Answer.ai & AI Magic with Jeremy Howard

Latent Space · Intermediate ·📰 AI News & Updates ·1y ago
Jeremy Howard and Eric Ries founded Answer.AI to do exactly one thing: “Practical AI R&D”. One of their first releases was a system based on FSDP + QLoRA that let anyone train a 70B model on two NVIDIA 4090s. Since then, they have come out with a long list of super useful projects with a very small team. In today's episode we talked through the origin of Answer, some of their recent work, and their upcoming project "Magic AI". Full show notes: https://www.latent.space/p/answerai 00:00:00 Introduction 00:01:07 Continous Pre-Training is Here 00:04:48 Schedule-Free Optimizers and Learning Rate…
Watch on YouTube ↗ (saves to browser)

Playlist

Uploads from Latent Space · Latent Space · 41 of 60

← Previous Next →
1 Ep 18: Petaflops to the People — with George Hotz of tinycorp
Ep 18: Petaflops to the People — with George Hotz of tinycorp
Latent Space
 2 FlashAttention-2: Making Transformers 800% faster AND exact
FlashAttention-2: Making Transformers 800% faster AND exact
Latent Space
 3 RWKV: Reinventing RNNs for the Transformer Era
RWKV: Reinventing RNNs for the Transformer Era
Latent Space
 4 Generating your AI Media Empire - with Youssef Rizk of Wondercraft.ai
Generating your AI Media Empire - with Youssef Rizk of Wondercraft.ai
Latent Space
 5 RAG is a hack - with Jerry Liu of LlamaIndex
RAG is a hack - with Jerry Liu of LlamaIndex
Latent Space
 6 The End of Finetuning — with Jeremy Howard of Fast.ai
The End of Finetuning — with Jeremy Howard of Fast.ai
Latent Space
 7 Why AI Agents Don't Work (yet) - with Kanjun Qiu of Imbue
Why AI Agents Don't Work (yet) - with Kanjun Qiu of Imbue
Latent Space
 8 Powering your Copilot for Data - with Artem Keydunov from Cube.dev
Powering your Copilot for Data - with Artem Keydunov from Cube.dev
Latent Space
 9 Beating GPT-4 with Open Source Models - with Michael Royzen of Phind
Beating GPT-4 with Open Source Models - with Michael Royzen of Phind
Latent Space
 10 The State of Silicon and the GPU Poors - with Dylan Patel of SemiAnalysis
The State of Silicon and the GPU Poors - with Dylan Patel of SemiAnalysis
Latent Space
 11 The "Normsky" architecture for AI coding agents — with Beyang Liu + Steve Yegge of SourceGraph
The "Normsky" architecture for AI coding agents — with Beyang Liu + Steve Yegge of SourceGraph
Latent Space
 12 The AI-First Graphics Editor - with Suhail Doshi of Playground AI
The AI-First Graphics Editor - with Suhail Doshi of Playground AI
Latent Space
 13 The Accidental AI Canvas - with Steve Ruiz of tldraw
The Accidental AI Canvas - with Steve Ruiz of tldraw
Latent Space
 14 The Origin and Future of RLHF: the secret ingredient for ChatGPT - with Nathan Lambert
The Origin and Future of RLHF: the secret ingredient for ChatGPT - with Nathan Lambert
Latent Space
 15 The Four Wars of the AI Stack - Dec 2023 Recap
The Four Wars of the AI Stack - Dec 2023 Recap
Latent Space
 16 The State of AI in production — with David Hsu of Retool
The State of AI in production — with David Hsu of Retool
Latent Space
 17 Building an open AI company - with Ce and Vipul of Together AI
Building an open AI company - with Ce and Vipul of Together AI
Latent Space
 18 Truly Serverless Infra for AI Engineers - with Erik Bernhardsson of Modal
Truly Serverless Infra for AI Engineers - with Erik Bernhardsson of Modal
Latent Space
 19 A Brief History of the Open Source AI Hacker - with Ben Firshman of Replicate
A Brief History of the Open Source AI Hacker - with Ben Firshman of Replicate
Latent Space
 20 Open Source AI is AI we can Trust — with Soumith Chintala of Meta AI
Open Source AI is AI we can Trust — with Soumith Chintala of Meta AI
Latent Space
 21 Making Transformers Sing - with Mikey Shulman of Suno
Making Transformers Sing - with Mikey Shulman of Suno
Latent Space
 22 A Comprehensive Overview of Large Language Models - Latent Space Paper Club
A Comprehensive Overview of Large Language Models - Latent Space Paper Club
Latent Space
 23 Why Google failed to make GPT-3 -- with David Luan of Adept
Why Google failed to make GPT-3 -- with David Luan of Adept
Latent Space
 24 Personal AI Meetup - Bee, BasedHardware, LangChain LangFriend, Deepgram EmilyAI
Personal AI Meetup - Bee, BasedHardware, LangChain LangFriend, Deepgram EmilyAI
Latent Space
 25 Supervise the Process of AI Research — with Jungwon Byun and Andreas Stuhlmüller of Elicit
Supervise the Process of AI Research — with Jungwon Byun and Andreas Stuhlmüller of Elicit
Latent Space
 26 Breaking down the OG GPT Paper by Alec Radford
