[ML News] MMO Game destroys GPUs | OpenAI quits Robotics | Today w/ guest host Sanyam Bhutani
deep learning machine learning arxiv explained neural networks ai artificial intelligence paper introduction to deep learning what is deep learning ml news machine learning news amazon mmo game breaks gpu google intrinsic alphabet intrinsic openai robotics openai robotics team chai time chai time data science chai time data science podcast sanyam sanyam bhutani saynam ml news nasa nasa ai ai common sense common sense dataset deep learning news
#chai #mlnews #nvidia

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Outline:
0:00 - Intro & Overview
1:30 - Amazon's MMO may destroy gaming GPUs
2:40 - OpenAI pivots away from Robotics
3:35 - Google parent Alphabet launches Intrinsic
4:55 - AI learns how vegetables taste
5:55 - NASA uses AI to better understand the sun
6:50 - Man used AI to bring back deceased fiancee
7:45 - Robot collision sparks warehouse fire
8:20 - AI deduces patients' racial identities from medical records
9:40 - AlphaFold protein structure database
10:15 - ICCV BEHAVIOR challenge
11:05 - IBM, MIT, Harvard release Common Sense database
11:35 - High quality image generation using diffusion models
12:50 - Conclusion

References:
1 Amazon’s new MMO may be bricking Nvidia 3090s
https://www.theverge.com/2021/7/21/22587616/amazon-games-new-world-nvidia-rtx-3090-bricked-evga-closed-beta
https://www.youtube.com/watch?v=KLyNFrKyG74

2 Open AI pivotes from Robots
https://venturebeat.com/2021/07/23/ai-weekly-openais-pivot-from-robotics-acknowledges-the-power-of-simulation/

3 Google parent Alphabet launches Intrinsic: a new company to build software for industrial robots
https://www.theverge.com/2021/7/23/22590109/google-intrinsic-industrial-robotics-company-software
Introducing Intrinsic
https://blog.x.company/introducing-intrinsic-1cf35b87651
https://x.company/projects/intrinsic/
https://www.forbes.com/sites/jenniferhicks/2021/07/20/ai-is-learning-to-understand-how-vegetables-taste/?sh=73e6f646e1b2

4 Artificial Intelligence Helps Improve NASA’s Eyes on the Sun
https://www.nasa.gov/feature/goddard/2021/artificial-intelligence-helps-improve-nasa-s-eyes-on-the-sun

5 A man used AI to bring back his deceased fiancé. But the creators of the tech warn it could be dangerous
https://www.businessinsider.co.za/man-used-ai-to-talk-to-late-fiance-experts-warn-tech-could-be-misused-2021-7

6 Robot collision at Ocado warehouse near London sparks fire, delaying customer orders https://www.theverge.com/2021/7/18/22582454/robot-collision-ocado-warehouse-england-fire-delayed-orders

10 Reading Race: AI Recognizes Patient’s Racial Identity In Medical Images
https://arxiv.org/pdf/2107.10356.pdf

11 AlphaFold Protein Structure Database
https://alphafold.ebi.ac.uk
https://www.theverge.com/2021/7/22/22586578/deepmind-alphafold-ai-protein-folding-human-proteome-released-for-free

12 Behavior Challenge
http://svl.stanford.edu/behavior/challenge.html

13 Researchers from IBM, MIT and Harvard Announced The Release Of DARPA “Common Sense AI” Dataset Along With Two Machine Learning Models At ICML 2021
https://www.marktechpost.com/2021/07/20/researchers-from-ibm-mit-and-harvard-announced-the-release-of-its-darpa-common-sense-ai-dataset-along-with-two-machine-learning-models-at-icml-2021/
https://www.reddit.com/r/MachineLearning/comments/onxw90/n_researchers_from_ibm_mit_and_harvard_announced/

14 Google uses diffusion model for image generation
https://www.reddit.com/r/MachineLearning/comments/ors7ht/r_using_the_diffusion_model_google_ai_is_able_to/
https://www.reddit.com/r/MachineLearning/comments/oo4cla/n_nvidia_launches_tensorrt_8_that_improves_ai/


