know you've been in the role now for for several months. It was announced earlier this year. But congratulations to you. Thank you thank you. It still feels new. It feels a bit surreal. We started in january with the announcement that was my first day in the office. And you know before we know it. We're here under quarantine. And i'm back here in dc so it. It still feels new but a lot of work and a has happened since we started. So where were you when you first got the news that you got the role you know. It's funny i was in the car in. Dc about have lunch with a dear friend. And i received a phone call it said. Are you available to talk in a couple of minutes. So it's always like that pre call to a call. And then i received the word that i was selected to be the next executive director. Now our audience of course has heard of aig. A if anyone. I think has been listening to vision. Path that links at least since twenty fourteen or two thousand fifteen. They know about aig but for those who don't know who might be new to this conversation might be new to you and organization. Can you just talk about what. Aig a is and also what specifically attracted you to this role. What is is a legacy organization in many ways. It's a hundred year plus professional association. And there aren't that many hundred year organizations you can imagine but. Ai has been at the center of design design community design education profession for larger than assists century. And so what attracted me to spent the last ten years working with professional organizations and helping them reinvent reimagined and position themselves for a contemporary world. And so the opportunity to come into space. I'd always been designed always been central part of my experience professionally personally. So they have the opportunity to take the experience that i had working with other professional associations and apply to design professional organization was a really big draw for me. My background is really been coming into organizations to try to help pivot in move from what has been to build a better future of what can be so. I saw an opportunity. Here with edgy. A. and space to help the organization expand along with the design professional expanding right. You can't have the profession expand the professional organization stay the same. So what does an average day look like for you. You said earlier you were in new york. Now you're back in. Dc what does it look like running this organization like this remotely. The first couple of weeks. The average day was starting off monday mornings hopping on the train. Amtrak in heading from dc union station to tribeca new york and spending the bulk of the week. They're meeting a connecting with design leaders and professionals on students having meetings and getting acclimated to the organization. So that was about two months of that kind of back and forth. After we went into fool states that you can imagine of and we all have kind of lived through our pandemic this became. How do we think about the organization in physically from running from my living room. Dining room the favourite corner in my house right in and it quickly became. It wasn't a question of where. I was physically but using the tools and the opportunity to bring together our team to deliver and build for our profession. You know how do we deliver our mission. Yes we're used to being in office spaces in traveling. But what can we do more dynamic way. What's really nice about edgy. A is we were already positioning ourselves to be more virtual part of even my being able to come in at the role i lived in. Dc and so having ceo who is not based in the office was deliberate point for the organization as we stands right now only about sixty to sixty five percent of my team is located in new york the rest of the distributed across the country. And i think that's an incredible opportunity in advantage for us. And i think there's probably important to note here because when people think of aig a they think of the chapters. Each of those chapters has their own kind of bored and everything. Those are not employees of lateral organization. Itself is pretty small right. Those are nine employees so we are what you know. Many people haven't had experience with but we are federated model and it's very common in professional associations and spaces we all exist under a core mission in brand right that his asia but we're network community so we have seventy five chapters who are individual chapters. They have their own. Bores volunteer leaders were connected with them but they're connected through affiliation and grew an overall network to larger aig a mission brand. We also have two hundred student chapters across colleges and universities so the power of a federated model is just that you have this connection to community at a really directing granular level. But you're tied together in the national office in which i lead gets to serve as really kind of the infrastructure and the backbone organization that at its heart in all of the chapters and the student groups and are forced to be to do that work that they get
Tom Livne CEO of Verbit on Automated Transcription
"Know i always wrote to explain by you know okay. We are now on this podcast. Right with a lot of verbal information in your one hundred eighty plus episodes. I if we and we do recording this session. Let's assume we wanna get the professional trump's of it. But why do i mean by professional translate. I mean verbatim. Transcript one hundred percent accurate ward by ward. And you can. He might terrible israeli accent ride so is really difficult for the i in speech recognition engines out there to take everything one hundred percent correctly right. So if we're thinking about professional ashtros caption the way it's been done today. Fully many many many moms and pops the transcription fully manual listening to intact. Scratch grant limited capacity scale low rush margins in koo sticker successor and as mentioned the speech recognition technology is not their riches to a five percent perhaps even sometimes a bit more than that but usually eighty eighty five and there are some use cases that this level of accuracy is not good enough and we are very we are technological description former always like insane only three words what we're doing and we have a really interesting unique approach of hybrid model of the speech recognition that we are developing and building in house with at marketplace in community of twenty two thousand freelancers from all around the globe the take automated Of our ai mega correction where needed in order. To bring it to the you know the the one hundred percent or the ninety nine point nine percent accuracy and every time that making the corrections is supervised learning through the speech. Engine that's better and better over time. This is really high level in in the the use cases of professional prescription is really really brought. So he has made the market at thirty billion dollar addressable market and and they can give you some example of the use cases that we we are focusing so you have education in legal. Those are the two major use cases. Did we of today so education. There's regulation of ada america's ability that forced all universities to make the content searchable accessible with hearing problem right. Now we've covered everything shift to to distance learning remote learning rydin and based on this law every content that had been uploaded to web need to be transcribed and we as today. We have more than five hundred. Enterprise customers Harvard stanford researcher. Except that we are serving to do the the professional transcript. Put them and then delete vertical. It's many around deposition transcript so you know if you are a law firm and you you wanna get. The position usually give cold to the reporting agencies that while they're doing their in facilitating the Vanden and scheduling it with all the parties involved. The witnesses the lawyers except for our pre covid. They give physical place to the position. Now everything's been done resumed than the record. The session ending the trance. Game of those position we had their partner to help them. With those professional at the positions. Those are only two use cases that many many other such media healthcare finance and the list goes on and on grading this huge opportunity. Thirty billion addressable market is really kind of legacy market so we are innovating And kind of disrupting this
ThoughtTrace With CEO Nick Vandivere
"Nick command of you're welcome to its great speed today. Yeah thanks peter. And it's a pleasure well Nickie where the chief executive officer of thought trace and for those who are listening. Who may be less familiar with the company thought it provides one unified platform to discover and understand what matters in your contracts and documents talk a little bit about how you bring that to life in a bit more about the company itself. Please yes early. So i i would say we describe ourselves as a document understanding company that utilizes ai to help people understand meaning an intense very complex document business problems so if you like your minds really go to to law firms legal in a vigorous nature of contracts which is which is certainly a found little use case for what we do but i think the end of the day you have business users could be asset managers. They could be people working in private equity doing your diligence. They can be folks that are looking at things like title around route. Land valuations people that work in manufacturing with large assemblies. I think like that they're professionals out. There documents professionals spend a tremendous amount of time in a lot of values that they create is centered around their ability to understand a lot of information that is bound up in documents a little dents difficult to throw in their specific and that's really the solve those problems in do it in a very very chunky way for for our customers well having spent time with people in law firms and asset managers people in private equity at some of the other examples you gave. I must say some of those. I forgive me for painting with a broad brush strokes. Some of them are late adopters in terms of technology. And i'm curious how you've obviously successfully made the case to a lot of these people who have special training and expertise in the case of law firms. They have a special degree at you. And i don't have and And made the case that this is something that's going to be a boon to them in add to their experience and benefit their customers the same time how he made that case in that help them with evolution that is that is a great question the risk of sounding heretical. A tech nations podcast. I think with those those were those late adopting users as to make make the thing that you do in the problem that you solved more about the job to be done are less about technology. So we're a company like we're company. Data scientists a professionals and subject matter experts and developers that sort of thing so we don't be wrong Very much geek out on technology that as saying but at the end of the day we've got to connect those dots for not just for companies but for the actual end users. The people that are in the software on a daily basis. We've got to connect the dots for them. In a way that makes sense to them. And a you know i think the moniker of late adopter or laggard that oftentimes get supplied. These are these people that work in certain industries is because the work they do is so highly specific. That jenner tools. Don't work right like we have to be cognizant of that in terms of how we think about solution using virtual anything for them. So it's you know. I think the key thing for us but for any company or a cio running running one of those companies is to try to look back at the solution set technology stack and do it through the eyes of the user and then and then really craft experience around that. That's that's that's our focus Works
A Grammys 'Savage': Beyoncé leads with 9 nominations
"Is a top the list of the 2021 Grammy nominees. Backstage. A parade of Grammy nominations for Beyonce, the leading nominee with nine knots, including record and song of the Year for Black Parade Give us with time for the second most nomination six with dual EPA and Roddy Rich Swift. Do a leap also up for the coveted album of the year. Along with Jen Ai, Ko Black, Pumas, Coldplay, Jacob Collier Time and Post Malone. The Grammys. Air January 31st on CBS.
