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Captainant
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There's some wild new machine learning techniques out there these days - reinforcement learning lets robots teach themselves how to do a task without training data, unsupervised learning alerts heavy machinery operators know when something is fucky in a system, and NLP is unlocking the data within unstructured text and giving us a mechanism to rapidly crunch through thousands of pages of documents.

Newest to the fold for me, and what I've been getting my mind blown by: neural graphics primitives (short video of what that actually means lol). It's effectively a new mechanism to encode spatial and visual data so that rather than storing the polygons and geometry, it's training a neural net on how to generate that data on the fly based on a small number of input 2d images. The results are astounding. I'm working on getting it running on my local desktop computer but alas my puny 1080ti doesn't have tensor cores so it runs slow as hell.

The real innovation of this technique is that it's using NV's tensor cores to calculate the intersection of rays projected from your input images to create a fully 3D representation, and then training an ML model to infer the rest of the 3D space. It's some crazy higher order math - the originating paper for these concepts were published just a couple years ago, and they've already developed new techniques to operationalize and optimize the math. For context: these models fully train in two seconds using these new techniques and hardware. It's wild.

 

Any other ML nerds on surly? Also, does anyone have an RTX 3080 I can buy? lol

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  • 4 weeks later...
On 2/23/2022 at 8:37 AM, Captainant said:

There's some wild new machine learning techniques out there these days - reinforcement learning lets robots teach themselves how to do a task without training data, unsupervised learning alerts heavy machinery operators know when something is fucky in a system, and NLP is unlocking the data within unstructured text and giving us a mechanism to rapidly crunch through thousands of pages of documents.

Newest to the fold for me, and what I've been getting my mind blown by: neural graphics primitives (short video of what that actually means lol). It's effectively a new mechanism to encode spatial and visual data so that rather than storing the polygons and geometry, it's training a neural net on how to generate that data on the fly based on a small number of input 2d images. The results are astounding. I'm working on getting it running on my local desktop computer but alas my puny 1080ti doesn't have tensor cores so it runs slow as hell.

The real innovation of this technique is that it's using NV's tensor cores to calculate the intersection of rays projected from your input images to create a fully 3D representation, and then training an ML model to infer the rest of the 3D space. It's some crazy higher order math - the originating paper for these concepts were published just a couple years ago, and they've already developed new techniques to operationalize and optimize the math. For context: these models fully train in two seconds using these new techniques and hardware. It's wild.

 

Any other ML nerds on surly? Also, does anyone have an RTX 3080 I can buy? lol

But what are the enterprise use cases?

Seriously though, this is a cool thread and post-- wish it was in a different forum with more eyes and traffic instead of buried in nerdz because I guarantee this place has at least a half a dozen ML/AI/Data Scientist whizs.

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Posted (edited)
On 2/23/2022 at 8:37 AM, Captainant said:

There's some wild new machine learning techniques out there these days - reinforcement learning lets robots teach themselves how to do a task without training data, unsupervised learning alerts heavy machinery operators know when something is fucky in a system, and NLP is unlocking the data within unstructured text and giving us a mechanism to rapidly crunch through thousands of pages of documents.

Newest to the fold for me, and what I've been getting my mind blown by: neural graphics primitives (short video of what that actually means lol). It's effectively a new mechanism to encode spatial and visual data so that rather than storing the polygons and geometry, it's training a neural net on how to generate that data on the fly based on a small number of input 2d images. The results are astounding. I'm working on getting it running on my local desktop computer but alas my puny 1080ti doesn't have tensor cores so it runs slow as hell.

The real innovation of this technique is that it's using NV's tensor cores to calculate the intersection of rays projected from your input images to create a fully 3D representation, and then training an ML model to infer the rest of the 3D space. It's some crazy higher order math - the originating paper for these concepts were published just a couple years ago, and they've already developed new techniques to operationalize and optimize the math. For context: these models fully train in two seconds using these new techniques and hardware. It's wild.

 

Any other ML nerds on surly? Also, does anyone have an RTX 3080 I can buy? lol

My first thought because I'm old and stupid was "this seems like something PTC would be trying to bring to market" but I clicked your link and it looks like a labs/sub of nVidia. Which should be no surprise as they have quietly been one of the greatest underrated American companies the past decade and have an amazing CEO.

Also, institutional investors must be savvy to the use case potential I was half-way joking about:

Quote

Markets: Investors were feeling risky yesterday, piling into tech stocks and semiconductors in particular. Nvidia, the seventh-largest S&P 500 company by market cap, soared on expectations that it’ll play a pivotal role in the development of AI.

https://www.cnbc.com/2022/03/24/nvidia-and-intel-lead-rally-in-semiconductor-stocks-.html

Edited by TurkeyChew
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10 minutes ago, TurkeyChew said:

But what are the enterprise use cases?

Seriously though, this is a cool thread and post-- wish it was in a different forum with more eyes and traffic instead of buried in nerdz because I guarantee this place has at least a half a dozen ML/AI/Data Scientist whizs.

For this specific technique, imagine being able to take a series of flat ultrasound images from different angles and reconstruct the actual geometry of that object - either a tumor, or an organ, or even a baby's face. All non-invasively and with already existing tools, we're just using the data more effectively.

Enterprise specific, I have a customer that runs a huge fleet of vessels for ocean floor mapping. Imagine if instead of sending down an ROV, they could simply aggregate enough sonar depth data from enough points of reference to get the same result.

Neural nets in general are pretty incredible technology. We understand the mechanics of how they work, but are still learning why they work. 3brown1blue has an excellent explainer on them that's 90 minutes long in total.