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 Once upon a time during his vacation, Yannick LightspeedKilcher found chai. He had so much of chai and he liked it so much that he turned into the host of Chai Time Data Science. That's why I'm hosting Machine Learning News. Hi everyone, I'm Syam. I host the Chai Time Data Science podcast on YouTube channel and I'm hosting Machine Learning News today because because I'm holding the mic. Yes. Before we start the news, I have a news to matter. I don't care. I'm holding the mic. I'll be interviewing Yannick on my channel, linked in the description. If you have any questions that you want me to ask him, any questions that you want to ask him and you want me to ask him so that your questions can be asked to him, you get the point. Please leave a comment down below. I'll make sure I ask you questions to Yannick. And now let's start with your weekly. Absolutely regular. You don't need to look at your calendar. You know it's mundane. In this week's news, Amazon's new game pricks. A few actually quite a lot. 3090s. Imagine running a game and breaking your GPUs. Open AI pivots from robots. They take a pivot away from that direction. And Google. Interesting timing. Or launches a new company to build software for industrial robots. Welcome to Machine Learning News. Before we start, I have something important. It's hot, but it's really good. So this is Kashmiri Kawa. I recommend it. I recommend any child. Let's jump into it. Amazon's new MMO may be breaking Nvidia 3090s. The words right after intensive Googling, we have discovered that MMOs are massively multiplayer online games. Amazon created this massively multiplayer online games. Now I know. Apparently this was breaking a few EVGA cards. Since then the game has been patched and Amazon issued a statement that is there in this blog. But based on what I've understood by watching so many YouTube videos, the power draw on these graphic cards was just going haywire when the game would launch and that would end up frying the card, which is kind of crazy. I mean, I'm not supposed to laugh at these. These are like pretty expensive cards, but it's kind of crazy to think that a game could do that and that these cards could go through that. Luckily, EVGA has like phenomenal customer service based on what I understand when you return a product, the RMA process is undertaken. Now GPUs are pretty short on supply, but EVGA has a separate supply of cards for just covering under warranty and they've already started shipping out cards. Who does do these guys? But how is that under machine learning news? Well, if you're in machine learning, you probably would want a 39 day and you wouldn't want a game to break it. Open AI check Yannick's previous video here for an intro about it. Open AI pivots from robotics and acknowledges the power of simulation venture be it right. So Open AI co-founder, I don't want to butcher the name W Zarambia has shared according to this blog that the company is pivoting from solving robotics. Robotics is such a harder problem. I feel it's quite underrated and we still working on this even though we have somewhat somewhat cars that can drive themselves in the US in India, you can't at least where I'm from. I mean, these cars work well when they do but then they don't because so many real world constraints kick in and that's again something that robotics deals with as a challenge. So that's what they talk about in this blog and it appears that Open AI will be focusing on other problems. Interesting timing on this. But Google's parent company Alphabet launches intrinsic new company to build software for industrial robots, the verge rights after reading this and reading the original post the announcement post by Wendy Tan White, who will be leading this company what I've understood is a large part that is still hot. That is still pretty hot. A large part of manufacturing is based on robotics and a large number of industries need this. Now personally, I'm not sure. So like for computers, a nice thing is you have x64 architectures for phones, you have arm architectures for iOS. I can't do anything, but they are different architectures. I mean, iOS does have the developer kit. But I'm not sure if the industry has standard robots. So I'm sure like they would be a similar type of robots on an assembly line intrinsic will be developing software for those robots who their customers are isn't clear from the blog. That's something that the verge mentioned as well. But it's interesting to see that robotics is making some progress in different areas and we're just starting to understand how difficult the problem this is. I mean, I've seen Boston Dynamics robot stance, which is really, really cool. And it's great to see more companies working in this direction. Jobs writes AI is learning to understand how vegetables taste. I won't believe in the internet until I can download these things don't surprise me. So you can actually 3d print food, which means that I believe in the internet. Sorry. This blog talks about a farm called fifth season, which is in Pittsburgh, that is using a software stack and