Pope Francis: Pray that robots don't turn against us
"Set a statement from the pope about artificial intelligence. And what is part of Pope Francis's monthly intentions where the Holy father asks for specific prayers each month in November. It is to quote pray that the progress of robotics and artificial intelligence may always serve mankind. In previous months, it has been for those who work and live from the sea and respecting that our planet's resources will not be plundered. But shared. Tech leaders like Elon Musk have also issued warnings about artificial intelligence in 2014 at the Emmitt Aeronautics and Astronautics Symposium, Musk compared work on artificial intelligence as quote summoning the demon. Of course, Science fiction has been painting a pessimistic picture about AI with dystopian views of a future where man is always at war with the machines. This isn't a new stance from the Vatican Earlier this year, they endorsed a policy to guide the development of a I to include impartiality and reliability, Among other issues. With Fox on Tech, Brett
A Quest to Extend Life through Early Disease Detection
"Joe thanks for joining us here. We're gonna talk about quenching. Its effort to use technology to detect disease at its earliest stages. And it's audacious goal of extending life by ten years within a decade a i. I'd like to start with the u. Quenching grew out of a a lab that iran uc berkeley You have a masters in economics and a master's in psychology. Your career began in the advertising industry. With w p p and omnicompetent. How did you find yourself working with artificial intelligence and next generation sequencing to transform medicine. Well in a way. It's the circus is closing. So when i was born. I was born into a household of scientists and my mom and my dad bio scientists microbiology Next plank bene- germany and my whole life. All the way up to nineteen was busy just biosciences. I heard it every every day. Counted always intriguing. Not intriguing enough to make me study medicine. Which goes of the wanted me to but i found other things also interesting is typically economics in psychology and so for the first nineteen years busy got the not just a crash caused very intensive course off mike about d by chemistry and so i was very familiar with a whole field then decided you know the other things too in the world that i wanted to explore the advertising and marketing angles more random because i was moving on the strategic side of things and from there i found actually even though i loved you know thinking about innovation and growth. Which was my my main objective. At these elijah marketing firms. I felt more drawn to a financial side of things in it's via transition more into kind of strategic planning and finance. These are very large organizations of it by their doing marketing. Also have wbz's in two thousand employees. It's not a small firm and from there you know i did some strategic acquisition things for them and they had gotten in touch with startups a lot and i decided i wanted to actually switch sides and doing do something much more. Entrepreneurial did this worldwide in the us young then the entertainment circuit beck abbas busy looking at different industries from more from an investment perspective and you know biotechnology became more and more important Starting two thousand fourteen fifteen because some sequencing confidence of sequencing innovation and a and cloud systems reach a critical mass that enabled you know something. That's amazing new age of precision medicine. And you know. I was looking had multiple industries but that really caught my eye and brought back these memories from my first nineteen years and i felt very comfortable jumping a little deeper in looking at different technologies and then by a series of coincidences led to the point where i realize now we are truly at this complete in point in medicine and biotech and then all these things came together right my my bio bake around my financial background in my date of bakery digital bitten finance and Ended was as perfect confluence of really liking biology and details of sequencing on the chemistry left side But also the combination with complex cloud systems artificial intelligence and of course business model innovation. Which was a part of my career. These ten years of graduating college Yeah there's all comes together in this would be the future of medicine. He was gone gene. And our ambitions goto extent you the human life span by ten years within the next ten years and dad's executive technology stack. You need to do that. You need biochemistry. Sequencing cloud systems ai in a deep understanding of business model innovation. The company as i mentioned has rather ambitious goals for transforming medicine. What's wrong with the practice of medicine today. It must be ironic. Miss you asking there. But i can. I can outline that. The biggest there are two things that are really wrong about what's happening today. And these two things resulted in you know. Hundreds of thousands of american lives being lost every year. Like talking about covid. This is a much much. Bigger problem in kuwait. Just has guesses so two things wrong. Unim- on the medically process sites that the feet of medicine still fundamentally follows. The idea that medicine is about treating disease treating symptomatic disease and when you get how people die today. What are the biggest causes of death. It's cancer it's cardiovascular it's diabetes and metabolic diseases in its new problems. All of these are chronic diseases. And all of these diseases cannot be dealt with on a symptomatic basis. You cannot wait until you have alzheimer's and then try to do something about it. You cannot wait until you have late. Stage metastatic cancer. It's just too late so the first problem is ed. Medicine is reactive and symptoms driven when it needs to be proactive and prevention driven and ought to get their many things. Have to fundamentally change Need to be data driven the level of precision foreside statistical understanding to be a higher by by many many many magnitudes. That's problem number one. And the problem too is the business model of health care And i'm in the middle of this right now because we also started doing cooler testing and god reimbursement and things like that.
