For instance, autonomous cars don't hallucinate. But they don't drive on LLMs.
LLMS
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LLMs Develop Taste Capabilities Through Advanced Sensory Analysis
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LLMs will soon have taste.
— Robert Scoble (@Scobleizer) 28 avril 2026
Already Grok can look at a box of strawberries and tell you if they are fresh or not.
That's about to go another level. https://t.co/c3LDXi9uLKLLMs will soon have taste. Already Grok can look at a box of strawberries and tell you if they are fresh or not. That's about to go another level.
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Harvard Neuroscientist Launches Large Memory Model for Proactive AI Agents
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Gabriel Kreiman closed his Harvard lab to build this.
— Charly Wargnier (@DataChaz) 28 avril 2026
20 years of Neuroscience Research.
160+ publications.
This Large Memory Model (LMM) enables proactive memory and allows Agents to automatically surface vital context, without explicit prompting 👀pic.twitter.com/Qpu1PmV1MN https://t.co/YQ67SaKSs4Gabriel Kreiman closed his Harvard lab to build this. 20 years of Neuroscience Research. 160+ publications. This Large Memory Model (LMM) enables proactive memory and allows Agents to automatically surface vital context, without explicit prompting
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Types of LLMs in AI Agents: A Comprehensive Overview
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Types of #LLMs in #AIAgents by @ingliguori #GenerativeAI #ArtificialIntelligence #MachineLearning #ML
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Synthetic Pretraining Improves Reasoning in Sub-1B Models
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Synthetic pretraining for sub-1B reasoning models Cool write-up from Tufa Labs (Matteo Saponati) on whether synthetic data augmentation actually helps very small (<1B) models reason better. They pretrain a 0.8B model with the Qwen3 architecture from scratch on 12B tokens of
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Bookmarking Latest AI Models: Laguna, Ling, Xiaomi MiMO, Minimax
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Awesome, thanks. I am bookmarking all of these and will add as soon as time permits:
– Laguna XS.2
– Ling 2.6
– Xiaomi MiMO v2
– Minimax M2.7
– Tencent Hy -
Codex Transforms Messy Data Into Clean Usable Artifacts
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For knowledge work, Codex can turn messy inputs into usable artifacts: clean datasets, spot anomalies, synthesize feedback, and package the result into a sheet or report pic.twitter.com/19Kk2XY2Oa
— Vaibhav (VB) Srivastav (@reach_vb) 28 avril 2026For knowledge work, Codex can turn messy inputs into usable artifacts: clean datasets, spot anomalies, synthesize feedback, and package the result into a sheet or report
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Codex Advances Toward General-Purpose Work Agent Capabilities
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Over the last two weeks, Codex got a lot closer to a general work agent
— Vaibhav (VB) Srivastav (@reach_vb) 28 avril 2026
It can now use more of your computer, inspect what it builds, create richer artifacts, and keep longer-running work moving pic.twitter.com/3xJa6K9ArLOver the last two weeks, Codex got a lot closer to a general work agent It can now use more of your computer, inspect what it builds, create richer artifacts, and keep longer-running work moving
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Thoughtful Linguistics Perspective on Large Language Models
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Thoughtful book on LLMs and linguistics — by someone who actually knows linguistics.
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SambaHouse AI Demo Night: Open-Source Models and Production Inference
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We’re teaming up with @InfercomAI for SambaHouse AI Demo Night. Real demos, lightning talks, and honest conversations with builders working on open-source models and production inference. Details below