robotics to automate their farms and what they're trying to understand is based on this blog, what I want to show you is that they have QR codes associated with different plants, and they really use data monitoring and really try to target a crop towards a certain taste, which is pretty good I feel again in agriculture, it's it's again so many areas where AI is just being applied where machine learning just needs to be applied. And it'll become global, you know, we need tensor flows for agriculture, we need pie torches for agriculture, just like we need them for robotics. So it's great to see that this company is working for it. It's not open source, but at least there's some news around someone working on this. NASA writes AI helps improve NASA's eyes on the sun. NASA has been collecting images of the sun, you can't just actually you can you can just you can take your phone take a picture of the sun. But that's not good enough. Because you can't see UV rays from Earth in the atmosphere filters it out. You can't see UV rays anyway, and you wouldn't want to because they might damage your skin and eyes. But that is part of the spectrum that the sun emits, among many other things. So the sun isn't exactly how we see it from this surface. NASA has been collecting these images over years now. And this blog talks about how they're trying to calibrate it. There's a nice animation that shows you how the calibration actually changes the images that we have. So based on robots that NASA has been sending into the orbit, orbit, now they're calibrating these images. Very cool. Next up a man actually foreshadowed Black Mirror had foreshadowed this. And it's reality sort of a reality. Now a man used AI to bring back his deceased fiance, the creators of techmonet could be dangerous. I'm not going to get into how ethically right or wrong this is. That's an independent discussion. And that's why we need those discussions. But this blog talks about how this person I'm not going to name the service used a service built on top of GPT three, which now makes sense that wasn't released, but is an API. So the person used the API and built a chat board service on top of it. And this person, the one who contacted his deceased fiance created a chat board around it and just interacted with it for so long. I leave it at that and let you think about this. I'm not going to this is a sensitive topic. So I don't want to speak too much about it. As if the robots were upset about opening shutting down its robotics this division they collided at Ocado warehouse near London sparking a fire and delaying orders he was right. If you're watching this robots, I'm on the side of you. I'm on the side of Yannick. I know he's a robot. That's why he wears aviators to hide his vision system. Just wanted to tell you I'm on your side. Jokes aside, again, a large part of these systems are being automated and we really need companies working on these because again, these problems happen and they can cause huge issues or damages. This wasn't a huge one, but again, that's why you need them. Too much ethics, but I feel these discussions are important. Reading race that's the name of the paper. AI recognizes patients racial identity in medical images. Medical domain is one of those areas where the impact to humans is more directly felt than any other. That's when we talk about having biases in these models. This paper shows that these models are able to pick on the race of a person based on the medical images. Note the doctor can't even make out from these pictures, these x-ray images, the CT scans the race of a person. It's not because of just some tissue being fired for certain races, etc, etc, etc. That's what this paper says. And apparently it's also able to deduce these technologies. Deep learning algorithms are able to deduce based on corrupt images also the race of a person. They actually go ahead and show this in the studies as well. Let's say there's a race, chai race. I really like that. But there's also a coffee race. As a doctor, I can't imagine myself as a doctor, but let's let's picture myself as being a doctor. I might not give the best treatment to coffee. That's why we need more rigorous testing around these systems. And it's great to have such papers come up from now and then. DeepMind had created Alpha Fold2. I'm sure Yannick would cover that paper on his channel. So Alpha Fold2 is an architecture based on transformers. And it has created this breakthrough in understanding protein folding and protein structures. That's an independent discussion, but it's a huge breakthrough in human history. They've created this database of so many proteins that can be just very useful in understanding life and for biology, they've open sourced it. That's how research should be. And it's available for free as long as you cite the results for you to use. Very nice. ICCV launches behavior challenge. The goal of embodied AI research as written in this post is to develop intelligent agents that can assist humans in their everyday lives in activities like washing dishes, cleaning floors. While recent, okay, let me go out of this post. Recent activities