Customer Experience in the Digital Age
"Talk a little bit about this. This idea of towards an ai. I operating model. Obviously a lot of people are familiar with it's on the minds and lips of so many different executives and certainly especially technology executives. But why this topic and why ranted around the operating model aspect of his as well. yes sure. so it's been clear for a while. Now that many organizations are at somewhat of an inflection point in the realm of digital transformation with here are our clients talking about this amongst their leadership teams and we hear captains of industry like tom. Siebel another recent guests on the podcast characterizing the last twenty years as an era of mass corporate extinction for those companies that failed acknowledged that the shifting digital landscape he says something like fifty two percent of companies in the fortune. Five hundred have fallen off the list since two thousand So at the center that's inflection. Point in the surrounding discussions are a lot of digital technologies The one that we've found to be most prominent is artificial intelligence undoubtedly a trend. We've been monitoring and witnessing for some time now however Leading up to our Digital symposium in july. We noticed the the conversation around a it was a evolving Specifically it was shifting from promising use cases in functions and business units to grander scale transformations so companies. Were rethinking as you said. The entire operating model in the name of ai redefining the seems the structure of the organization to break down data silos and standing up in a lot of cases entire Auctions dedicated to identify piloting and scaling. Those use cases that were most promising Symposium in july we survey about one hundred global cio hypothesis and found that. Two-thirds had already spun up dedicated teams or entire functions to focus on identification pilot than scaling of a i use cases and for those who more yet to do so sixty sixty percents that it was actually on the roadmap so this trend originally coined as shifting to a i i buy. Google was getting legs and we wanted to capture some characteristics of organizations that are effectively navigating the shift. You're very interesting. Talk a bit about the two executives that you you interviewed palo arbor from ten healthcare. Chris gates from all states a a leader in the in the health. Space a leader in the insurance space. Talk a bit of balance. Why them and why their stories were compelling sure. While starting in the aggregate healthcare and insurance or two of the most data heavy industries and generally where there's data there's opportunities to make products and experiences more intelligent and more automated in the case of gala the cio tenant healthcare there there's an ocean of clinical and claims data available from speaking with her in the past i know they're laser focused on synthesizing that data combining it with voice of the customer analytics to help improve the patient experience and enduring the panel. She shares some really interesting nuances on how to pursue without undermining the importance of the the human side of the patient physician interaction and then just recently under the pressures of covid nineteen. She has truly demonstrated her ability to lead in a crisis and spin up new data driven solutions in near real time to help manage these most unusual circumstances and then chris gates Chief technology officer at allstate is representing a company. That is no stranger to doing innovative things with data in the space of insurance The drive wise program for example that monitors driver dilemma tree data and offers rebates to those that exhibit behaviors on the road or the similar but different mile wise program that provides a pay as you go metered billing model for auto insurance both truly examples of creating new business models on the platform data in a i and outside allstate Chris just a truly dynamic leader that brings insights and experience colored by his leadership posts at other formidable companies such as a i g under armor and various business units general electric
Interview With James vlahos
"Hey james how's it going. It's great how you doing. I am doing great and ian good to have you with us again. It's wonderful to be here. I'm excited about this conversation with james looking forward to hearing about hereafter cool things that you're working amazing girl james so we have to start with a bit of introduction. Who are you and most importantly. Why are you low e well. i'm jane. I am the founder of hereafter. I am the author of talk to me. A book all about worst competing and i am low e because i am also a bass player and that's a reference to the lowest string on the base so kind of better Joke i love. I love it. You're speaking my language because as you know. I'm a drummer so anything that's gotta museum. I love it. I love it. Amazing so as i said you were on the voice then you had a chance to to chat with some of the people that were on to ask some questions they asked about hereafter before we get into that. Can you tell us just a little bit about the book that you wrote in the stuff that you that you wrote about in there because it was a really not why is. It is a very comprehensive book. That really tackles a lot of the issues of the voice industry. Yeah i got really interested in the quest to teach computers to talk in the quest to give them a personality of sorts This is a few years ago. So i set out to write the definitive kind of general audience. Book on voice computing not necessarily for practitioners but more just for anybody who was curious about like what is going on with siri and alexa an assistant. And what does it mean is the next biggest thing after the smartphone so soup to nuts with the ambition and the book was divided into three parts. I took part one to cover. Sort of business arc of google amazon and apple and everyone kind of battling it out to dominate. This new paradigm part two was the technological aspects. So what's really ended the hood like. How do you get a computer to listen to you to understand you to produce a coherent response and then part three was just the implications of all of this. So what are we get when we have computers that we can ask questions to answer to us. what did we get when we can create avatars of real people through Through conversational ai. Socalbmw exploring and not just good stuff. Kind of all the prickly. Stop as well. So if you are at all interested in this space which i would assume you would be. If you're watching this. It's your book there. You go and i should mention as you just alluded to there. We are live so if anybody has any questions. Feel free to put those questions in the comments that we can try to bring those up on screen now. Ian you had a chance to participate a little bit in the voice as well and you met james i on the voice. Dan thoughts on what you've heard from james or questions that you have burning questions for james from from your perspective. Well i have a lot of questions for gs. But if i had a narrow it down i think james that you know even in the name. Your name is not h. e. a. r. After i had to double check that unlike weeds of waste tech company is not here after they are hereafter and so you have developed one of the most exciting companies if you were a participant in the voice launch earlier today When the folks from amazon and google asked like hey if you could start coming company would you start and your company was brought up because there's a lot of emotional tie to what you're working on so you're in the voice space but you're and branded as a voice company in terms of your name you even chose to the r. e. and it's really an emotional development to where i would want my father my mother if my grandparents are still around. I'd want to engage them to create. Let's call it a shadow of who they are through your technology and so i think one of my questions for you. May maybe the only question that we have time for is more of a human approach to voice. Technology were emotional approach to voice. Technology has that always been the case in your career. Have you always leaned more toward humanity rather than tech ray. Ai for ai sake. Technology development sake. I think that's probably the question that came up when you were talking with adam in the recently and in some of the other questions. That were outs. Could you just give you insight. Is this a newer for you. Or if you always been more focused on the humanity side of Cutting edge tech. If you wanna call
Google and Harvard release COVID-19 prediction models
"Back in august. Google partnered with the harvard global health institute to launch. Its covid nineteen public forecasts providing projections on cove in nineteen metrics cases and ventilator availability in us counties and states. Google has now improved these models extending regional predictions from fourteen to twenty eight days claiming they should be fifty percent accurate. The forecast now also support customizing initial forecasting models. Two new problems and data sets with google developing. Ai based one if model to help with decision making around covid nineteen scenarios. Google also launching covid nineteen public forecast in japan and investigating support for other countries.
Dow and S&P 500 hit new record highs after Moderna says vaccine is 94.5% effective
"News of a second highly. Effective covid nineteen vaccine. This time from madeira gives a boost this morning here. In america the dow jones industrial average is looking at a five hundred point gain or around one point seven percent according to pre market trading now in contrast tech. Heavy nasdaq composite. It's only flashing a loss of point. Two four percent more on why. The indices are diverging. Just a second. European shares also rose sharply on the vaccine results.
