The AI Infra Diaries

Latent Space · Advanced ·🏭 MLOps & LLMOps ·1y ago

Key Takeaways

The AI Infra Diaries by Latent Space discusses inference optimization and model versioning in AI systems, highlighting the importance of context and multimodal interaction.

Full Transcript

One of them is just like this AI co-presence which I think we're getting like one of the big limitations of AI systems being useful is like they don't have the context like they can't see what you see. They don't have access to the stuff that you that you do. And I think the models actually being able to see and you being able to interact interact with them using your voice I think bridges us closer to this world where we're actually not limited by the context cuz the models can see and do all the same stuff that I'm able to do. But also, I think it's just like it's one of those experiences that's so fundamentally visual. Like you can show the model what you see on the screen. You can, you know, have it connect to your camera. You can send text to it. You can talk to it. All this stuff, which I think feels feels like the AI experience. Uh, which is really interesting to me. Like it's not just chat. It's it's truly this like different experience than you get

Original Description

From inference optimization to model versioning — Swyx and Alessio unpack the hard engineering behind today’s smartest systems
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Playlist

Uploads from Latent Space · Latent Space · 0 of 60

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1 Ep 18: Petaflops to the People — with George Hotz of tinycorp
Ep 18: Petaflops to the People — with George Hotz of tinycorp
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 2 FlashAttention-2: Making Transformers 800% faster AND exact
FlashAttention-2: Making Transformers 800% faster AND exact
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 3 RWKV: Reinventing RNNs for the Transformer Era
RWKV: Reinventing RNNs for the Transformer Era
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 4 Generating your AI Media Empire - with Youssef Rizk of Wondercraft.ai
Generating your AI Media Empire - with Youssef Rizk of Wondercraft.ai
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 5 RAG is a hack - with Jerry Liu of LlamaIndex
RAG is a hack - with Jerry Liu of LlamaIndex
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 6 The End of Finetuning — with Jeremy Howard of Fast.ai
The End of Finetuning — with Jeremy Howard of Fast.ai
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 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
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 8 Powering your Copilot for Data - with Artem Keydunov from Cube.dev
Powering your Copilot for Data - with Artem Keydunov from Cube.dev
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 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
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 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
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 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
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 12 The AI-First Graphics Editor - with Suhail Doshi of Playground AI
The AI-First Graphics Editor - with Suhail Doshi of Playground AI
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 13 The Accidental AI Canvas - with Steve Ruiz of tldraw
The Accidental AI Canvas - with Steve Ruiz of tldraw
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 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
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 15 The Four Wars of the AI Stack - Dec 2023 Recap
The Four Wars of the AI Stack - Dec 2023 Recap
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 16 The State of AI in production — with David Hsu of Retool
The State of AI in production — with David Hsu of Retool
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 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
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 18 Truly Serverless Infra for AI Engineers - with Erik Bernhardsson of Modal
Truly Serverless Infra for AI Engineers - with Erik Bernhardsson of Modal
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 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
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 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
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 21 Making Transformers Sing - with Mikey Shulman of Suno
Making Transformers Sing - with Mikey Shulman of Suno
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 22 A Comprehensive Overview of Large Language Models - Latent Space Paper Club
A Comprehensive Overview of Large Language Models - Latent Space Paper Club
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 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
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 24 Personal AI Meetup - Bee, BasedHardware, LangChain LangFriend, Deepgram EmilyAI
Personal AI Meetup - Bee, BasedHardware, LangChain LangFriend, Deepgram EmilyAI
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 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
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 26 Breaking down the OG GPT Paper by Alec Radford
Breaking down the OG GPT Paper by Alec Radford
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 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
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 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)
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 29 LLM Asia Paper Club Survey Round
LLM Asia Paper Club Survey Round
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 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
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 31 How AI is Eating Finance - with Mike Conover of Brightwave
How AI is Eating Finance - with Mike Conover of Brightwave
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 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)
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 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
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 34 The 10,000x Yolo Researcher Metagame — with Yi Tay of Reka
The 10,000x Yolo Researcher Metagame — with Yi Tay of Reka
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 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
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 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
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 37 Synthetic data + tool use for LLM improvements 🦙
Synthetic data + tool use for LLM improvements 🦙
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 38 RLHF vs SFT to break out of local maxima 📈
RLHF vs SFT to break out of local maxima 📈
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 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)
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 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
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 41 Answer.ai & AI Magic with Jeremy Howard
Answer.ai & AI Magic with Jeremy Howard
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 42 Is finetuning GPT4o worth it?
Is finetuning GPT4o worth it?
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 43 Personal benchmarks vs HumanEval - with Nicholas Carlini of DeepMind
Personal benchmarks vs HumanEval - with Nicholas Carlini of DeepMind
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 44 Building AGI with OpenAI's Structured Outputs API
Building AGI with OpenAI's Structured Outputs API
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 45 Q* for model distillation 🍓
Q* for model distillation 🍓
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 46 Finetuning LoRAs on BILLIONS of tokens 🤖
Finetuning LoRAs on BILLIONS of tokens 🤖
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 47 Cursor UX team is CRACKED 💻
Cursor UX team is CRACKED 💻
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 48 Choosing the BEST OpenAI model 🏆
Choosing the BEST OpenAI model 🏆
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 49 How will OpenAI voice mode change API design?
How will OpenAI voice mode change API design?
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 50 STEALING OpenAI models data 🥷
STEALING OpenAI models data 🥷
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 51 [Paper Club] 🍓 On Reasoning: Q-STaR and Friends!
[Paper Club] 🍓 On Reasoning: Q-STaR and Friends!
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 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
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 53 The Ultimate Guide to Prompting - with Sander Schulhoff from LearnPrompting.org
The Ultimate Guide to Prompting - with Sander Schulhoff from LearnPrompting.org
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 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
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 55 Prompt Engineer is NOT a job 📝
Prompt Engineer is NOT a job 📝
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 56 Prompt Mining LLMs for better prompts ⛏️
Prompt Mining LLMs for better prompts ⛏️
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 57 The six pillars of few-shot prompting 🔧
The six pillars of few-shot prompting 🔧
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 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
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 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)
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 60 Can you separate intelligence and knowledge?
Can you separate intelligence and knowledge?
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The AI Infra Diaries discusses the importance of context and multimodal interaction in AI systems, and how inference optimization and model versioning can improve their performance. By understanding these concepts, developers can create more effective and user-friendly AI applications. The diary highlights the potential of AI co-presence, where models can see and interact with users in a more human-like way.

Key Takeaways
  1. Implement multimodal interaction in AI systems
  2. Optimize inference for improved performance
  3. Develop strategies for model versioning
  4. Design visual experiences for AI applications
  5. Integrate voice interaction in AI systems
  6. Connect AI models to cameras and other sensors
  7. Send text to AI models for processing
💡 The future of AI lies in creating systems that can interact with users in a more human-like way, using multimodal interaction and inference optimization to improve performance and user experience.

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