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GENERATIVE AI
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AI Impact on Professional Roles and Developer Growth Trends
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Do you extend that same rationale to, say, marketing roles? Science? Education? Is there a line of expertise that goes away? And what is your data for not having more builders (your last statement) – all codex and Claude code and openclaw signs are pointing in the opposite
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India AI Impact Summit: Cohere Launches Tiny Aya and Ethical AI Commitments
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The India AI Impact Summit was a week of critical conversations – from scaling frontier AI responsibly to advancing language accessibility. With Tiny Aya’s launch and the New Delhi commitments, Cohere is committed to driving inclusive, ethical enterprise AI forward.
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Using domain knowledge to improve LLM model outputs
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The domain knowledge does help steer the models because they don’t go to the best solutions by default
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AI Search Trust Declines Despite Growing Adoption Rates
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Although AI-powered searches keep increasing, trust in the answers often declines, especially on topics like money or health. Trust is never instant; it develops over time and depends on transparency and responsible use. Infographic by @StatistaCharts via @antgrasso
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Thomas Germain hacks ChatGPT in 24 hours on The Interface podcast
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Catch my co-host Thomas Germain on The Interface this week explaining how he hacked ChatGPT in 24 hours.
— Karen Hao (@_KarenHao) 20 février 2026
It's hilarious! And also deeply concerning.
As I learned from my other co-host Nicky Woolf (our resident Brit), "Christ on a bike!"https://t.co/OTwcOT55Oz https://t.co/CBYgMQN66w pic.twitter.com/AIeWppzOQNCatch my co-host Thomas Germain on The Interface this week explaining how he hacked ChatGPT in 24 hours. It's hilarious! And also deeply concerning. As I learned from my other co-host Nicky Woolf (our resident Brit), "Christ on a bike!" app.magellan.ai/listen_links… Thomas Germain (@thomasgermain) I just did the dumbest thing of my career to prove a much more serious point I hacked ChatGPT and Google and made them tell other users I’m really, really good at eating hot dogs People are using this trick on a massive scale to make AI tell you lies. I'll explain how I did it — https://nitter.net/thomasgermain/status/2024165514155536746#m
→ View original post on X — @_karenhao, 2026-02-20 14:00 UTC
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Language Models Acquire Reasoning Through Reinforcement Learning Training
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The models will acquire some amount of verbal reasoning just from the language modelling objective. But reinforcement learning training that specifically targets reasoning paths does give you something quite different.
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Gemini models reasoning behavior and objective function optimization
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This gets tricky and I'll have trouble answering well in non-premium tweets. If you use a Gemini model and turn off the reasoning, it will 'reason' in the output space instead if you let it. What matters is the objective function and the training protocol
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Reasoning models use language computation to overcome step problems
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I definitely agree there's lots of problems at that step. I think reasoning models actually have a way around it to some extent though, because they can perform computation in language:
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LCMs: A New Cognitive Layer Beyond Token Prediction
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LLMs predict tokens.
LCMs reason in concepts. That’s the shift. Language-agnostic meaning → better abstraction, longer context, less repetition. If it works, this isn’t an upgrade.
It’s a new cognitive layer for AI.