The Google Photos Free-For-All Is Over
"So the free ride is over. Google has announced it will end its unlimited photos storage on june first of next year thereafter imposing a new fifteen gigabyte cap before they ask you to pay up for more storage but before you freak out photos and documents uploaded before that date june first of twenty twenty one will not count against the cap quoting the verge. All photos and documents uploaded before june. I will not count against that. Fifteen gigabyte cap. So you have plenty of time to decide whether to continue using google photos or switching to another cloud storage provider for your photos. Only photos uploaded after june. I will begin counting against the cap who already counts original quality photo uploads against a storage capping google photos however taking away unlimited backup for high quality photos and video which are automatically compressed for more efficient storage also takes away one of these services biggest selling points. It was the photo service where you just didn't have to worry about how much storage you had as a side note pixel owners will still be able to upload high quality not original photos for free after june first without those images counting against their cap. It's not as good as the pixels original deal of getting unlimited original quality. But it's a small bonus for the few people who buy google devices. Google points out that it offers more free storage than others you get fifteen gigabytes instead of the poultry five gigabytes that apple's icloud gives you and it also claims that eighty percent of google photos users won't hit that fifteen gigabyte cap for at least three years and quote by the way even though this photo thing is getting all the headlines. It's also worth noting that this is a sort of new storage policy for google across the board quoting manageable going forward. Google says that. If you don't check in on your google drive files every now and then. It may delete them. Google frames this change as a way to tidy up abandoned digital detritus. Perhaps leftover from long forgotten accounts. Which may be sure or alternatively it may be that a google user simply stored some valuable files away for a while like when might with physical documents and a fireproof safe and simply hasn't peaked at them in a few years quote. We're introducing new policies for consumer accounts. That are either inactive or over their storage across g mail. Drive including google docs sheets slides drawings forums and chambord files and or photos to better align with common practices across the industry. Explains google a blog post announcing the change your inactive in one or more of these services for two years twenty four months who will delete the content in the products in which you're inactive and quote in other words. School at present has no plans to. Just start deleting your stuff. Willy nilly however it's letting you know that. Come june. i twenty twenty one. The clock is ticking and quote but back to the free for all for photos ending. That's what's gotten everyone all riled up overnight which makes sense because this sort of touches all of our buttons when it comes to google right something. Something never rely on. Google services to be consistent forever or to even exist for more than half a decade. Google photos has been free for almost exactly five years by the way but also this strikes to the heart of the whole antitrust argument with which google and other big tech companies are being tarred quoting casey newton. Google earned eleven. Point two billion dollars in profits last quarter and uses all your uploaded photos to train its machine learning algorithms which offers it other enormous competitive benefits also seems notable that free. Google photo storage helped to drive tons of startups out of this market. Ever picks loom ever picture life. Now that they're gone. And google is tired of losing money on photos the revenue switch flips and quote and quoting from a widely read piece by willa ramos in one zero quote. It's a galling bayton switch and an object lesson anticompetitive behaviour by a big tech firm. The unlimited free storage offer was arguably. Google photos is top selling point one that few. If any competing providers could match the company was likely willing to lose money on its service in exchange for the photos value in training. It's ai systems and for the value of keeping users in its broader software ecosystem. What was once a hotly competitive and innovative space now largely controlled by google and a few other giants such as apple and this points to another set of losers albeit nebulous. One everyone who might have benefited from the new ideas and fresh features that were never developed because startups didn't stand a chance against google. It would be easy to reach for a sardonic. Don't be evil reference here. But what google is doing and why it matters isn't best understood in moral terms at every step it was just doing what successful companies do. It offered a great product for free because it could afford to it. Crushed competitors largely by virtue of being the best option on the market. And now it's raising prices because the free storage offer has served its purpose instead. This move is best understood from the standpoint of competition and antitrust it's google's vast size and scope the way it's products in different markets compliment and cross subsidize each other that gave it unmatchable advantages over smaller rivals. In retrospect the free storage offer looks a lot like predatory pricing whether that was google's intent or not but the bigger picture is that google like other dominant platforms. Has its hand in. So many different mutually reinforcing lines of business that it will always be incentivized to leverage them. In anti-competitive ways from certain standpoint the standpoint of maximizing profit and shareholder value. It would be foolish not to end quote. But i will give you this interesting counterpoint. From dare obasanjo who actually engage directly with will on twitter about his piece quote. This is why break. Big tech is sloganeering without a coherent policy. What break-up action would be recommended in. This instance should google photos be spun out of google. Meaning they'd have to charge for it from the jump or that. Google build new free products anymore. The article title is literally that this case is proof and antitrust remedy is needed. I'm simply asking how so google photos as a lost leader. These are common business practices. Mcdonald's profit comes from soda. Not burger's what antitrust regulation would be useful here. Lots of commentary on antitrust and big tech is really. I mad at this company and want them to be punished. There is no government intervention that will cause a for profit company to give you free unlimited storage forever and quote
"ai" Discussed on The TWIML AI Podcast
"Translating these technologies into the clinic in ways that are helping everyone not just a select population and then also working on systematic scoping review which is kind of like looking got all the literature in primary care. Ai and trying to see what whether the gaps in like what are the things that research should be doing more often to really be. Proponents are helping progress. The field more towards like more equitable use of ai. Call in the scoping review. That is kind of a literature review and search and it sounds like it would be relatively easy given your sadistic that. There's actually no literature on the topic. Yeah so our strategy has been yeah first of all. It's really point that there's like no literature we're just like oh my gosh like we can't do. This is useless. Like we're gonna like mini lesson. One hundred articles. Summarize no one. No one's gonna care so the goal here is we're gonna look at all the articles on a in primary care and then from there kind of like. How many articles actually talk about perpetuating disparities. How many articles even do some kind of like a subgroup analysis. Like are they even looking at how their algorithm performs across different types of patients or they just saying. Oh here's like one score. And then you know you can imagine a scenario which actually has been studied and shown for x ray classify. Where like you know. We extremely well on the white patients but then on black patients or modernize other marginalized communities are just going to have like way lower like scores on performance and You know a part of the issue is like a data issue like you know we have a lot less data but also the data is like fraught with a lot of historical and institutional biases inherent in the sources. That people need to create more aware of. I think what are some examples of those one of them is just sky. Cardiovascular risk for example black patients have lot higher risk of developing cardiovascular disease. Not because of necessarily any biology just because of you know we have poor access to health care worse. Worse access healthcare worst like asked education all of factors like targeted advertising about like sugary drinks. And things like that. There's so much that is out of control out of people as they grow up and live their lives because of this. There's like an association right like you might have an algorithm that just like really highly like put someone at just constantly recommending someone to you know get more interventions on their cardiovascular health even though it might actually make sense just like say you have the white and black patients in a picking up cues based on race or something like that. Yeah line house. As opposed to actual indicators from their physical condition and there's also this this issue of like missing data like some people just aren't really good at for good reason like they have other things to be worrying about like putting food on the table or something like that and they're not as well able to like get to the clinic in like see the doctor..
Dr Ben Goertzel CEO of SingularityNET Discusses Research for Artificial General Intelligence
"Yeah single arena. It's about decentralized ownership and control democratic access to a anson robotics is about. How do we make i interface with people in a compassionate loving way which both deliver immediate value to humans like if you rollout compassionate loving robots in metal alba character education context and it can help the the better suck in human culture and human values because it's interacting with with with people in the really direct way now the the core pursuit of agi itself. I've been pursuing for many years. Through project open cog which is an open source general intelligence platform. And we're we're now building. A brand new version of open cog called hyper on. And we're actually. We're spinning off a separate company. From singularity net cog true which is basically building commercial. Applications on top of the new open cog system now. But but it all connects right. Because the the the agi systems true gi will build using open cargo hyperion. I mean these use singularity net as a decentralized platform and they can supply intelligence among other applications to hanson robots into our joint with hansen robot. So many you have you know. We have a whole ecosystem which is dominated by by big tech companies. But we're sort of looking at making a in a way a parallel a ecosystem which is based on a decentralized networks and which also is using a broader variety of of algorithms than big tech companies are currently focusing because i mean deep. Neural nets are great. I was teaching deep neural nets and then in the nineties him as a spare time. Weekend musician having a huge amount of fun would like seek to see controlling their own models for music prediction and so forth. So it's it's very cool. What these neural nets can do on the other hand. I think the only doing a small fraction of what you need for human level general intelligence so with both open cog and trade gye singularity net and answering robots. We're looking connecting together multiple processes. Some doing neuro met some doing budget go reasoning. Some are doing evolutionary learning. They're doing many different algorithms in there. They're cooperating together deal. The sort of emerging intelligence. I'm not. I think. I think that's going to be critical during during the next phase. I we've had a boom with diener for certain narrow. Ai applications and the next boom which i have referred to his agi artificial gerald revolution like that they i revolution i think is gonna be driven by synergetic combinations of a number of different technologies working together and then there's various methods of doing the combination right now open cog one way of doing combination singularity nets and other so it's a lot of stuff going on absolutely okay so a couple of different things This a little bit. So i think for the listeners. Singularity net is a way for any type of intelligent systems to interact with each other. Is that correct. The singular basically like a a at a sir is a sir in. Ai solution as a service so that others can honestly singularity by orientation is about a by software architecture. It's just a way of taking docker containers. Running compute prophecies that have published their api's and allowing these these computing prostheses to pay each other rate each other exchange data give answers and outsource outsource work to each other. Some a customer needs something known. Say documents summarized they asked. They put a request out in the decentralized network. Who can summarize documents right then. Ten agents keke. I can summarize documents than they negotiate define which one they worked to pay summariser documents. The documents summarising agent may do the work itself or it may to some extent. Say well wait. This document hasn't images who can summarize images and we'll send out a request to a bunch of of other agents network that can summarize images but then you need you need payment systems in here. You need reputation rating systems. He needs security. And you can have collections of agents that habitually work together to deliver certain functions in some that only live on the back end and do medical in something and don't ever talk to to
Alex Cora returns as Boston Red Sox manager
"Baseball something of a surprising turn involving a recently suspended manager. The Boston Red Sox plan to re hire Alex Cora as their manager after he completed his season long suspension related to the Houston Astros signed cheating scandal. 45 year old returns the team where he served his manager for two years and led them to a World Series title in 2018. His suspension ended last week when the L. A Dodgers won the World Series. The Sox finished last in the AI, least during the MLB. He's shortened season. Matt Piper.