Breaking down the OG GPT Paper by Alec Radford
Latent Space
 27 High Agency Pydantic over VC Backed Frameworks — with Jason Liu of Instructor
High Agency Pydantic over VC Backed Frameworks — with Jason Liu of Instructor
Latent Space
 28 This World Does Not Exist — Joscha Bach, Karan Malhotra, Rob Haisfield (WorldSim, WebSim, Liquid AI)
This World Does Not Exist — Joscha Bach, Karan Malhotra, Rob Haisfield (WorldSim, WebSim, Liquid AI)
Latent Space
 29 LLM Asia Paper Club Survey Round
LLM Asia Paper Club Survey Round
Latent Space
 30 How to train a Million Context LLM — with Mark Huang of Gradient.ai
How to train a Million Context LLM — with Mark Huang of Gradient.ai
Latent Space
 31 How AI is Eating Finance - with Mike Conover of Brightwave
How AI is Eating Finance - with Mike Conover of Brightwave
Latent Space
 32 How To Hire AI Engineers (ft. James Brady and Adam Wiggins of Elicit)
How To Hire AI Engineers (ft. James Brady and Adam Wiggins of Elicit)
Latent Space
 33 State of the Art: Training 70B LLMs on 10,000 H100 clusters
State of the Art: Training 70B LLMs on 10,000 H100 clusters
Latent Space
 34 The 10,000x Yolo Researcher Metagame — with Yi Tay of Reka
The 10,000x Yolo Researcher Metagame — with Yi Tay of Reka
Latent Space
 35 Training Llama 2, 3 & 4: The Path to Open Source AGI — with Thomas Scialom of Meta AI
Training Llama 2, 3 & 4: The Path to Open Source AGI — with Thomas Scialom of Meta AI
Latent Space
 36 [LLM Paper Club] Llama 3.1 Paper: The Llama Family of Models
[LLM Paper Club] Llama 3.1 Paper: The Llama Family of Models
Latent Space
 37 Synthetic data + tool use for LLM improvements 🦙
Synthetic data + tool use for LLM improvements 🦙
Latent Space
 38 RLHF vs SFT to break out of local maxima 📈
RLHF vs SFT to break out of local maxima 📈
Latent Space
 39 The Winds of AI Winter (Q2 Four Wars of the AI Stack Recap)
The Winds of AI Winter (Q2 Four Wars of the AI Stack Recap)
Latent Space
 40 Segment Anything 2: Memory + Vision = Object Permanence — with Nikhila Ravi and Joseph Nelson
Segment Anything 2: Memory + Vision = Object Permanence — with Nikhila Ravi and Joseph Nelson
Latent Space
 ▶ Answer.ai & AI Magic with Jeremy Howard
Answer.ai & AI Magic with Jeremy Howard
Latent Space
 42 Is finetuning GPT4o worth it?
Is finetuning GPT4o worth it?
Latent Space
 43 Personal benchmarks vs HumanEval - with Nicholas Carlini of DeepMind
Personal benchmarks vs HumanEval - with Nicholas Carlini of DeepMind
Latent Space
 44 Building AGI with OpenAI's Structured Outputs API
Building AGI with OpenAI's Structured Outputs API
Latent Space
 45 Q* for model distillation 🍓
Q* for model distillation 🍓
Latent Space
 46 Finetuning LoRAs on BILLIONS of tokens 🤖
Finetuning LoRAs on BILLIONS of tokens 🤖
Latent Space
 47 Cursor UX team is CRACKED 💻
Cursor UX team is CRACKED 💻
Latent Space
 48 Choosing the BEST OpenAI model 🏆
Choosing the BEST OpenAI model 🏆
Latent Space
 49 How will OpenAI voice mode change API design?
How will OpenAI voice mode change API design?
Latent Space
 50 STEALING OpenAI models data 🥷
STEALING OpenAI models data 🥷
Latent Space
 51 [Paper Club] 🍓 On Reasoning: Q-STaR and Friends!
[Paper Club] 🍓 On Reasoning: Q-STaR and Friends!
Latent Space
 52 [Paper Club] Writing in the Margins: Chunked Prefill KV Caching for Long Context Retrieval
[Paper Club] Writing in the Margins: Chunked Prefill KV Caching for Long Context Retrieval
Latent Space
 53 The Ultimate Guide to Prompting - with Sander Schulhoff from LearnPrompting.org
The Ultimate Guide to Prompting - with Sander Schulhoff from LearnPrompting.org
Latent Space
 54 llm.c's Origin and the Future of LLM Compilers - Andrej Karpathy at CUDA MODE
llm.c's Origin and the Future of LLM Compilers - Andrej Karpathy at CUDA MODE
Latent Space
 55 Prompt Engineer is NOT a job 📝
Prompt Engineer is NOT a job 📝
Latent Space
 56 Prompt Mining LLMs for better prompts ⛏️
Prompt Mining LLMs for better prompts ⛏️
Latent Space
 57 The six pillars of few-shot prompting 🔧
The six pillars of few-shot prompting 🔧
Latent Space
 58 Language Agents: From Reasoning to Acting — with Shunyu Yao of OpenAI, Harrison Chase of LangGraph
Language Agents: From Reasoning to Acting — with Shunyu Yao of OpenAI, Harrison Chase of LangGraph
Latent Space
 59 [Paper Club] Who Validates the Validators? Aligning LLM-Judges with Humans (w/ Eugene Yan)
[Paper Club] Who Validates the Validators? Aligning LLM-Judges with Humans (w/ Eugene Yan)
Latent Space
 60 Can you separate intelligence and knowledge?
Can you separate intelligence and knowledge?
Latent Space