like whatever progress you've seen, even the papers that Yannick discusses heavily are narrow AIs and these are slightly greater broader, but we need now for the broader AI if that makes sense. I'm not talking about AGI, it's broader AI. And these challenges, these tasks are a goal towards these. So there are different tasks that can that are a part of this and the deadline is October 17. I encourage you to check it out. The behavior challenge is a benchmark with 100 household activities that represent a new challenge. Very cool. And I look forward to seeing the results from this. IBM, MIT and Harvard release common sense AI data set at ICML. The argument in this post by IBM is when you see an infant, they're able to reduce so much just based on common sense even at a young AI models can't they've put together a lot of animations and similar things for an agent to learn these along with few interesting baseline models and they're trying to advance machine common sense. That's such a funny word. That's why I brought this up. Finally, Google AI generates even higher quality images. So generative adversarial networks, I mentioned this on my Twitter, but I'm also highly interested in these. That's why I got this nice box that you don't see it's full of RGB. You know what I'm talking about. I feel this is an interesting area because we've seen so much progress recently style can came out which made the image is super nice. Now we've seen a further improvement. I feel we really need a good benchmark to measure these beyond a certain point. But anyways, the team at Google released Google brain released a new natural image synthesis super resolution via repeated refinements SR three model and cascaded diffusion model based on the demo on the page. These images do look really nice quality. How nicer are they are compared to style can or the recent papers you really need to look at them side by side. But what they what they say here is it's about it's can perform face super resolution in quite higher resolution. That's it. That's just an area I'm interested in. So I thought I might share that. But that is it for this week's machine learning news. You know, it's Monday. Thanks for tuning in on a Monday, please subscribe to your next channel. Let's get him to 100k so that we can celebrate his 100k subscribers on my interview. Leave a comment down below for the questions that you want me to ask him for now. Please keep drinking chai please enjoying your day and please keep watching ML news. Thanks for watching.
 Once upon a time during his vacation, Yannick LightspeedKilcher found chai. He had so much
 of chai and he liked it so much that he turned into the host of Chai Time Data Science. That's
 why I'm hosting Machine Learning News. Hi everyone, I'm Syam. I host the Chai Time
 Data Science podcast on YouTube channel and I'm hosting Machine Learning News today because
 because I'm holding the mic. Yes. Before we start the news, I have a news to matter. I
 don't care. I'm holding the mic. I'll be interviewing Yannick on my channel, linked in the description.
 If you have any questions that you want me to ask him, any questions that you want to
 ask him and you want me to ask him so that your questions can be asked to him, you get
 the point. Please leave a comment down below. I'll make sure I ask you questions to Yannick.
 And now let's start with your weekly. Absolutely regular. You don't need to look at your calendar.
 You know it's mundane. In this week's news, Amazon's new game pricks. A few actually quite
 a lot. 3090s. Imagine running a game and breaking your GPUs. Open AI pivots from robots. They
 take a pivot away from that direction. And Google. Interesting timing. Or launches a
 new company to build software for industrial robots. Welcome to Machine Learning News.
 Before we start, I have something important. It's hot, but it's really good. So this is
 Kashmiri Kawa. I recommend it. I recommend any child. Let's jump into it. Amazon's new
 MMO may be breaking Nvidia 3090s. The words right after intensive Googling, we have discovered
 that MMOs are massively multiplayer online games. Amazon created this massively multiplayer
 online games. Now I know. Apparently this was breaking a few EVGA cards. Since then the
 game has been patched and Amazon issued a statement that is there in this blog. But
 based on what I've understood by watching so many YouTube videos, the power draw on
 these graphic cards was just going haywire when the game would launch and that would
 end up frying the card, which is kind of crazy. I mean, I'm not supposed to laugh at these.
 These are like pretty expensive cards, but it's kind of crazy to think that a game could
 do that and that these cards could go through that. Luckily, EVGA has like phenomenal customer
 service based on what I understand when you return a product, the RMA process is undertaken.
 Now GPUs are pretty short on supply, but EVGA has a separate supply of cards for just covering
 under warranty and they've already started shipping out cards. Who does do these guys?
 But how is that under machine learning news? Well, if you're in machine learning, you probably