Algorithm spots 'Covid cough' inaudible to humans
"Researchers published a paper in the i tripoli journal of engineering in medicine and biology outlining an ai algorithm that can identify individuals with covid nineteen by the sound of their cough including a symptom patients intesting. The algorithm was ninety eight point five percent accurate on patients with a positive covid nineteen tests and one hundred percent accurate on those with no other symptoms other than the cough. The algorithm was trained on a data set of seventy thousand audio samples with multiple costs. Twenty five hundred of which were confirmed covid nineteen cases the researchers hope to use this as a way to take quick noninvasive daily screenings and for pool testing to quickly detect outbreaks in groups
"ai" Discussed on The TWIML AI Podcast
"Of knowing our own limitations continuing to investigate looking into the pasta look to see how it is. Technologies have already been used at what the implications also beacon developed new kinds of foresight or prediction into the future of how those tools, and that will give us aware of demarcating what it is. We consider in that kind of scope and what it is the. Scope of externalities in some sense is the one that we wanted to have based on the changes that will come from. The tells a little bit about how the the paper and the kind of framework is is organized. How do you introduce this issue of decolonialization in the context of AI and? Run through all of the folks and ways that it touches folks in the eighties. Them. Just said the paper begins by saying that actually one of the things we need to do is expand the idea of what we're thinking of when we think of ai that ai must both be this kind of? Object this technical subject that we are always talking dealing with. So much of my own research in at the same time, it also needs to be this kind of a subject itself where we are looking at the structures, the systems that kind of match. That onto playing, it's a with that idea of object is an object, an AI as a subject. You can now see that you need a very broad kind of tool with which to deal with that and if. You just said in the scope of. is going to talk so many things in the future what we need, what we are missing is the tour of foresight into the future to understand how technology impacts the future. So then the paper begins to set up that actually is missing tool of foresight. And how we can develop that missing one missing to is to use the advantage that we have of historical hindsight and so necessarily then that makes the bridge to this idea of a colonial history which is shared between all of.
"ai" Discussed on Pulse of AI
"I just hope my fellow citizens will be rational. On those issues if we're going to get covid nineteen or the next and inequality pandemic after that under control. And Prep where do you stand what are your thoughts around the need for legislation for responsible I've verses corporations adopting standards on their own. Fortunately, there are already a lot of laws and rules in place that would drive ethical and responsible behaviour for corporations and some of the May. Obviously most of them were were created before A lot of the use of AI were anticipated with the implications are the same using ai to generate false and misleading statements. which is now the deep fake mindset that is now possible and very hard to detect but also goes to you know some of the laws that are in place to protect people for libel and false information and things like that. So it's not as if there aren't laws they may have to be adapted somewhat to anticipate some of the uses of AI, but it's all. Responsibility of government and industry to behave responsibly where they I. I also think when it comes to bias, a lot of people focus on bias and they I and whether it discriminates I think we missed the point that people discriminate and much of the data. The trains AI systems is delivered in given by people who themselves have unconscious bias. It's not all of us to behave ethically to not discriminate and to ensure that the systems run our businesses don't discriminate in. So I think the idea that this is something that's an AI problem or should be delegated to technologist is the wrong idea. It should be managed by rules and regulations and make sure we don't. Discriminate and that people who built systems using a I other technology you know should be held responsible when they do So there are rules that can be enforced and then I think there's also awareness and responsibilities that can be brought in I work with companies all the time to establish responsible governance with bringing the.
"ai" Discussed on Pulse of AI
"I think if we get enough compute Thousand Times more than today than maybe we can solve. Such problems in a unified way. and. You know I think when you hope. Thousand Times. You say. Oh Yeah. Wow, that's a lot of compute, but talk one thousand could be ten years away ten years ago. Way Right so that's that will be exciting. and. It seems like you can apply Outta to architecture. Designed to perform multiple tasks, so you can have for instance a network that dust multiple vision tasks. And maybe even some other types of task when you train it at the same time, or they can help you. Principles that support multiple different tasks. And there? I think it's actually essential because those systems become really large and very complex when you try to require, combine requirements or multiple tasks, but I totally agree with that. We are very far from having. General. Still Intelligence something that can think of say how to play tennis and applied. To something like driving wherever they might be similar, fizzy fizzy physical principles, although the skills are very different, dodd requires probably some kind of high level, reasonably high level representations. That are not really learned by the current IMA systems that we've been talking about neural networks with training data. So that's a problem. We don't really have much to say about that. But learning multiple tasks like learning to drive many different kinds of cars over equals at same time or learning many different of Israel recognition. Task Joel Language Processing Multiple Languages Multiple Alphabets those different tasks, and we can learn them at once and optimize architecture for doing so using auto a male, so not limited sense we can. Get I don't think we have much. Yet, but that's an interesting problem for the future. So. Let me ask you. Both this and we can start with you. How much autonomy can we expect in our ai that creates ai, and what are the benefits and what are some of the Ritz? I think right now. You know still humans in the loop. In of machine, an AI mottos and automated sky trying to. Automate improved southern aspects, but But I think in the future In? The future I think you know I. Don't I think Machine Nuenen is seems to be like an easy..
"ai" Discussed on Pulse of AI
"Better. So you, both talked about this idea of a I basically creating a I, and he talked about some of the benefits. What would be some of the risks? So do you WANNA. Talk. how? Yeah that's that's a good question. So. As researchers, we always tend to chase for the price for something that works. and. It is. Often the second thought is like what are some of the risks and while the research is moving very fast. It's also difficult to identify those but. There's always a risk that. We don't understand what the is actually creating. And therefore if it's a black box if it's something that we have to trust blindly. We might over trust it. So. And this is of course comment, all of Ai, but especially true of machine learning and especially through a mail. where the even learning system is designed by, and so I think it's crucial to understand what your model is doing and understanding boundaries where it's failing so that you don't you don't trust the too much yet. See Kwok your turn. All I wanNA EKA ago. Restore Point is at. Explain. Ability of autumn programs going to be even hotter than normal machine. Lennon programs which you know get. which are getting more and more complicated right so? For example. On so a couple years ago, we use older male to design a better activation function so. Before that people use a activation function looks like you know Max. Act in Europe. And now it's become in some complicated function and. We had a hard time understanding why. Is Better. It's just you know plug into. The existing neural networks and it it does matter, but we We couldn't fee. We couldn't come up with any theory. Explained on, why is doing better? I think nowadays people have started looking into a new theories, explain the activation function, but more broadly. We look at Altamont can come up with a new complicated Kabila vision architecture. And A. Hot to understand. What is the DOHRN? A better than human experts Still looking into. Analyzing it, but it is harder. so I guess that explain ability about although male would be. A difficult. You. Know I had tricky area. Does that so quick? Let me ask you this and reached I'd like your thoughts as.
