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open-source RL-as-a-service https://github.com/radixark/miles
Vendor-neutral startups are uniquely positioned to solve any given task better than the frontier labs. They have access to the full set of open-weight and frontier models. They can still use the frontier models where needed, but can optimize the harness e2e for any given task. They can even posttrain the model itself because they have the domain expertise to create specialized evals.
What is required to get the most out of models? “To take the most advantage out of models, you need to do something a little different from just routing. You need your agent or system to dynamically understand the task it is working on and understand how to allocate
View quoted postcan't stop playing w/ this sexy webgl gallery 😍 https://cultural-alignment.com
websites can give chatgpt work + codex tools directly through webmcp. on supported accounts, open a supported site in the desktop app’s built-in browser. the address-bar arrow shows its tools. no separate connection needed. https://help.openai.com/en/articles/20001423-using-site-tools-in-the-chatgpt-desktop-app
RT Imaan Sultan 🇵🇰🇸🇦 monopoly monday (shoutout to @alameldinkhaled @bigdogbower @stephen_revamp for bringing us all together 💌) my fav part of growth events is that you meet new people and suddenly find yourself in situations like eating yemeni mandi in the mission (pic attatched)
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View on GitHubWe've benchmarked all the latest frontier models on hard document extraction tasks (with Fable 5.1 and Gemini 3.8 Flash coming soon!). ExtractBench is now live on @kaggle . 5.6 Sol leads the pack, followed by other OpenAI models, then Gemini 3 Flash and Opus 5. Come check it out! https://www.kaggle.com/benchmarks/llamaindex-org/extractbench-leaderboard/leaderboard If you're looking for a dedicated extraction tool with out of the box grounding, citations at the price/performance frontier, come check out LlamaParse: https://cloud.llamaindex.ai/
ExtractBench is now live on @Kaggle. It tests schema-guided document extraction on the documents most likely to break downstream agents and workflows, including long record lists, noisy scans, handwriting, and complex tables. The benchmark covers 370 enterprise documents across