Все опубликованные аналитические материалы, исследования суверенного стека, новости экосистемы и обзоры моделей ИИ.
hello there today we're going to take a brief look at GSM symbolic understanding of the limitations of mathematical reasoning in large language models this paper is out of apple which uh continues to slowly but surely enter into the research area obviously with uh personal…
hello there today we're going to look at safety alignment should be made more than just a few tokens Deep by Anonymous authors so this is a paper that had been submitted as far as I can tell to eclair is currently on open review and has already gotten reviews and is one of the…
hello there yeah it's cold here um we cannot be dissuaded from reviewing papers today we're going to look at token forer rethinking Transformer scaling with tokenized model parameters this seems to be a collaboration of MOX plunk Institute for informatics Google and picking…
hello there today we're looking at the paper bite lat and Transformer patches scale better than tokens this paper in a sense does away with classic fixed vocabulary based tokenization and in doing so develops a new architecture called The Bite latent Transformer and in their…
Hello. Today we're taking a look at on the biology of a large language model which is a sort of paper published by anthropic on their kind of series on transformer circuits where they investigate what's going on inside of transformer language models and sort of how do they come…
Hello and welcome back to our analysis of on the biology of a large language model by anthropic. This is a blog post that anthropic has published uh investigating what they call the biology of a large language model. This works through uh a technique called attribution graphs.…
Hello, how's it going? Today we're going to look at this paper right here. Energy- based transformers are scalable learners and thinkers. This paper combines the uh general concept of energybased models with transformers and suggests a learning paradigm for it and shows how that…
Hello, today we are looking at context rot how increasing input tokens impacts LLM performance. This paper looks at what happens if with these long context models now we are just sort of putting more and more stuff into the context of LLMs and even though all of these models do…
Hello there. Today we are looking at the free transformer from France Fur at Farret Meta. This transformer is extending the classic decoderbased transformer with uh a series of latent variables that can be used to kind of make underlying decisions about the sequence to be…
Hello there. Today we're going to look at on the theoretical limitations of embedding based retrieval. And this paper is really interesting uh because it proves something about embedding based retrieval. So think vector databases in rag and things like this. And the paper proves…
[фыркает] Привет. Сегодня мы рассмотрим, как Титаны учатся запоминать во время тестов. Это статья исследования Google, которая была опубликована как часть публикаций Nurips. Итак, об этом есть сообщение в блоге, и люди написали об этом в социальных сетях, и я должен признать, что…
Здравствуйте, сегодня мы рассматриваем доклад TiDaR Thinking Diffusion Talk и авторегрессию от исследователей из Nvidia. И это действительно классная статья, потому что она фактически подтверждает, что вы уже заметили, что у нас нет полного использования графического процессора во время авторегрессионной модели большого языка…
The initials GPT stand for Generative Pretrained Transformer. So that first word is straightforward enough, these are bots that generate new text. Pretrained refers to how the model went through a process of learning from a massive amount of data, and the prefix insinuates that…
In the last chapter, you and I started to step through the internal workings of a transformer. This is one of the key pieces of technology inside large language models, and a lot of other tools in the modern wave of AI. It first hit the scene in a now-famous 2017 paper called…
If you feed a large language model the phrase, Michael Jordan plays the sport of blank, and you have it predict what comes next, and it correctly predicts basketball, this would suggest that somewhere, inside its hundreds of billions of parameters, it's baked in knowledge about…
[Submit subtitle corrections at criblate.com] Imagine you happen across a short movie script that describes a scene between a person and their AI assistant. The script has what the person asks the AI, but the AI's response has been torn off. Suppose you also have this powerful…
[Submit subtitle corrections at criblate.com] In January 2024, Google DeepMind released an AI model called Alpha Geometry, which could solve geometry problems from the International Mathematical Olympiad, or the IMO. The IMO is the highest level of competitive math contests at…
If you tell me what you like and what you don't like, I'll use that to train my model. Stack Quest. Hello, I'm Josh Starmer and welcome to Stack Quest. Today we're going to talk about reinforcement learning with human feedback and it's going to be clearly explained. This Stack…
You start with nothing, then you move. And you keep on moving till you can't get any more, then you're [music] done. StatQuest, bam. Hello, I'm Josh Starmer and welcome to StatQuest. Today, we're going to talk about optimization with linear programming main ideas. Specifically,…
We're going to find the optimal solution one row at a time. Stack Quest. Hello, I'm Josh Starmer and welcome to Stat Quest. Today we're going to talk about the simplex algorithm and we're going to go through the mathematical details. This stack quest is brought to you by the…
Привет, меня зовут Маджид из Intel Research India, и я очень рад выступить на конференции PyTorch в Северной Америке в октябре этого года. Я буду говорить об эффективном сочетании заключений экспертов LLM по использованию VLLM и OpenVINO, а также о том, как мы можем эффективно запускать эти модели на процессорах ARM. Если…
Hi, I'm G from Google. >> I'm Colin from Meta. >> I'm Angela from Meta. >> We are going to be speaking at the PyTorch conference San Jose about new VLM and SG learn engines built on a new PyTorch native TPU backend torch TPU. >> Rather than build a new serving engine or porting…
Интересно представить, что будущее клинической помощи может заключаться в том, что мы будем слышать, прежде чем видеть. В исследовательском центре Google мы разработали акустические модели для здравоохранения, известные как Here, которые являются базовой моделью. С помощью Here…
Hi, I'm Masahiro Hiramoto from Mitsubishi Electric. I'm a member of the program committee for PyTorch conference North America and a PyTorch ambassador. I'm especially looking forward to seeing what people across the community are building with PyTorch and exchanging ideas with…
Hello everyone, I'm Carlos Costa, a distinction engineer here at IBM Research and co-founder of the LMD project. I'll be heading soon to San Jose for PyTorch Conference North America, where I'll have the privilege of sharing some exciting news about LMD. How the project changed…
When you look at the history of humanity, you can see just how important scientific discovery has been. From the invention of the microscope and the discovery of bacteria to the invention of antibiotics. So I want to understand what will artificial intelligence mean for science.…
Admit, this was actually much more simple than I was imagining, but nonetheless, it's interesting to read. So, we we The title gives it away, right? Embarrassingly >> [laughter] >> In in a previous uh journal club, we read a paper on self-distillation, and in that paper uh there…
Hi, in this video I'm going to walk you through a multi-agent setup of AutoResearch. I use open source models and an open source code harness, OpenCode, and I implement AutoResearch, which is a project by Andre Carpathie where he takes a nano GPT project, an LLM in its simplest…
Good morning everyone. How's it going today? Today we're going to be talking about the fine web data set. Now, this is a project by Hugging Face and it is a great example of how to gather all the data that you need to train a large language model. This actually is also available…
This paper is doing something if I understand correctly that is very similar to what pipeline RL proposed for reinforcement learning which is where you want to basically have like really decoupled generators from learners from trainers um but you have the additional complexity…