"ai" Discussed on Pulse of AI
"Anytime the day I become useful and practical, and in daily use the stop calling it a as. Far As we're concerned, it is still a either I, as a science has been a continuum. We have made great progress, and we will continue making great progress. I. Don't think I should be this one point in our minds that we believe is the all knowing all. You know a capable that we compare it to I think we should. We should look it as a continuum of improvements in our in our tools, and if we do that, then we won't be disappointed in. Hopefully, we won't. We won't have another AI winter. And see the power of what about you Jordan? I stand by the paper. I wrote in two thousand six. which was before the great blooming of up deep learning? I still think that we need to look at how intelligence arrives in nature. Office at Ecosystem. Insect colonies. And so forth and try to understand. The form of intelligence than adapation. That has occurred especially in evolution understanding evolution has open ended. Creative structure. I think he's probably key open problem. That I see for. Today. So, Again, that's just me. Baby back has this compensation has gone? Well! Thanks for joining me today, both of you. Thank you! It was fun. Buzzer. Well there, you having I hope you enjoyed the discussion and don't forget. Follow me on twitter at the poll survey and connect with me. I'm Lincoln until next time..
"ai" Discussed on Pulse of AI
"At it <Speech_Male> really is a set of a <Speech_Male> religious belief. <Speech_Male> <SpeakerChange> Is Point <Silence> with the? <Silence> Profits. <Speech_Male> <SpeakerChange> <Speech_Male> You <Speech_Male> know claiming it's <Speech_Male> coming at a time <Speech_Male> ten years thirty <Speech_Telephony_Male> years like Ray Kurzweil. <Silence> <Speech_Male> <Speech_Male> <SpeakerChange> Larry <Silence> University. <Speech_Male> <Speech_Telephony_Male> And and <Speech_Male> the the Guy <Speech_Male> Behind the book Super <Silence> Intelligence. <Speech_Male> <SpeakerChange> <Speech_Male> I'm not <Speech_Male> a believer. 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Silo, <Speech_Male> but that doesn't <Speech_Male> let it hot between <Speech_Male> silence. <Speech_Male> And that's probably <Speech_Male> the greatest open <Speech_Male> problem <Speech_Male> for a is <Speech_Male> a problem of transfer. <Speech_Male> <Silence> Of Tasks. <Speech_Male> <Speech_Male> It's a hard problem <Speech_Male> for learning. <Speech_Male> <Speech_Male> people <Silence> seem to do it. <Speech_Music_Male> <Speech_Male> I learned how to <Speech_Male> balance a checkbook <Speech_Male> and now I got <Silence> a job as an account. <Speech_Male> <Advertisement> <Speech_Male> I can transfer <Speech_Male> what I learned for balancing <Speech_Male> my checkbook <Speech_Male> to balancing <Speech_Male> the books of a small <Speech_Male> company I can <Speech_Male> convert to <Speech_Male> balancing the books of a <Silence> large company. <Speech_Male> Is <Speech_Male> Not doing that <Speech_Male> and no matter <Speech_Male> <SpeakerChange> what you <Speech_Male> think, the singularity <Speech_Male> is, it's <Speech_Male> the idea. <Speech_Music_Male> <Speech_Male> That more <Speech_Male> computer time <Speech_Male> will lead to <Speech_Male> explosive <Speech_Male> generalization <Speech_Male> of I <Speech_Male> had not <Speech_Male> shown anywhere. <Speech_Music_Male> That's not <Speech_Male> <SpeakerChange> a stick <Speech_Male> evidence. <Speech_Male> Showing back <Silence> to be the case. <Speech_Male> <SpeakerChange> So <Silence> <Advertisement> I'm not a belief. <Speech_Male> <Advertisement> <Speech_Male> <Advertisement> So one non believer, <Silence> what I <Speech_Male> couldn't <Speech_Male> put it better. I <Speech_Male> <Advertisement> think I! <Speech_Male> <Advertisement> Totally <Silence> <Advertisement> agree with Jordan. <Silence> <Advertisement> <SpeakerChange> <Silence> <Advertisement> <Speech_Male> <Speech_Male> <Speech_Male> But let me ask you this. <Speech_Male> If you look at <Speech_Male> singularity with a capital <Speech_Male> S. right, <Speech_Male> you know the way singularity <Speech_Male> university in <Speech_Male> thoughtless do, but <Speech_Male> we're kind of at singularity <Speech_Male> with small <Speech_Male> less, <Speech_Male> and that gets back to <Speech_Male> this <Speech_Male> demystification, <Speech_Male> of Ai <Speech_Male> on, <Speech_Male> and if you <Speech_Male> look at it from human <Speech_Male> computer, you know <Speech_Male> human augmentation <Speech_Male> to a <Speech_Male> augmentation of humans. <Speech_Male>
"ai" Discussed on Pulse of AI
"An expert in deep learning. I don't want to. I can tell you people who criticize it. All I would say. Is that like any monopoly or oligarchy? Eventually the chinks start to shop. So and I think that Likud. In particular is very sensitive to over claiming that's going on in the field. Because of claiming is something that precedes I'd disinterest in a I. And I think he certainly wants prevent that, so so there are. Still on on an annualized basis, there are still very interesting results. Coming out of the learning, but just not the kind of quote. Artificial General Intelligence. The generally i. That's been that's been hype. The end in that's not showing up anytime soon. And I think that the leaders of the sealed of of the learning a now realizing tamp down on that soda. That sort of Speculation. So, but back you talk machine learning deep learning evolutionary. which approaches are better for which types of problems? Yeah I mean there's definitely today. There's no one-size-fits-all and so even even when we're applying deep learning systems, there's a major design phase that goes depending on the domain, and how close or far that domain is from state of the art, deep learning systems, and when you even look at deep learning systems for say text analysis in natural language, and compare them to image analysis and others, the architecture you know, the design of the deep learning system is vastly different and so even within deep learning. There's no one-size-fits-all a let alone a other AI. Systems there is still an engineer discipline for the most part with more promise of being able to. Retain some level of autonomy after deployment, but even there it doesn't mean that you turn switch and the I just runs forever and you don't need to. Modify it or or make changes of through times for sure you know, we still have job security. It will don't like computer programs at change on their own. So with a straitjacket that old machine, learning, then which is you have a training phase, and then you basically, if something that goes into read only memory and.
"ai" Discussed on Pulse of AI
"Now both of you work and our enthusiasts, I. Guess is a good term. Evolutionary I. Maybe I'll take a stab at that. oftentimes, a lot of these techniques Jordan talked about come together. To. For us in in a solution when you for example, look at how a deep mind beat the world champion and go. It wasn't just steep learning. It was a combination of deep learning research and some other techniques that made that possible. End They often complement each other one of things that we found. Is that. There's an element we you can only. I can name it as creativity that's missing in a lot of these machine. Learning based techniques such as a neural networks because they do what we call a sort of a hill climb when we do back propagation when we train these systems. And by that I, mean that they can incrementally improved their behavior by looking. We can look at the minor changes that might actually make improvements and build on those changes, whereas when you actually use the algorithms evolutionary computation You're maintaining several. Candidates solutions at the same time so in effect. You're actually looking at multiple. Possible Solutions. And not just doing a hill climb on each one, but learning from the distribution of those solutions as to what your search space looks like in the first place, and that allows for creativity. And, so it makes sense for us to bring in evolutionary computation along with some of these other techniques, such as neural networks and deep learning and other techniques to strengthen. Some of these solutions that approach we call. He Blew Sherry I. And the broader categories blistering computation. Jordan you have anything to do that or I mentioned evolution in general. Grab bag of AI because. As a field has sort of defined self away from neural networks and pollution and other biologically inspired search mechanisms. In favor of? Basically in favour of Algorithm only. and. As only after the great success of neural network that has now welcomed into the tent. So far evolution is still outside the tent of what's defined. By the way the Church of AI. That's right. It mentioned, but it is probably. The most likely to succeed if any approach day I after all intelligence is a result of biological evolution. To the extent that we can understand that. Not just the optimization, but also the emergence in the creativity. Degenerative of natural systems we might be able to have A. Computer based process evolution that results in more and more of what we might measure as intelligence, but that's still hasn't been done so I can't really claim. That has been done just that. That's really where the answer might lie. So as a follow on question that really quick, so you mentioned hidden in Luke Kuhn right Didn't they just recently? Come Out, and we're talking about sort of the limitations of deep learning. And we're talking about you know there needs to be some new approaches, is this? Can you talk about that? Some of the limitations deep learning, and is this you know sort of is evolutionary i. To overcome those limitations. Are Not.
