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Зерттеулер1 мин

Byte Latent Transformer: Patches Scale Better Than Tokens (Paper Explained)

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…

YouTube — Yannic Kilcher
Зерттеулер1 мин

On the Biology of a Large Language Model (Part 1)

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…

YouTube — Yannic Kilcher
Зерттеулер1 мин

On the Biology of a Large Language Model (Part 2)

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.…

YouTube — Yannic Kilcher
Зерттеулер1 мин

Energy-Based Transformers are Scalable Learners and Thinkers (Paper Review)

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…

YouTube — Yannic Kilcher
Зерттеулер1 мин

Context Rot: How Increasing Input Tokens Impacts LLM Performance (Paper Analysis)

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…

YouTube — Yannic Kilcher
Зерттеулер1 мин

[Қағазды талдау] Еркін трансформатор (және кейбір вариациялық автокодер материалдары)

Саламатсызба. Бүгін біз Фаррет Метадағы France Fur тегін трансформаторын қарастырамыз. Бұл трансформатор классикалық декодер негізіндегі трансформаторды жасырын айнымалылар сериясымен кеңейтеді, оларды келесі реттілік туралы негізгі шешімдерді қабылдау үшін пайдалануға болады ...

YouTube — Yannic Kilcher
Зерттеулер1 мин

Титандар: сынақ уақытында есте сақтауды үйрену (қағазды талдау)

[Ықылас] Сәлем. Бүгін біз сынақ кезінде есте сақтауды үйренетін титандарды қарастырамыз. Бұл Google зерттеуінің мақаласы және олардың Nurips басылымдарының бөлігі ретінде шығарылды. Сонымен, бұл туралы блог жазбасы бар және адамдар бұл туралы әлеуметтік желіде жариялады және мен мойындауым керек ...

YouTube — Yannic Kilcher
Зерттеулер1 мин

TiDAR: диффузияда ойлаңыз, авторегрессияда сөйлесіңіз (қағазды талдау)

Сәлеметсіз бе, бүгін біз Nvidia зерттеушілерінің TiDaR ойлау диффузиясы мен авторегрессиясын қарастырамыз. Және бұл өте керемет қағаз, өйткені ол авторегрессивті үлкен тіл үлгісінде GPU толық пайдаланылмағанын байқағаныңыз тиімді ...

YouTube — Yannic Kilcher
Зерттеулер1 мин

Transformers, the tech behind LLMs | Deep Learning Chapter 5

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…

YouTube — 3Blue1Brown
Зерттеулер1 мин

Attention in transformers, step-by-step | Deep Learning Chapter 6

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…

YouTube — 3Blue1Brown
Зерттеулер1 мин

How might LLMs store facts | Deep Learning Chapter 7

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…

YouTube — 3Blue1Brown
Зерттеулер1 мин

Large Language Models explained briefly

[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…

YouTube — 3Blue1Brown
Зерттеулер1 мин

The AI that solved IMO Geometry Problems | Guest video by @Aleph 0

[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…

YouTube — 3Blue1Brown
Зерттеулер1 мин

Reinforcement Learning with Human Feedback (RLHF), Clearly Explained!!!

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…

YouTube — StatQuest AI
Зерттеулер1 мин

Optimization with Linear Programming (and the Simplex Algorithm), Main Ideas!!!

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,…

YouTube — StatQuest AI
Зерттеулер1 мин

The Simplex Algorithm, Mathematical Details!!!

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…

YouTube — StatQuest AI
Зерттеулер1 мин

ARM процессорларындағы Experts LLM тұжырымының қоспасын оңтайландыру

Сәлем, мен Intel Research India компаниясынан келген Маджидпін және осы қазан айында Солтүстік Америкадағы PyTorch конференциясында сөйлейтініме қуаныштымын. Мен VLLM және OpenVINO қолдану бойынша LLM сарапшыларының тиімді қоспасы және бұл модельдерді ARM процессорларында қалай тиімді іске қосуға болатыны туралы айтатын боламын. Егер…

YouTube — PyTorch Official
Зерттеулер1 мин

PyTorch-Native LLM Serving on TPU: SGLang and vLLM

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…

YouTube — PyTorch Official
Зерттеулер1 мин

Can we hear disease before we see it?

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…

YouTube — Google Research
Стартаптар1 мин

Open Source Inference at Production Scale

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…

YouTube — PyTorch Official
Зерттеулер1 мин

How Google Research Is Accelerating Scientific Discovery | The Google Research Podcast

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.…

YouTube — Google Research
Зерттеулер1 мин

Multi-Agent AutoResearch with Open Source Models

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…

YouTube — Hugging Face
Зерттеулер1 мин

How to Create an LLM Dataset | FineWeb Overview

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…

YouTube — Hugging Face
Зерттеулер1 мин

Hugging Face Journal Club: AsyncOPD and How Stale Can On-Policy Distillation Be?

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…

YouTube — Hugging Face
Зерттеулер1 мин

The Hugging Face Hub for Enterprise & Academia

Всем привет. Если вы работаете с ИИ, у вас наверняка уже есть аккаунт на Hugging Face Hub, где удобно демонстрировать свои модели, скачивать модели с открытым кодом, использовать публичные наборы данных и создавать демоверсии своих моделей. Но публичный хаб—это только начало. В…

YouTube — Hugging Face
Зерттеулер1 мин

Hugging Face Journal Club: Kimi K3

Let [clears throat] me think where to start. Okay, so we've got the Kim K3 report and it's quite a beast in terms of details, which is pretty awesome. And the bits that I focused on were really just the the pre- uh sorry, the post-training parts. And even that I wasn't able to…

YouTube — Hugging Face