Updated: alignednews.com/ai All the AI news discussed here on X today. Papers. Models. Events. Announcements. And more. [Translated from EN to English]
→ View original post on X — @scobleizer, 2026-04-07 02:15 UTC
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Updated: alignednews.com/ai All the AI news discussed here on X today. Papers. Models. Events. Announcements. And more. [Translated from EN to English]
→ View original post on X — @scobleizer, 2026-04-07 02:15 UTC
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do planes crash 4.6% of the time? no, not even close. but that’s the # the guy gave me as an estimate. when hallucinations are as rare as plane crashes, the world will be very very different.
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literally exactly what i said in March 2022. if only people had read the full article [nautil.us/deep-learning-is-h…] and not just the title, we wouldn’t be here now. Hillbilly Cosmologist (@RobinWeep) It took most of us several years but the magic has finally worn off. LLMs do not reason and are not intelligent. They're remarkable tools for accomplishing simple tasks, but they have real limits that are seemingly unsolvable without a paradigm shift. — https://nitter.net/RobinWeep/status/2041334881901322533#m
→ View original post on X — @garymarcus, 2026-04-07 02:10 UTC
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Do you even know who @GaryMarcus is? He has been doing fundamental work on AI since before you were born. He is far more of an expert on AI than you, or 99.999% of self-proclaimed "experts". He has always thought about AI in the right ways. You are attacking his authority?? [Translated from EN to English]
→ View original post on X — @garymarcus, 2026-04-07 02:05 UTC

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#AI Debt: The Hidden Cost Of Unchecked AI Acceleration by Amy Gu @Forbes Learn more: bit.ly/4sgieNH #MachineLearning #ArtificialIntelligence #ML #MI
→ View original post on X — @ronald_vanloon, 2026-04-07 01:58 UTC
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I'm enjoying building an AI that worries about what's coming next. It reads the entire AI community here and builds this site: https://
alignednews.com/ai all about the AI community here on X. And it's fun!

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10 Most Popular #MachineLearning Models by @goyalshaliniuk #ArtificialIntelligence #AI #ML #MI
→ View original post on X — @ronald_vanloon, 2026-04-07 01:37 UTC

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What if robotic hands could learn complex maneuvers purely in simulation and work perfectly in reality? ByteDance Seed just unveiled a breakthrough. Their new RL framework bridges the sim-to-real gap for dexterous hands with a fast virtual tactile simulation, current-to-torque calibration (no extra sensors!), and actuator dynamics modeling with randomization to cover real-world quirks. Result? Policies trained 100% in simulation directly enable a five-finger hand to perform precise, controllable grasp force tracking and object reorientation – a first for zero-shot sim-to-real multi-finger manipulation! Closing the Reality Gap: Zero-Shot Sim-to-Real Deployment for Dexterous Force-Based Grasping and Manipulation Paper: arxiv.org/abs/2601.02778 Project: dexmanip-seed.github.io/dexm… Our report: mp.weixin.qq.com/s/7TQC0sJfw… 📬 #PapersAccepted by Jiqizhixin
→ View original post on X — @jiqizhixin, 2026-04-07 01:35 UTC
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One thing about DL researchers that has always been surprising to me, is that a lot of them have never been exposed to forms of learning other than fitting the parameters of a curve via gradient descent, and are even unable to conceive that there might exist other options
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prima facie as long as context rot is a thing you are going to need specialization or you're gonna have a bad time