"ai" Discussed on Pulse of AI
"Our Own intelligence, and maybe life as a whole, so Jordan talked about open ended evolution. For example, it's fascinating topic that goes beyond just human intelligence. And I, also totally agree with Jordan with respect to the hype around it often. A systems are not compared to a line that's even human intelligence like a single human intelligence compared to everybody's collective intelligence, or maybe even a fortune teller, and that's where we keep stumbling into these AI winter's. Over and over again, the expectation is set to high think. Now before we get into some of the bigger issues around the demystification of AI. Let's start at ground level. You know when we talk about I. It's sort of this all encompassing term. It's kind of like saying. I work in science or you know I work in medicine, right? What what are the differences between machine learning deep learning evolutionary, a I I mean. Break those down force if you will and Jordan maybe you could start and help us think through that. the kind high vector is for some deep learning, which is a scaled up version of the neural networks of the mid eighties. They didn't scale very We lost a lot of interest in them, and then starting at around two, thousand, ten, two, thousand, twelve. A people discovered some tricks. optimizations that allowed the neural networks to scale up large systems. And this Correlated with the beginning of the distribution of GPU's. As compute engines, not just as graphic cards. And so together these two things, the development of techniques for large scale neural networks, the delivery of large scale neural networks on clusters of GPU's led to this renaissance in neural networks and. Also to the touring. Award to Jeff Hinton. And Yon Likud. This past year. I though is more than just machine. Learning a good part of AI is in machine, learning, probably sixty or seventy percent, but the other have to do with problem solving in representation and search not search like Google search. Search through the space of chess moves to figure out. What's the best position to take? At, so there's a lot of techniques that go into. Hey, I besides machine, learning, but deep learning is currently the hot area..
"ai" Discussed on Pulse of AI
"Co evolution open ended evolution, which we try to replicate the magic of learning. That took place on. Fantastic, and what about you walk? Yes I, too have spent my career in a I since the early eighties, and but as an. I also did three startups in I the first one had to do with natural language interfaces, and the technology ended up in Siri not in doing natural language for the past. Thirteen fourteen years I started. A company called sentient where. We worked on a revolutionary computation. spun off Fund and we split off a website opposition company, and then rejoined forces with cognizant. We're a I'm the VP of evolutionary eye for cognizant, and he blew is what we consider. The tip of the spear in Cognizance Ai Strategy. Exciting. I'm looking forward to the show, so there is a lot of confusion out there on. Jordan, What is after all? Wrong there's really two different meanings of the word one. Is this mystical fictional idea? Of machine that would have human capabilities. They commanded data robot for example. And the second, the more realistic definition of is at collection of tools and techniques. For adding. Intelligence to our, computer systems. And at right, now is a pretty hot face. Using. Research results machine learning, specifically deep neural network learning. and. That's what led to a lot of the current hyphen confusion. But in every era of AI, some successes lead to media over. Compensated hype. And that often leads to. A loss of interest eventually. The AI winter as we call him sometimes. Winner was worse than disinterest. Disinterest leave us alone, but here I went to. They come for us. We don't want anybody coming forth so back. What do you think about that? What what what is I? Do agree with that or things like to add or. Oh, absolutely I agree with it. I think it's a set of tools inspired by human biological intelligence. It pushes us. Actually define what we mean by intelligence, various aspects of intelligence respect is interesting but did also has very practical applications. And often maybe not always often. Ai Systems are systems in which we pose the problem and we expect the system to solve it. and and therefore they do represent a a sea change to the way we were used to using software where we actually build the solution as part of the software. So. Yeah, that's to me. That's that's very interesting also gives us a sense. Of what we mean by intelligence for example gives us a away to reflect into..
"ai" Discussed on Artificial Intelligence (AI Podcast) with Lex Fridman
"You can imagine. Another person who's very skilled incapable but very cold. And you wouldn't you wouldn't really highly you might have some reservations about that other person, right? But there's also a reservation that we might have about another person who who elicits or displays human warmth but is. Not Good at getting things done. that. The greatest esteem that we we reserve our greatest esteem really for people who are both highly capable and also. Quite warm right. That's that's like the best of the best this. This isn't a a normative statement I'm making. This is just an empirical is an empirical statement. This is what humans seem this. These are the two dimensions that people seem to kind of like along which people size other people up. In research, we really focus on this capability thing we want to agents to be able to do stuff. This thing can play go at a superhuman level. That's awesome. But that's only one dimension. What's the? What about the other dimension? What would it mean for an AI system to be warm? and. I know maybe there are easy solutions we can put put a face on our AI systems. It's cute. It has big years I mean that's probably part of it but I think it also has to do with a pattern of behavior. A pattern of? You know what would it mean for an AI system to display caring compassionate behavior in a way that actually made us feel like it was for real that we didn't feel like it was simulated. We didn't feel like we were being duped to me that you know people talk about the turing test or some some descendant of I feel like. That's the ultimate turing. Test. Is there. Is there an AI system that can not only convince us that it knows how to reason that it knows how to interpret language but that we're comfortable saying yeah that AI systems a good guy. On the warmth scale whatever warmth is. Intuitive we understand it, but we also want to be able. To yeah, we don't understand it explicitly enough yet to be able to junior it exactly, and that's and that's an open scientific question. You kind of alluded it several times in the human interaction that's the question that should be studied and probably one of the most important questions and he has and Human Humans are are so good at it. Yeah. You know it's not just weird. It's not just that we're born warm. I. Suppose some people are are warmer than others given whatever they managed to inherit but there's also there's also there are also learned skills involved right I mean there are ways of communicating to other people that you care that they matter to you. You're enjoying interacting with them right and we learn these skills from one another and it's not out of the question that we could build engineered systems. I think it's hopeless as you say that we could somehow hand design these sorts of these sorts of behaviors but it's not out of the question that we could build systems that kind of. We instill in them something that sets them out in the right direction. So that they they end up learning what it is to interact with humans in a way that's gratifying to humans are honestly if that's not where we're headed..
