Tech News
I indexed 669 GB of my GoPro videos using my M1 Max computer and local ML models
A developer indexed 669 GB of GoPro videos (628 videos, 15+ hours) on an M1 Max using open-source ML models to search for moments and send clips to DaVinci Resolve. The project processed 57,537 frames over 67 hours, enabling local video search and editing automation
vllm-project/vllm v0.23.0
vllm-project/vllm v0.23.0 updates # vLLM v0.23.0 Release Notes Please note that Minimax M3 is not yet supported in this version. Please follow [vLLM recipe]( for usage guides for M3. ## Highlights This release f.
Why AI hasn’t replaced software engineers, and won’t
Simon Willison covers Why AI hasn’t replaced software engineers, and won’t, with why AI hasn’t replaced software engineers, and won’t Arvind Narayanan and Sayash Kappor take on the question of AI job losses through the lens of a profession that is uniquely s.
Introducing the OpenAI Partner Network
OpenAI News covers Introducing the OpenAI Partner Network, with openAI launches the Partner Network, investing $150M to help global partners accelerate enterprise AI adoption, deployment, and transformation.
NVIDIA Achieves Leading Agentic Coding Performance on First Agentic AI Benchmark
NVIDIA AI Blog covers NVIDIA Achieves Leading Agentic Coding Performance on First Agentic AI Benchmark, with aI agents have fundamentally changed the complexity of inference workloads. Until now, the industry has struggled to define a standard for measuring how.
GitHub Repos
upstash/context7
ClassicTypeScriptllmmcplobehub/lobehub
ClassicTypeScriptagentagent-collaborationAI-QL/tuui
High PotentialTypeScriptagentagentic-aiResearch Papers
OpenCUA: Open Foundations for Computer-Use Agents
OpenCUA provides an open-source framework for building computer-use agents, including a large dataset (AgentNet) spanning 200+ apps across 3 OSes, and a pipeline that uses reflective Chain-of-Thought reasoning to improve performance, achieving state-of-the-art among...
Diversity-Aware Policy Optimization for Large Language Model Reasoning
This paper shows that promoting solution diversity during reinforcement learning training improves the reasoning performance of large language models, achieving a 3.5% average gain on math benchmarks.
AdaSR: Adaptive Streaming Reasoning with Hierarchical Relative Policy Optimization
Large reasoning models typically follow a read-then-think paradigm: they observe the complete input, reason over a static context, and then produce the answer. Yet many real-world scenarios are inherently dynamic, such as audio and video stream, where information arrives as a...