Linking pages
- Throw more AI at your problems https://frontierai.substack.com/p/throw-more-ai-at-your-problems 55 comments
- Artificial general intelligence (AGI) may arise in 2027 with artificial 'super intelligence' sooner than we think | Live Science https://www.livescience.com/technology/artificial-intelligence/ai-agi-singularity-in-2027-artificial-super-intelligence-sooner-than-we-think-ben-goertzel 49 comments
- DSPy Documentation https://dspy.ai/ 43 comments
- LLMs Know More Than What They Say - by Ruby Pai https://arjunbansal.substack.com/p/llms-know-more-than-what-they-say 18 comments
- AI leaderboards are no longer useful. It's time to switch to Pareto curves. https://www.aisnakeoil.com/p/ai-leaderboards-are-no-longer-useful 14 comments
- Sober AI is the Norm | Drew Breunig https://www.dbreunig.com/2024/06/12/sober-ai-is-the-norm.html 7 comments
- Introducing Baseten Chains https://www.baseten.co/blog/introducing-baseten-chains/ 5 comments
- RAG is Dead. Long Live RAG! - Qdrant https://qdrant.tech/articles/rag-is-dead/ 1 comment
- Introducing world's largest synthetic open-source Text-to-SQL dataset https://gretel.ai/blog/synthetic-text-to-sql-dataset 1 comment
- GitHub - JoshuaC215/agent-service-toolkit: Full toolkit for running an AI agent service built with LangGraph, FastAPI and Streamlit https://github.com/JoshuaC215/agent-service-toolkit 1 comment
- Maithra Raghu | The best AIs will be constructed not emergent https://maithraraghu.com/blog/2024/best-ai-constructed-not-emergent/ 1 comment
- Introducing world's largest synthetic open-source Text-to-SQL dataset https://gretel-ai.webflow.io/blog/synthetic-text-to-sql-dataset 0 comments
- Breaking software bottlenecks https://aiprospects.substack.com/p/breaking-software-bottlenecks 0 comments
- How to Create High Quality Synthetic Data for Fine-Tuning LLMs https://gretel.ai/blog/how-to-create-high-quality-synthetic-data-for-fine-tuning-llms 0 comments
- What we've learned from analyzing hundreds of AI web agent traces https://invariantlabs.ai/blog/what-we-learned-from-analyzing-web-agents 0 comments
- Superhuman Powers for Superhero Developers https://benfutor.substack.com/p/superhuman-powers-for-superhero-developers 0 comments
- Beyond LLMs: Compounds Systems, Agents, and Whole AI Products https://thetechnomist.com/p/beyond-llms-compounds-systems-agents 0 comments
Linked pages
- Bing https://bing.com 750 comments
- AlphaGeometry: An Olympiad-level AI system for geometry - Google DeepMind https://deepmind.google/discover/blog/alphageometry-an-olympiad-level-ai-system-for-geometry/ 262 comments
- [2302.04761] Toolformer: Language Models Can Teach Themselves to Use Tools https://arxiv.org/abs/2302.04761 153 comments
- PyTorch http://pytorch.org/ 100 comments
- copilot-explorer | Hacky repo to see what the Copilot extension sends to the server https://thakkarparth007.github.io/copilot-explorer/posts/copilot-internals.html 95 comments
- LlamaIndex - Data Framework for LLM Applications https://www.llamaindex.ai/ 55 comments
- Introducing Gemini: Google’s most capable AI model yet https://blog.google/technology/ai/google-gemini-ai/ 10 comments
- Maithra Raghu | Does One Large Model Rule Them All? https://maithraraghu.com/blog/2023/does-one-model-rule-them-all/ 6 comments
- LMQL: Programming Large Language Models https://lmql.ai/ 6 comments
- GitHub - yoheinakajima/babyagi https://github.com/yoheinakajima/babyagi 3 comments
- https://storage.googleapis.com/deepmind-media/AlphaCode2/AlphaCode2_Tech_Report.pdf 3 comments
- [2201.11903] Chain of Thought Prompting Elicits Reasoning in Large Language Models https://arxiv.org/abs/2201.11903 1 comment
- https://arxiv.org/pdf/2203.11171.pdf 1 comment
- [2305.05176] FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance https://arxiv.org/abs/2305.05176 1 comment
- The Power of Prompting - Microsoft Research https://www.microsoft.com/en-us/research/blog/the-power-of-prompting/ 1 comment
- A Guide to Large Language Model Abstractions - Two Sigma https://www.twosigma.com/articles/a-guide-to-large-language-model-abstractions/ 1 comment
- [2001.08361] Scaling Laws for Neural Language Models https://arxiv.org/abs/2001.08361 0 comments
- [2005.11401] Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks https://arxiv.org/abs/2005.11401 0 comments
- [2201.08239] LaMDA: Language Models for Dialog Applications https://arxiv.org/abs/2201.08239 0 comments
- LangChain https://langchain.com/ 0 comments
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