 would want a 39 day and you wouldn't want a game to break it. Open AI check Yannick's
 previous video here for an intro about it. Open AI pivots from robotics and acknowledges
 the power of simulation venture be it right. So Open AI co-founder, I don't want to butcher
 the name W Zarambia has shared according to this blog that the company is pivoting from
 solving robotics. Robotics is such a harder problem. I feel it's quite underrated and
 we still working on this even though we have somewhat somewhat cars that can drive themselves
 in the US in India, you can't at least where I'm from. I mean, these cars work well when
 they do but then they don't because so many real world constraints kick in and that's
 again something that robotics deals with as a challenge. So that's what they talk about
 in this blog and it appears that Open AI will be focusing on other problems. Interesting
 timing on this. But Google's parent company Alphabet launches intrinsic new company to
 build software for industrial robots, the verge rights after reading this and reading
 the original post the announcement post by Wendy Tan White, who will be leading this
 company what I've understood is a large part that is still hot. That is still pretty hot.
 A large part of manufacturing is based on robotics and a large number of industries
 need this. Now personally, I'm not sure. So like for computers, a nice thing is you have
 x64 architectures for phones, you have arm architectures for iOS. I can't do anything,
 but they are different architectures. I mean, iOS does have the developer kit. But I'm not
 sure if the industry has standard robots. So I'm sure like they would be a similar type
 of robots on an assembly line intrinsic will be developing software for those robots who
 their customers are isn't clear from the blog. That's something that the verge mentioned
 as well. But it's interesting to see that robotics is making some progress in different
 areas and we're just starting to understand how difficult the problem this is. I mean,
 I've seen Boston Dynamics robot stance, which is really, really cool. And it's great to
 see more companies working in this direction.
 Jobs writes AI is learning to understand how vegetables taste. I won't believe in the internet
 until I can download these things don't surprise me. So you can actually 3d print food, which
 means that I believe in the internet. Sorry. This blog talks about a farm called fifth
 season, which is in Pittsburgh, that is using a software stack and robotics to automate
 their farms and what they're trying to understand is based on this blog, what I want to show
 you is that they have QR codes associated with different plants, and they really use
 data monitoring and really try to target a crop towards a certain taste, which is pretty
 good I feel again in agriculture, it's it's again so many areas where AI is just being
 applied where machine learning just needs to be applied. And it'll become global, you
 know, we need tensor flows for agriculture, we need pie torches for agriculture, just
 like we need them for robotics. So it's great to see that this company is working for it.
 It's not open source, but at least there's some news around someone working on this.
 NASA writes AI helps improve NASA's eyes on the sun. NASA has been collecting images of
 the sun, you can't just actually you can you can just you can take your phone take a picture
 of the sun. But that's not good enough. Because you can't see UV rays from Earth in the atmosphere
 filters it out. You can't see UV rays anyway, and you wouldn't want to because they might
 damage your skin and eyes. But that is part of the spectrum that the sun emits, among
 many other things. So the sun isn't exactly how we see it from this surface. NASA has
 been collecting these images over years now. And this blog talks about how they're trying
 to calibrate it. There's a nice animation that shows you how the calibration actually
 changes the images that we have. So based on robots that NASA has been sending into
 the orbit, orbit, now they're calibrating these images. Very cool. Next up a man actually
 foreshadowed Black Mirror had foreshadowed this. And it's reality sort of a reality.
 Now a man used AI to bring back his deceased fiance, the creators of techmonet could be
 dangerous. I'm not going to get into how ethically right or wrong this is. That's an independent
 discussion. And that's why we need those discussions. But this blog talks about how this person
 I'm not going to name the service used a service built on top of GPT three, which now makes
 sense that wasn't released, but is an API. So the person used the API and built a chat
 board service on top of it. And this person, the one who contacted his deceased fiance
 created a chat board around it and just interacted with it for so long. I leave it at that and
 let you think about this. I'm not going to this is a sensitive topic. So I don't want
 to speak too much about it. As if the robots were upset about opening shutting down its
 robotics this division they collided at Ocado warehouse near London sparking a fire and