"ai" Discussed on Artificial Intelligence (AI Podcast) with Lex Fridman
"Ai and that sort of I guess bought me a ticket to be involved in all of the amazing things that are going on in I research right now I do know a few people who I would consider pretty expert on both fronts. And I won't embarrass them by naming them but there are there are like exceptional people out there who are like this the the one the one thing that I find. Is A is a barrier to being truly world-class on both fronts is is. The, just the the complexity of the technology that's involved in both disciplines now. the the engineering expertise that it takes to to do truly frontline hands on AI research is really really considerable. The learning curve of the tools just the specifics of just whether it's programming the kind of tools necessary to collect the data managed data to distributed, compute all that kind of stuff. Yeah and on the neuroscience I guess I'd there'd be all different sets of tools exactly especially with the recent explosion in you know in neuroscience methods. So but you know so having said all that I I think. I think the I think the best scenario. For both neuroscience and AI is to have people who interacting who live at every point on the spectrum from. Exclusively focused on neuroscience to explore exclusively focused on the engineering side of ai but but to have those people. Inhabiting a community where they're talking to people who live elsewhere on the on the spectrum and I be I may be someone who's very close to the center in the sense that I have one foot in the neuroscience world and one foot in the world, and that central position I will admit prevents me at least someone with my limited cognitive capacity from from being a truly true having true technical expertise in any domain but at the same time. I at least hope that it's worthwhile having people around who can kind of. See the connections between unity the Yeah. The the merger intelligence of the community I guess nicely distributed. Is Useful. Okay. Exactly. Yeah. So hopefully that I mean I've seen that work I've seen that workout well at mind there are there are people who I mean even if you just focus on the I work that happens at deep mind it's been a good thing to have some people around doing that kind of work. WHO's PhD's are in neuroscience psychology every every academic discipline has it's.
"ai" Discussed on Pulse of AI
"So we've evolutionary eye. You're able to optimize the design of a model models. Give you a prediction. They tell you what will happen so if I do this and this. This is likely to happen. So a prediction is wonderful. But would you really want to know is what to do. So the thing that ever sharing does is run. Your models through old data and other conditions uses a technique called population based learning where? It's doing these simulations in every possible chances informing the other decisions. And what comes out of? That is an optimal decision. So a model might tell you what your revenue is likely to be on Tuesday but if we can run this through simulations we can also tell you what you should set your prices your staffing on your inventory levels to be to maximize revenue on a given day. And so what you WanNa do is not just predictable. Happen but control your outcomes in business terms so we use evolutionary eye to define a model refine it using evolutionary techniques and then run simulations against it to find optimal decisions. It's very very efficient way to do that. I brought to talk a little bit about why he thinks podcast series will be an important tool help. Business leaders unleash the power of data in a in their enterprise. There's so many missteps companies have taken as they've attempted to use ai or to embrace it And it's really important. I think to learn from each other and to find those best practices that actually do work One of the things I've seen people do is to throw a bunch of very smart data scientists in a room give them some data and tell them to produce something and that kind of experimentation very valuable in our research perspective in a business context create a lot of frustration. Which you really need to do. Is You need to align business leaders who understand data in the power of algorithms and combine business leaders with data scientists engineers in aim them at problems worth solving so the best programs. I've seen is where money is spent to bring the best people to go solve a problem. Why is the revenue forecasting You know so inaccurate. How do I better staff my team? What's the best optimal route from drivers? You got to pick questions that are meaningful in their business. Outcome in solvable using data and machine learning So by combining data scientists engineers business leaders. You're able to select those problems with a higher degree of success in your projects are more successful overall and I think a lot of companies dabbled in data science or or or Data engineering and they were frustrated because they didn't properly contextualized it in the companies. That really seemed to succeed. Have business leaders who are Algorithm Mickley? Aware they understand the power of data that they probably don't have all the data they need. That models are predictor and there are many predictors of outcome. You need to look at multiple models to run your business and then you have to turn those into action. That deliver outcomes which is why we're so focused on evolutionary eye because it can help prescribe decisions but this kind of outcome oriented. Thinking is the difference between companies that Dabble in companies. That make money using a data. This podcast series is starting while the world is experiencing the pandemic which is a black swan event. If there ever was one and I wanted to get Brett's thoughts around how companies should look at digital transformation going forward from this point. I think I advice is a quote from Douglas. Adams don't panic This is you know a black swan moment. There are many in business. Some are large like this many small but they happen all the time and I think what companies have come to realize is. They were probably operating under the assumption. Nothing will happen and that the old way of working was fine passing spreadsheets between departments running. Your forecast thirteen weeks in advance. These were okay when things are stable but it turns out that they're not okay and that things are rarely stable a lot of times you just don't see the changes in so you run it out consistently. I was in a team wants that said on. I assume what they're GONNA do next year because they said their business on a cyclical model. And I said what are you GONNA do next year for your plan. They said well since it always goes down. We're just going to keep everything flat. And sometimes they'll be goodson will be bad. They didn't really know how to adapt to change so they just wrote it out. I find that most companies actually have been doing that for a long time. So what I'm seeing. Companies do is to embrace their data and the data. They don't normally look at that. Might be good leading indicators. For what might happen and they're bringing together they're realizing that spreadsheets passed around by people are not GonNa be enough whether this crisis for the next one that they need to shorten the time between data and outcome the manual handoffs conversions the data. They need to make much more accessible to models and they need to think in terms of how models can predict what might happen and then had to make decisions. I think if anything this pandemic has made everyone amateur. Data scientist not a good one but an amateur because they're at least looking at the charts trans they're understanding what Curve might mean but people still they panic they over extrapolate. What is going to happen? Because they're looking at the outcomes and not the leading indicators in our data really means underneath so what you really need to do is to aim your business leaders who understand the data can be quite in A. I can help them in combined with people who don't panic but actually understand do data science to create useful models and to enable better decisions so that people can see what's coming not just what happened unleashing the power of data and AI. In the enterprise isn't just about technology it is also about changing the mindset of leadership. I asked Brett about his thoughts on this topic. Digital leaders see the world differently in the movie. The Matrix one of my favorite scenes when neo is looking around and he sees the table on the wall in the chairs and then when he looks up he sees just the green numbers floating what he sees is. The data makes up the world. Not just the world itself. Once you see the data you can imagine changing data in creating better outcomes. There's awakening moments for a lot of leaders when they see data new way on as an antidote as working with a chief data officer and he told me that they were looking at a retail store and they wanted to know where to go after the retail store and they realize they can combine geospatial data from public sources with mobile data on phones with instore loyalty programs and they could see that. After the major retail store people tended to certain Fast Food Restaurant afterwards that give them a chance to give him a chance to do cross promotion and much more targeted marketing because they got to understand the customers better. How many people know where people go after they buy something from you but that's possible to be known if you think of through a new lands and your opened up to new ways of bringing together. Well there you have it. I hope you enjoyed the discussion. And don't forget. Follow me on twitter at the pulse survey and connect with me. I'm Lincoln until next time..
"ai" Discussed on Gigaom AI Minute
"This is the minute brought to you by Byron Reese. And Prior A and I talked a little bit about explain ability how people want an explanation on why AI makes a decision. I talk about how explanations imply understandability and that some decisions by a is may not be understandable by humans. Why would this be? In large part, it's because I models are systems and their systems with an enormous number of levers if you were to ask the question. Of about whether on the Earth broadly speaking. Then, you have to say well, there really isn't. A single Y of anything that happens there the oceans and there's the solar winds and solar activity in this vegetation and there's all of these other factors. But in addition to the complexity of it. is every single factor in is interdependent on other factors? So. There's no way to understand just part of the system. The only way to understand the system is to understand the entirety of it system and how everything within it interacts. As an models become more and more complex. This probably isn't. A feasible thing. Your other. which has a thermostat and heater and a few basic components in a system. That you can understand and they I'm Mata with billions of pieces of. Data thousands of different fields and different weightings and all the rest maybe a system that's beyond understanding..