At first, in the early 2020s, I worried that LLMs were often confidently wrong, calling them “fluent spouters of bullshit”. (And I was right; they have been and continue to be.). But now we have a new problem which is that *people* who *learn* from LLMs are also often
LLMS
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Fine-tuning strategies and future plans for expanding capabilities
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Thanks! The fine-tuning section is more general in the first one, and the second one is focused on math because it makes it easier from a security perspective. But I plan to add bonus materials over time, and function calling would be an interesting one.
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HyperOffload: Compiler Framework Optimizes LLM Memory Management
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Tired of LLMs maxing out memory even on powerful supernode architectures? Shanghai Jiao Tong University and Huawei Technologies Co., Ltd. introduce HyperOffload! This new compiler-assisted framework intelligently plans data movement for large language models. By treating
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ULMFiT LSTM Evolution Language Model Fine-tuning History
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Right, and indeed ULMFiT was an LSTM. But also, that earlier work wasn't using language modeling on a general purpose corpus as a self-supervised task then fine-tuning that in two more steps for downstream tasks like today's LLMs. (It wouldn't have been feasible on that h/ware)
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AgenticRAG: From Answers to Action with AI Agents
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#AgenticRAG: From Answers to Action
by @ingliguori #AI #Automation #Tech #GenAI #LLM -
RAG vs Fine-Tuning: What Works in Enterprise AI
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RAG vs Fine-Tuning: What Actually Works in Enterprise AI (And Why Most Get It Wrong) https://
craigbrownphd.substack.com/p/rag-vs-fine-
tuning-what-actually?utm_source=dlvr.it&utm_medium=twitter
… #DataScience #DataAnalytics -
Meta tests multiple Avocado AI variants internally
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BREAKING : Meta is testing loads of Avocado variants internally, including multiple release candidates, Avocado-mango agent, Avocado 9B, and more. Avocado Think Hard performs quite well and, as reported earlier, is comparable to Gemini 3 level models. All this in parallel to
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OpenResearcher: An Open-Source Offline-Trained Research Agent
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You can now train a deep research agent without a single API call.
— AlphaSignal AI (@AlphaSignalAI) 29 mars 2026
OpenResearcher is a new open-source repo that's trained entirely offline.
A 10-billion-token corpus generates 100+ turn research trajectories.
All offline. Zero API costs.
It learns three browsing actions… pic.twitter.com/4wgFUaFhFxYou can now train a deep research agent without a single API call. OpenResearcher is a new open-source repo that's trained entirely offline. A 10-billion-token corpus generates 100+ turn research trajectories. All offline. Zero API costs. It learns three browsing actions
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Language Barriers Finally Overcome Through Advanced Technology
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It's still nuts to me how this sci-fi dream becomes reality: language barriers are solved forever.
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Frontier Models Vision Capabilities: Benchmarks Gaming Problem
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Frontier models can’t see, and if you think they can, you’ve probably been fooled by benchmarks that can totally be gamed. In the very short essay linked below I discuss a stunning new finding from Stanford that shows just how serious the problem is. And why this means a lot