I'm glad the Washington Post's editorial board is pushing for governments to engage in exploring climate geoengineering. I believe AI climate modeling has an important role to play. Here's the situation as I see it:
– Earth is on track to a catastrophic 2-4 degrees Celsius of
@andrewyng
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AI Climate Modeling and Geoengineering Solutions
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Agentic Workflows Enable Synthetic Data Training for LLMs
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Inexpensive token generation and agentic workflows for large language models (LLMs) open up intriguing new possibilities for training LLMs on synthetic data. Pretraining an LLM on its own directly generated responses to prompts doesn't help. But if an agentic workflow implemented
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Groq CEO discusses fast token generation and AI expansion plans
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Chatting with @GroqInc
’s CEO @JonathanRoss321
. Groq has super fast token generation capabilities now. And, I was excited also to hear about his plans to scale up capacity aggressively and also expand this to other models than just LLMs! This is a good time to be building AI -
Prompt Engineering for Vision Models: Generation, Editing, Detection
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In Prompt Engineering for Vision Models, taught by @anmorgan2414 @JacquesVerre and @KaiserFrose of @Cometml , you’ll learn how to prompt and fine-tune vision models for personalized image generation, image editing, object detection and segmentation. The prompts you'll use for… pic.twitter.com/sXis2waFDH
— Andrew Ng (@AndrewYNg) 29 avril 2024In Prompt Engineering for Vision Models, taught by @anmorgan2414 @JacquesVerre and @KaiserFrose of @Cometml , you’ll learn how to prompt and fine-tune vision models for personalized image generation, image editing, object detection and segmentation. The prompts you'll use for
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CrewAI Multi-Agent Systems: Building Productive Agentic Workflows
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I've really enjoyed using @crewAIInc 's tools to build multiagent AI systems — in addition to being productive, it's also fun to use! It was great hanging out with its creator @joaomdmoura to chat about best practices for building agentic workflows.
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Inference Compute Shortage: Foundation Models Need More Resources
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Much has been said about many companies’ desire for more compute (as well as data) to train larger foundation models. I think it’s under-appreciated that we have nowhere near enough compute available for inference on foundation models as well. Years ago, when I was leading teams
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Mistral Mixtral 8x7B Mixture of Experts Architecture Course
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New short course with @MistralAI !
— Andrew Ng (@AndrewYNg) 22 avril 2024
Mistral's open-source Mixtral 8x7B model uses a "mixture of experts" (MoE) architecture. Unlike a standard transformer, an MoE model has multiple expert feed-forward networks (8 in this case), with a gating network selecting two experts at… pic.twitter.com/VFOg1dDab8New short course with @MistralAI ! Mistral's open-source Mixtral 8x7B model uses a "mixture of experts" (MoE) architecture. Unlike a standard transformer, an MoE model has multiple expert feed-forward networks (8 in this case), with a gating network selecting two experts at
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Meta Releases Llama 3 Language Model
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Meta released Llama 3 on my birthday! Best present ever, thanks Meta!
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Multi-Agent Collaboration: Key AI Design Pattern for Complex Tasks
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Multi-agent collaboration has emerged as a key AI agentic design pattern. Given a complex task like writing software, a multi-agent approach would break down the task into subtasks to be executed by different roles — such as a software engineer, product manager, designer, QA
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Quantization Dramatically Compresses LLMs for Consumer Hardware
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LLMs can take gigabytes of memory to store, which limits what can be run on consumer hardware. But quantization can dramatically compress models, making a wider selection of models available to developers. You can often reduce model size by 4x or more while maintaining reasonable… pic.twitter.com/ASQ28fzgkB
— Andrew Ng (@AndrewYNg) 15 avril 2024LLMs can take gigabytes of memory to store, which limits what can be run on consumer hardware. But quantization can dramatically compress models, making a wider selection of models available to developers. You can often reduce model size by 4x or more while maintaining reasonable