 delaying orders he was right. If you're watching this robots, I'm on the side of you. I'm on
 the side of Yannick. I know he's a robot. That's why he wears aviators to hide his vision
 system. Just wanted to tell you I'm on your side. Jokes aside, again, a large part of
 these systems are being automated and we really need companies working on these because again,
 these problems happen and they can cause huge issues or damages. This wasn't a huge one,
 but again, that's why you need them. Too much ethics, but I feel these discussions are important.
 Reading race that's the name of the paper. AI recognizes patients racial identity in
 medical images. Medical domain is one of those areas where the impact to humans is more directly
 felt than any other. That's when we talk about having biases in these models. This paper
 shows that these models are able to pick on the race of a person based on the medical
 images. Note the doctor can't even make out from these pictures, these x-ray images, the
 CT scans the race of a person. It's not because of just some tissue being fired for certain
 races, etc, etc, etc. That's what this paper says. And apparently it's also able to deduce
 these technologies. Deep learning algorithms are able to deduce based on corrupt images
 also the race of a person. They actually go ahead and show this in the studies as well.
 Let's say there's a race, chai race. I really like that. But there's also a coffee race.
 As a doctor, I can't imagine myself as a doctor, but let's let's picture myself as being a
 doctor. I might not give the best treatment to coffee. That's why we need more rigorous
 testing around these systems. And it's great to have such papers come up from now and then.
 DeepMind had created Alpha Fold2. I'm sure Yannick would cover that paper on his channel.
 So Alpha Fold2 is an architecture based on transformers. And it has created this breakthrough
 in understanding protein folding and protein structures. That's an independent discussion,
 but it's a huge breakthrough in human history. They've created this database of so many proteins
 that can be just very useful in understanding life and for biology, they've open sourced
 it. That's how research should be. And it's available for free as long as you cite the
 results for you to use. Very nice.
 ICCV launches behavior challenge. The goal of embodied AI research as written in this
 post is to develop intelligent agents that can assist humans in their everyday lives
 in activities like washing dishes, cleaning floors. While recent, okay, let me go out
 of this post. Recent activities like whatever progress you've seen, even the papers that
 Yannick discusses heavily are narrow AIs and these are slightly greater broader, but we
 need now for the broader AI if that makes sense. I'm not talking about AGI, it's broader
 AI. And these challenges, these tasks are a goal towards these. So there are different
 tasks that can that are a part of this and the deadline is October 17. I encourage you
 to check it out. The behavior challenge is a benchmark with 100 household activities
 that represent a new challenge. Very cool. And I look forward to seeing the results from
 this.
 IBM, MIT and Harvard release common sense AI data set at ICML. The argument in this
 post by IBM is when you see an infant, they're able to reduce so much just based on common
 sense even at a young AI models can't they've put together a lot of animations and similar
 things for an agent to learn these along with few interesting baseline models and they're
 trying to advance machine common sense. That's such a funny word. That's why I brought this
 up. Finally, Google AI generates even higher quality images. So generative adversarial
 networks, I mentioned this on my Twitter, but I'm also highly interested in these. That's
 why I got this nice box that you don't see it's full of RGB. You know what I'm talking
 about.
 I feel this is an interesting area because we've seen so much progress recently style
 can came out which made the image is super nice. Now we've seen a further improvement.
 I feel we really need a good benchmark to measure these beyond a certain point. But
 anyways, the team at Google released Google brain released a new natural image synthesis
 super resolution via repeated refinements SR three model and cascaded diffusion model
 based on the demo on the page. These images do look really nice quality. How nicer are
 they are compared to style can or the recent papers you really need to look at them side
 by side. But what they what they say here is it's about it's can perform face super
 resolution in quite higher resolution. That's it. That's just an area I'm interested in.
 So I thought I might share that. But that is it for this week's machine learning news.
 You know, it's Monday. Thanks for tuning in on a Monday, please subscribe to your next
 channel. Let's get him to 100k so that we can celebrate his 100k subscribers on my interview.
 Leave a comment down below for the questions that you want me to ask him for now. Please
 keep drinking chai please enjoying your day and please keep watching ML news. Thanks for
 watching.