perhaps we should compare calculators to humans? also, if you actually follow my work (eg October 2025 NYT oped) you will know I am a fan of domain specific AI (like Waymo) and skeptical of domain-general AI (like chatbots), so I appreciate your making my case for me.
RESEARCH
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Converting 30k arXiv papers to Markdown using SOTA OCR
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New blog post: converting 30k @arxiv papers to Markdown using SOTA OCR models to enable chat with paper functionality
— Niels Rogge (@NielsRogge) 7 avril 2026
Includes:
> leveraging an open OCR model (Chandra 2 by @datalabto)
> running on GPU infra – @huggingface Jobs
> using Codex with a SKILL.md pic.twitter.com/jrpin9oq5uNew blog post: converting 30k @arxiv papers to Markdown using SOTA OCR models to enable chat with paper functionality Includes: > leveraging an open OCR model (Chandra 2 by @datalabto) > running on GPU infra – @huggingface Jobs > using Codex with a SKILL.md
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ARC Prize 2026 Launches with $2M in Prizes and L4 Compute
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ARC Prize 2026: ARC-AGI-2 has been upgraded to L4x4s Thank you @kaggle for upgrading compute for all participants ARC Prize (@arcprize) Also live today: ARC Prize 2026 – 3 tracks, $2,000,000 in prizes available! Get involved: • Play a Game: arcprize.org/tasks/ls20 • Build Agents: docs.arcprize.org • Win Prizes: arcprize.org/competitions/20… — https://nitter.net/arcprize/status/2036860092046598213#m
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Growing Up Means Understanding Multiple Perspectives in Complex Situations
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Big part of growing up is realizing that there are more than two sides in any situation.
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Kevin Ellis on DreamCoder: Neurosymbolic AI and Program Synthesis
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On the pod: our most-requested guest! @ellisk_kellis from @Cornell shares the origins of his influential neurosymbolic paper "DreamCoder".
— Ndea (@ndea) 7 avril 2026
Plus: program synthesis, wake-sleep library learning, world models, running an AI research lab, and more. pic.twitter.com/MS0mW0b2y1On the pod: our most-requested guest! @ellisk_kellis from @Cornell shares the origins of his influential neurosymbolic paper "DreamCoder". Plus: program synthesis, wake-sleep library learning, world models, running an AI research lab, and more.
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Stanford AI Index 2026 Analyzes AI’s Impact on Research Economy Policy
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The #AIIndex2026 returns this year with comprehensive analysis from an expanded interdisciplinary team of experts – bringing fresh perspectives and deeper insights on how AI is shaping research, the economy, policy, and public opinion. Subscribe here: https://t.co/iMfE3xkyHG pic.twitter.com/e3miEDcBNB
— Stanford HAI (@StanfordHAI) 7 avril 2026The #AIIndex2026 returns this year with comprehensive analysis from an expanded interdisciplinary team of experts – bringing fresh perspectives and deeper insights on how AI is shaping research, the economy, policy, and public opinion. Subscribe here: hai.stanford.edu/ai-index
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GLM 5.1 Open-Source Model Tops SWE-Bench Pro Performance
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The best performing model on SWE-Bench Pro is open-source on @huggingface! Welcome GLM 5.1! huggingface.co/zai-org/GLM-5…
→ View original post on X — @clementdelangue, 2026-04-07 16:31 UTC
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GLM-5.1: Revolutionary Open-Source Agentic Coding Model Released
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Another big release: GLM-5.1! China is on fire! significant increase in evals compared to GLM-5.0 tl;dr GLM-5.1 is the new open-source agentic coding model that significantly outperforms its predecessor by sustaining long-horizon problem-solving over hundreds of iterations, continuously improving results instead of plateauing, achieving state-of-the-art performance on complex software engineering benchmarks. Z.ai (@Zai_org) Introducing GLM-5.1: The Next Level of Open Source – Top-Tier Performance: #1 in open source and #3 globally across SWE-Bench Pro, Terminal-Bench, and NL2Repo. – Built for Long-Horizon Tasks: Runs autonomously for 8 hours, refining strategies through thousands of iterations. Blog: z.ai/blog/glm-5.1 Weights: huggingface.co/zai-org/GLM-5… API: docs.z.ai/guides/llm/glm-5.1 Coding Plan: z.ai/subscribe Coming to chat.z.ai in the next few days. — https://nitter.net/Zai_org/status/2041550153354519022#m
→ View original post on X — @kimmonismus, 2026-04-07 16:27 UTC
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Embeddings: The Unsung Hero Driving Model Accuracy Forward
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Embedding is an unsung hero in model accuracy and today is a big leap forward. It's at the heart of grounding; it's the layer that does the hard work of searching, retrieving, organizing, and connecting information across sources for a holistic response.
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Harrier Upgrades Bing Web Grounding for Agentic AI Era
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Bing's web grounding already powers almost every major AI chatbot today. With Harrier, it just got a big upgrade for the agentic era. Better embeddings lead to better retrieval, often more accurate answers, and better multilingual performance in the 100+ languages Harrier