Linking pages
- How to train a Million Context LLM — with Mark Huang of Gradient.ai https://www.latent.space/p/gradient 1 comment
- ICLR 2024 — Best Papers & Talks (ImageGen, Vision, Transformers, State Space Models) ft. Christian Szegedy, Ilya Sutskever https://www.latent.space/p/iclr-2024-recap 0 comments
- ICLR 2024 — Best Papers & Talks (Benchmarks, Reasoning & Agents) — ft. Graham Neubig, Aman Sanger, Moritz Hardt) https://www.latent.space/p/iclr-2024-benchmarks-agents 0 comments
- How To Hire AI Engineers - by Adam Wiggins and James Brady https://www.latent.space/p/hiring 0 comments
- State of the Art: Training >70B LLMs on 10,000 H100 clusters https://www.latent.space/p/llm-training-2024 0 comments
Linked pages
- https://twitter.com/ChrisJBakke/status/1736533308849443121 381 comments
- character.ai | Personalized AI for every moment of your day https://character.ai 54 comments
- GitHub - stanfordnlp/dspy: DSPy: The framework for programming with foundation models https://github.com/stanfordnlp/dspy 52 comments
- The Top 100 Gen AI Consumer Apps | Andreessen Horowitz https://a16z.com/100-gen-ai-apps/ 14 comments
- Segment Anything 2: Demo-first Model Development https://www.latent.space/p/sam2 2 comments
- Llama 2, 3 & 4: Synthetic Data, RLHF, Agents on the path to Open Source AGI https://www.latent.space/p/llama-3 1 comment
- Latent Space | swyx | Substack https://www.latent.space/ 0 comments
- RLHF 201 - with Nathan Lambert of AI2 and Interconnects https://www.latent.space/p/rlhf-201 0 comments
- Model merging lessons in The Waifu Research Department https://www.interconnects.ai/p/model-merging 0 comments
- AI Magic: Shipping 1000s of successful products with no managers and a team of 12 — Jeremy Howard of Answer.ai https://www.latent.space/p/answerai 0 comments
- Is finetuning GPT4o worth it? - Latent Space https://www.latent.space/p/cosine 0 comments
- Why you should write your own LLM benchmarks — with Nicholas Carlini, Google DeepMind https://www.latent.space/p/carlini 0 comments
- Efficiency is Coming: 3000x Faster, Cheaper, Better AI Inference from Hardware Improvements, Quantization, and Synthetic Data Distillation https://www.latent.space/p/nyla 0 comments
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