Christopher Nguyen ⽗ @pentagoniac
CEO @aitomatic—Builder, Leader, Professor—ex Panasonic/Google/HKUST/Refugee—https://t.co/cYhm4TOhNk. Industrial Brain Engineering—https://t.co/LlcBWzawTD bit.ly/m/ctn Los Altos, CA Joined December 2007-
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@martin_casado A theory paper supports this modeling: arxiv.org/abs/2111.02080, “ICL can be viewed as LLMs implicitly performing Bayesian inference”.
This work is excellent. Note the use of the term “Bayesian inference” and not “Bayesian learning”. In particular, note that ICL links the prompt with the pretraining distribution via latent concepts. In other words, the distribution is already there, and the prompt merely…
This work is excellent. Note the use of the term “Bayesian inference” and not “Bayesian learning”. In particular, note that ICL links the prompt with the pretraining distribution via latent concepts. In other words, the distribution is already there, and the prompt merely…
How Prados Beauty is using Gemini to grow their business blog.google/outreach-initi…
As a bonus, there should be no confusion that I do not find this behavior “useful”, which is very different a property from that of “novelty/learning”. x.com/pentagoniac/st…
As a bonus, there should be no confusion that I do not find this behavior “useful”, which is very different a property from that of “novelty/learning”. x.com/pentagoniac/st…
Authorities the world over hate social media platforms, regardless of regime. And it’s not really about the harm to “our children” or to society. It’s really about how these platforms enable the organization of powerful forces—grassroots or otherwise—that can challenge their…
👇🏼 and there is an art to this.
3 things we learned from professional creatives about their hopes for AI blog.google/technology/ai/…
A new report explores the economic impact of generative AI blog.google/technology/ai/…
👇because any unconstrained running process eventually finds its constraints. In steady state, everything is the result of an optimization problem. In transient state, everything is traversing through the gradients of an optimization problem.
👇because any unconstrained running process eventually finds its constraints. In steady state, everything is the result of an optimization problem. In transient state, everything is traversing through the gradients of an optimization problem.
There is definitely some deceit happening here.
There is definitely some deceit happening here.
And just under 7 million Vietnamese 👍🏼
Excellent thread about weird lobbying efforts that paint open source AI foundation models as anti-competitive (somehow!). @LauraEdelson2 is a Prof at Northeastern and the former Chief Technologist of the Antitrust Division of the Department of Justice. She knows what she's…
Excellent thread about weird lobbying efforts that paint open source AI foundation models as anti-competitive (somehow!). @LauraEdelson2 is a Prof at Northeastern and the former Chief Technologist of the Antitrust Division of the Department of Justice. She knows what she's…
Don’t confuse communication for intelligence.
Thinking wistfully of that old saw about how we humans use only 10% of our brain capacity 😉
Thinking wistfully of that old saw about how we humans use only 10% of our brain capacity 😉
👇🏼 This. This is the current disease of my industry.
👇🏼 This. This is the current disease of my industry.
Yann LeCun @ylecun
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@pentagoniac @martin_casado We can go on and on in circles about this. I thought we had agreed to disagree yesterday!
@pentagoniac Everyone's world model breaks down at some point.
How to be as "smart" as Auto-Regressive LLMs: - memorize lots of problem statements together with recipes on how to solve them. - to solve a new problem, retrieve the recipe whose problem statement superficially matches the new problem. - apply the recipe blindly and declare…
There’s an art to distilling these to the absolute minimal necessary text. The human brain can’t comprehend how stupid these things are without practice.
WHOA! Stunning reasoning capabilities on the missionaries and cannibals problem that has never ever been openly discussed anywhere on the web! What next? Should we go for the big guns and ask "Why are manhole covers round?" #AGIntimations
A mysterious chatbot has appeared on lmsys called "gpt2-chatbot". Many are speculating that this could be GPT-5. No one really knows, but its reasoning capabilities are absolutely stunning. We may be closer to ASI than ever before.
@pentagoniac @martin_casado Again, I am not seeing where in the pre-training it learnt about the concepts of my cricket query dsl
@martin_casado A theory paper supports this modeling: arxiv.org/abs/2111.02080, “ICL can be viewed as LLMs implicitly performing Bayesian inference”.
Join Xiande Cao, Sr.Deep Learning Software Engineer Manager from #NVIDIA at the upcoming hybrid community event co-hosted by Alluxio & Uber, AI/ML Infra Meetup, where he will share his perspective on the evolution of deep learning frameworks. Learn More: buff.ly/4b2XQI1
Love this genre
The Simpsons in the 1950s
You wouldn’t last an hour in the asylum where they raised me.
@pentagoniac @martin_casado I think we will have to agree to disagree here and leave it at that since I show that the conditional distributions are novel to the model. The model distributions are the prior, the prompt is the new evidence that is used to compute the posterior. Explained in our paper on arxiv
@pentagoniac @martin_casado could seem that adding more parameters might make this 'worse', as in increase the dimensionality of the hyperspace so increasing the number of 'subspaces' and making ICL (agreed "learning" is not the right term) even more important?
@pentagoniac @martin_casado It doesn’t matter if the model weights do not change - the point is that these LLMs, on demand, learn a new concept and adjust their distributions to account for it and predict the next token. What matters is the output, not whether it is coming via back propagation or not.
@pentagoniac @martin_casado I've seen this. It got massively stuck misunderstanding an insurance accounting answer in an actuarial exam. Even when I said x is wrong it disagreed with me! I included a two sentence accounting tutorial instead and it nailed it. Always thought of it as "relocating" focus.
How to build a complete RAG application without writing a single line of code. Langflow is impressive. It’s open-source, and it’s one of the best tools that I’ve tested so far (and I’ve tested a bunch!). Here is a step-by-step guide: youtu.be/RWo4GDTZIsE
@pentagoniac @martin_casado Please watch this talk I gave. The LLMs “learn” an entirely new DSL designed by me for cricket - there was no known pattern to match youtu.be/sLodkyHlQhY?si…
@martin_casado In context learning is badly named. It's all next token prediction still, you're just "moving" the distribution of what token you're going to see by using the in context information and examples. Anthropomorphisatiin sucks, and we frustratingly don't have the right terms yet.
tl;dr LLMS as Bayesian learning : Given a prompt, looks for something close in training set, then uses prompt for new evidence. Then computes a posterior using this new evidence. This posterior distribution is what is used to generate the new text. (@vishalmisra) It's so crazy…
Does anyone have a good intuitive explanation of why in context learning works? Unlike content creation and conversation, it’s not obvious to me why this ability would fall out of next token prediction.
OpenAI is the best hype-creation engine of our times They are constantly ginning up all kinds of theories about AGI! Claiming major improvements, threatening to steamroll start-ups and making up stories about AI sentience All while - llama-3 70b matches GPT-4 performance and…
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