I trolled OpenAI when they didn't initially release gpt2 because oooooh soooo dangerous
LLMS
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Claude’s Secret Leverage Point Deconstructor Mode
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BREAKING: Claude has a secret mode called "Donella Meadows Leverage Point Deconstructor." It maps any complex problem as interconnected feedback loops, finds the single point where a tiny change produces massive results, and rebuilds your entire strategy from the structure
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Cohere Transcribe: Advanced Speech Recognition Model with Browser Deployment
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Cohere Transcribe is setting a new standard for automatic speech recognition model accuracy in real world conditions – even with a noisy blender running. Try it out for yourself 👇https://t.co/cIHYqTVVyI https://t.co/yCdigM9U6W
— Cohere (@cohere) 28 mars 2026Cohere Transcribe is setting a new standard for automatic speech recognition model accuracy in real world conditions – even with a noisy blender running. Try it out for yourself 👇 cohere.link/hpqiVWT Nick Frosst (@nickfrosst) @cohere transcribe Sota open source transcription model running in the browser 🙂 Weights on @huggingface link below — https://nitter.net/nickfrosst/status/2037914966305493286#m
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GLM 5.1 fails to read tool output in Cursor IDE
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@Zai_org In Cursor, GLM 5.1 completely fails to find/read any tool output, where GLM 4.7 and 5.0 works with the same endpoint — just different model name. Not exactly sure what GLM 5.1 is doing differently, looks the same in IDE and different approaches and tools also failed…
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LLMs Excel at Technical Editing Tasks Over Content Generation
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Well, I guess that's because it had a lot of newspapers in it's training corpus .
Joking aside, I think LLMs work best for technical editing tbh. Things like "what sources did I forget to cite", "is my spelling of technical terms consistent" etc. -
Discussion on Frontier AI Model Capabilities and Compute Allocation
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Seedance 2.0 has been out for a while now and is SOTA. Strangely, there's been little word from US Frontier Labs to counter it. Either they're foregoing it because they need and are reserving the compute resources (as with OpenAI) for the development and research of upcoming
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Agentic AI Explained in a Nutshell
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#AgenticAI Explained in a Nutshell
by @Python_Dv #LLM #GenerativeAI #ArtificialIntelligence #MachineLearning -
Agentic Architectural Patterns for Multi-Agent GenAI Systems
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5- release from @PacktDataML at http://
amzn.to/3MaHy8T "Agentic Architectural Patterns for Building Multi-Agent Systems: Proven design patterns and practices for GenAI, agents, RAG, LLMOps, and enterprise-scale AI systems" Contents:
GenAI in the Enterprise: Landscape, -
Azure OpenAI Essentials: Practical Guide to Generative AI Innovation
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Azure OpenAI Essentials — A practical guide to unlocking Generative AI-powered innovation with Azure OpenAI: http://
amzn.to/3EWMFWk via @PacktDataML ——
#GenAI #MachineLearning #DataScience
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𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Explore the capabilities of Azure OpenAI’s LLMs Craft -
Data Quality Challenges in Open Source AI Models
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Yeah I keep thinking about how to do this well, but the data is too noisy and open models are mostly too small