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Ethan Kam
@ethank_6
search @p0 | prev @openai
108 Following    387 Followers
We've been testing the Decisions API for over a week. One of the coolest things was how many use cases the team found that just weren't practical before. We had to go back to every team and ask: what would you build with frontier intelligence at the cost of a tiny, tuned classifier? It was near-perfect at filtering low-quality pages and hit 88.8% AUPRC on page change classification. Prompt tuning helped push even more performance out of the model Excited to continue building!
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Let your app choose the right model, tool, or action in near real-time with Decisions API, now available to all developers in public beta. The Decisions API makes decisions up to 10x faster than GPT-6 Luna through the Responses API.
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hinge has decided a job is more realistic
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life update: i moved back to sf from seattle, started selling a few hundred units a month, hand soldering, assembling, and shipping them from my 1bdrm apt. life is good
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can the web help AI make better predictions from wearable data? rabbitholed this week after reading @Meta’s WearableQA paper. tested an LLM with and without @p0 search + extract and saw a meaningful lift in questions re: heart/metabolic health and inflammatory response with web data included!
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muse has spoken
Parallel 🤝 Muse Parallel Free Search can now supercharge your Muse agent. Just paste this: Install Parallel’s MCP via Streamable HTTP at - no API key or OAuth needed. Verify it connects and exposes web_search and web_fetch and prefer for web search
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Opus 5.5 pro tip: Use Parallel web search. It’s 🆓 Opus 5.5 is the best model at using the context retrieved from web search Just run: claude mcp add --transport http parallel-search
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Today we're launching Data Connectors in Parallel. Your agents can now work with specialized third-party data through Parallel's best-in-class agentic web research APIs. Our first partners are @AlliumLabs, @useapolloio, @Baselayerhq, @CarbonArcAI, @crunchbase, Faraday AI, @harmonic_ai, @MiddeskHQ, @Similarweb , @particle_news, @pensa_systems, and @Polymarket. We're also launching free, opt-in access to biomedical sources including PubMed, and ChEMBL.
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Claude Opus 5.5 takes the #1# spot on Parallel's Search Capability Leaderboard, with a +4.3 gain over the second-highest score from Opus 5.
Finally a model I can relate to. congrats anthropic on discovering overthinking from first principles
At its default effort setting, Opus 5.5 delivers frontier results for a fraction of the cost per task, often beating other models running at their highest settings. It also generates output more than 30% faster than Opus 5.
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