7/ The study found one thing that stopped the decline. When the AI made people reason through the answer themselves instead of just giving it, the skill stuck. Coach, not crutch. The difference was everything.
RESEARCH
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Pew: One in five US teens get news from AI chatbots
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6/ Here is who is doing it. Pew found one in five US teens now get their news from ChatGPT, Claude, or Gemini. The people still forming their instincts about truth are handing those instincts to a model.
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AI erodes your sense of truth, like GPS does for navigation
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5/ The researchers compared it to GPS. Follow turn by turn directions for a year and you can still reach any address. You also lose the ability to find your way without them. AI does that to your sense of what is true.
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AI improves fake news detection 21%, but feeling smarter is a trap
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2/ With the AI, people got 21% better at catching fake news. The chatbot worked. In the moment, it was a sharp lie detector. Everyone felt smarter. That feeling is the trap.
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MIT Media Lab Test: Discerning News With or Without AI
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1/ MIT's Media Lab conducted a simple test. 67 people. Four weeks. Their task was to examine news headlines and decide what was real and what was fake. Some did it with the help of an AI chatbot. Some did it alone.
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MIT Study: AI Destroys Our Ability to Discern Reality
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URGENT: A new MIT study has revealed that AI is destroying one of your most important skills. Discerning what is real. Here's what they found and how to stop it:
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AI Framework Creates Shadow Art from Object Scans
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Framework generates 'shadow art' from scan of any object
by Tom Fleischman @TechXplore_com Learn more: https://
bit.ly/4uYO5VB #GenerativeAI #ArtificialIntelligence #MachineLearning #ML -
Speculative decoding makes LLMs 8.5x faster without accuracy loss
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Researchers found a way to make LLMs 8.5x faster!
— Akshay 🚀 (@akshay_pachaar) 11 juin 2026
(without compromising accuracy)
Speculative decoding is quite an effective way to address the single-token bottleneck in traditional LLM inference.
A small "draft" model first generates the next several tokens, then the large… https://t.co/JCdqjCKcKU pic.twitter.com/HbKmRqdF5PResearchers found a way to make LLMs 8.5x faster! (without compromising accuracy) Speculative decoding is quite an effective way to address the single-token bottleneck in traditional LLM inference. A small "draft" model first generates the next several tokens, then the large
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Standardization of inter-paradigm evaluation for tabular encoders
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TRL-Bench Standardization of representation-level inter-paradigm evaluation for tabular encoders
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Toward Generalist Autonomous Research via Hypothesis-Tree Refinement
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Toward Generalist Autonomous Research via Hypothesis-Tree Refinement pic.twitter.com/NHDKezxAoY
— AK (@_akhaliq) 11 juin 2026Toward Generalist Autonomous Research via Hypothesis-Tree Refinement