 

 

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Like a lot of AI, I might assume that one of the primary use cases will be robotics, which doesn't mean better mechanical dogs, or things that holler Danger, Will Robinson, but things that handle materials and assemble products.

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9 minutes ago, thunderlounge said:

So take some 2D images, do math, make a 3D hologram?

 

Interesting. How long before Hooli buys that one too?

Sony? samsung?

I mean, the method mentioned in my OP runs on a desktop computer lol. A 3090 trains the model in minutes or even seconds. The thing to buy/sell is the data that you use to train models or a trained model, not the algorithm or framework. 

"Data is the new oil" has been repeated constantly for the last 5 years. Machine learning is how we refine it into a usable product. 

But yeah, Nvidia is the head and shoulders leader for this stuff. They're creating hardware acceleration for extremely complex higher order matrix operations, and they somewhat shape the academic focus as they create new acceleration techniques. All this latest stuff is the beneficiary of ray tracing and tensor processing cores for cleaning data and training models

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Sure, but my light-hearted reply was meant more for the tech’s future beyond just that. 
 

Look what happened in a couple short years, and give it 10 more. 
 

I don’t think it’s something that will have a broad use today, but give some nut job engineers some time and some smoke and they’ll get there. 
 

 

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Posted (edited)
On 3/25/2022 at 3:15 PM, Captainant said:

I mean, the method mentioned in my OP runs on a desktop computer lol. A 3090 trains the model in minutes or even seconds. The thing to buy/sell is the data that you use to train models or a trained model, not the algorithm or framework. 

"Data is the new oil" has been repeated constantly for the last 5 years. Machine learning is how we refine it into a usable product. 

But yeah, Nvidia is the head and shoulders leader for this stuff. They're creating hardware acceleration for extremely complex higher order matrix operations, and they somewhat shape the academic focus as they create new acceleration techniques. All this latest stuff is the beneficiary of ray tracing and tensor processing cores for cleaning data and training models

I just read this fascinating interview with nVidia CEO:

Quote

 

In no time in history have humans have the ability to produce the single most valuable commodity the world’s ever known, which is intelligence. We now have a structure of a model, a structure of a computer science program called a deep neural network, that has the ability to scale up quite tremendously. It’s doubling every six months, I mean, this is not your Moore’s Law where it’s doubling every two years, it’s doubling every six months. The rate of doubling is incredible, the compounded effect of that on computing is incredible.

The results of the capabilities of these neural networks and the software, another way of saying it, the software that is being created by computers is expanding and growing and achieving spectacular things at incredible rates. Our company is building the computers necessary to continue to advance that journey. I think that what companies are going to come to realize is that what they’re really all about is producing intelligence, and that’s what Nvidia’s really all about is producing intelligence. Some part of every company will automate the production of their intelligence, they’ll codify the production of their intelligence, which is one of the reasons why I believe every company will be an AI company, every company will produce intelligence at some level, all of that AI will be augmenting humans with humans in the loop, and the rate of that progress is accelerating and compounding at 2x every six months.

what is intelligence? Intelligence is the ability to recognize patterns, recognize relationships, reason about it and make a prediction or plan an action. That’s what intelligence is. It has nothing to do with general intelligence, intelligence is just solving problems. We now have the ability to write software, we now have the ability to partner with computers to write software, that can solve many types of intelligence, make many types of predictions at scales and at levels that no humans can.

For example, we know that there are a trillion things on the Internet and the number things on the Internet is large and expanding incredibly fast and yet we have this little tiny personal computer called a phone, how do we possibly figure out of the trillion things in the internet what we want to see on our little tiny phone? Well, there needs to be a filter in between, what people call the personalized internet, but basically an AI, a recommender system. A recommender that figures out based on the nature of the content, the characteristics of the content, the features of the content, based on your implicit and your explicit and implicit preferences, find a way through all of that to predict what you would like to see. I mean, that’s a miracle! That’s really quite a miracle to be able to do that at scale for everything from movies and books and music and news and videos and you name it, products and things like that. To be able to predict what Ben would want to see, predict what you would want to click on, predict what is useful to you. I’m talking about things that are consumer oriented stuff, but in the future it’ll be predict what is the best financial strategy for you, predict what is the best medical therapy for you, predict what is the best health regimen for you, what’s the best vacation plan for you. All of these things are going to be possible with AI.

 

Edited by TurkeyChew
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Posted (edited)

In general, if you want to get your mind blown I'd recommend checking out the youtube channel Two Minute Papers - he posts a new 5ish minute video every so often showing off a novel implementation of an ML model. This is a pretty neat one that combines reinforcement learning with adversarial networks

 

And on a personal note - I just scored an open box RTX 3080 with 12GB of VRAM from my local MicroCenter so I'm looking forward to finally getting to kick the tires on some of this stuff

Edited by Captainant
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Posted (edited)

Ok now I'm just pandering, but this is pretty fucking cool. I took this UT tower flyaround video (in spoiler)

Spoiler

Did the above process against the video file (720p 30fps source file), trained it for about 120 seconds, mapped a camera flight through the environment and rendered it back out to a short 1080p video as seen below @thunderlounge @TwiceHorn:

Edited by Captainant
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On 4/13/2022 at 7:58 AM, Captainant said:

Ok now I'm just pandering, but this is pretty fucking cool. I took this UT tower flyaround video (in spoiler)

  Reveal hidden contents

Did the above process against the video file (720p 30fps source file), trained it for about 120 seconds, mapped a camera flight through the environment and rendered it back out to a short 1080p video as seen below @thunderlounge @TwiceHorn:

 

spacer.png

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