Claude Code just shipped /goal. You set a condition. Claude keeps working across turns until it's met. No babysitting. No prompting each step. A separate AI checks the work after every turn. Not Claude judging itself. Set it. Walk away. Come back to finished work. I made a
LLMS
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AI Model’s Contextual Formatting Capabilities for Speech Transcription
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What impressed me most is the contextual formatting layer. The model does not just transcribe speech. It structures information automatically: → Dates
→ Numbers
→ Currency values
→ Speaker separation
→ Precise timestamps That means conversations instantly become usable -
The shift from voice transcription to structured AI understanding
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Most AI voice systems still break the moment humans act… human.
— Ronald van Loon (@Ronald_vanLoon) 14 mai 2026
Interruptions.
Messy audio.
Multiple speakers.
People switching languages mid-sentence.
But the real breakthrough is not transcription anymore.
It’s structured understanding.
That changes everything.
A thread… pic.twitter.com/HbMAbglURmMost AI voice systems still break the moment humans act… human. Interruptions.
Messy audio.
Multiple speakers.
People switching languages mid-sentence. But the real breakthrough is not transcription anymore. It’s structured understanding. That changes everything. A thread -
Google’s new Gemini model to rival GPT-5.5 at I/O
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Lets go: Google’s next Gemini model is expected to compete with GPT-5.5 Google is reportedly preparing to unveil a new Gemini model at I/O, positioning it near OpenAI’s recent GPT-5.5 rather than the more elusive Anthropic Mythos. Google i/o got even more exciting
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The reality of running local AI hardware
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The dream was always-on local AI. The reality is a very expensive always-on fan.
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Foundational Course on Large Language Models for Young Developers
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If you’ve been curious about how Large Language Models work, how AI tools generate responses, or what powers today’s Generative AI applications, this course is a great place to start. The LLM for Young Developers: Foundational Course offers a practical introduction to
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Hölder Policy Optimisation paper and code
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Hölder Policy Optimisation Paper: https://
arxiv.org/abs/2605.12058
Code: https://
github.com/YihangChen9/Ho
lderPO
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HölderPO: single-parameter fix to prevent AI training collapse
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Wow, fixing one simple parameter could stop your AI training from collapsing! UCL, Shanghai Jiao Tong University, and HKUST (Guangzhou) present HölderPO. Instead of summing token probabilities in a fixed way, HölderPO uses a flexible averaging trick controlled by a single “p”
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Peking University Researchers Unveil SEAlign for AI Code Agents
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Why can't top code models handle real-world software engineering? Researchers from Peking University unveil SEAlign — a new alignment framework that trains code agents on actual software workflows. Instead of just solving coding puzzles, it uses Monte Carlo Tree Search to
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Operational Usage of AI Agent Teams
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Agent teams count as interactive usage, so draw from your sub