Related AI Lessons

⚡
Inspire Change with an AI Innovation Keynote Speaker for Modern Businesses | Nate Patel
Hire an AI innovation keynote speaker to inspire change in your modern business and stay ahead of the curve in a rapidly changing world.
Dev.to AI
 ⚡
Big Tech firms are accelerating AI investments and integration, while regulators and companies focus on safety and responsible adoption.
Big Tech firms are increasing AI investments while focusing on safety and responsible adoption, and you can apply this knowledge to improve your own AI integration strategies
Dev.to AI
 ⚡
The Future of Education in an AI-Driven World (What Students Must Learn Now)
In an AI-driven world, students must learn to adapt, think, and evolve quickly, focusing on skills like creativity, critical thinking, and problem-solving.
Medium · AI
 ⚡
The Most Important AI Books Are Non-Technical.
Non-technical AI books can provide valuable insights and context for professionals, complementing technical knowledge with social and ethical understanding
Medium · AI

Chapters (12)

Introduction
1:07 Continous Pre-Training is Here
4:48 Schedule-Free Optimizers and Learning Rate Schedules
6:08 Governance and Structural Issues within OpenAI and Other AI Labs
13:32 How Answer.ai works
27:04 How to Recruit Productive Researchers
32:34 Building a new BERT
37:10 FSDP, QLoRA, and QDoRA: Innovations in Fine-Tuning Large Models
43:42 Research and Development on Model Inference Optimization
47:48 FastHTML for Web Application Development
1:01:16 AI Magic & Dialogue Engineering
1:04:11 AI wishlist & predictions
Justin Bieber Coachella conspiracy debunked #Vergecast
Next Up
Justin Bieber Coachella conspiracy debunked #Vergecast
The Verge