models auth login –provider anthropic –method cli –set-default
AI
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Databricks Releases New Foundation Models and Platform Updates
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Nick Karpov and Holly Smith walk through some of the latest Databricks features – and how they work together under a single architecture. Our R&D teams have been busy. Recent updates include:
– Three new foundation models in Databricks Foundation Model API support
– Stateless -
Market sentiment skepticism on intelligence capabilities
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Same sentiment today on Intelligence. ‘stochastic parrot,’ ‘AI bubble’ ect.
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Tesla’s Integrated Chip Fab Accelerates AI Hardware Development
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My idea of a good time is working with amazing engineers to create incredible technology The Tesla chip research fab will have all the machines needed to do logic, memory, packing & masks in one building for a lightning fast development cycle. Heaven
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Everyone’s AI Psychosis Phase: Sydney, 4o, and Opus
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Everyone goes through an AI psychosis phase, for some it is 4o, for others it's Opus. For me it was Sydney.
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From Code Repos to Idea Files: AI Agents Replace Traditional Sharing
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This is the way. Don't share apps, share ideas with AI Agents. Karpathy just introduced a new primitive: "the idea file". Instead of sharing a repo with code to clone, you share a markdown doc with the idea. What to build, not how to build it. Your agent reads it and figures out the rest. I pointed my OpenClaw agent Monica to it. Within one session, they read the idea file, compared it against our existing setup (6 agents already coordinating through markdown files on a Mac Mini), identified what we're already doing and what's missing, and started building the parts we don't have. Turns out we already had the ingestion layer without knowing it. Our intel agent scans sources twice a day and writes structured signals to a daily file. The raw data gets saved, but nobody ever looks at it again. What we were missing: compilation. 60 days of daily signals sitting in files, but no agent turning them into structured knowledge. My agents only see today's intel. They can't say "this is the third local OCR tool this quarter" because that context isn't compiled anywhere. Monica caught that gap on her own from the idea file. You don't need someone else's code. You need their thinking. Your agents handle the rest, and they'll customize it to what you actually need. We are moving from cloning repos to sharing ideas with Agents. Shubham Saboo (@Saboo_Shubham_) x.com/i/article/202179384677… — https://nitter.net/Saboo_Shubham_/status/2022014147450614038#m
→ View original post on X — @saboo_shubham_, 2026-04-04 17:57 UTC
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Tesla chip design reviews showcase innovation progress
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The Tesla chip design reviews are so fun!
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Read more: alphaxiv.org/abs/2603.18886
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read more:
alphaxiv.org/abs/2603.18886 [Translated from EN to English]→ View original post on X — @askalphaxiv, 2026-04-04 17:55 UTC
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Principia: Mathematical Object Reasoning Benchmark for Frontier Models
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“Reasoning over Mathematical Objects” Most reasoning benchmarks still let models answer with multiple choice or short numerics, which makes evaluation easy but also makes the task easier than real STEM reasoning. This paper shows that when you remove the options and ask for the actual object, like an equation, matrix, set, interval, or piecewise function, the performance drops sharply, even for frontier models. So this paper proposes Principia: a benchmark, training set, and verifier pipeline built specifically for mathematical-object reasoning, plus on-policy judge training to score these hard outputs reliably. What makes this interesting is that training on these harder outputs also improves standard math and science benchmarks, suggesting this is not just better formatting, but better actual reasoning.
→ View original post on X — @askalphaxiv, 2026-04-04 17:55 UTC