The amount of people here that skipped 1st grade algebra is astonishing. reckon they all did well in arts. ML/AI is maths, computers simply breaking down everything into numbers and for human brains to do the same, we need to be savants, AI is not stealing, AI is not sentient
ETHICS
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Robots Should Learn Some Manners and Etiquette
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robots should learn some manners! pic.twitter.com/i2NKZBz8tL
— clem 🤗 (@ClementDelangue) 13 février 2026robots should learn some manners!
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System Burden and Labor Challenges in Stretched Infrastructure
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We can try it, but that's an enormous additional labor burden on an already-stretched system
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AgentDoG: Real-time Diagnostic Framework for Safe AI Agents
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Can we trust AI agents to interact with the world safely without a clear way to diagnose their mistakes? Shanghai Artificial Intelligence Laboratory presents AgentDoG! It is a new diagnostic guardrail framework that monitors AI agents in real-time. Instead of just blocking
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Building Bridges Between AI and Hollywood at Sundance
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I recently spoke at the Sundance Film Festival on a panel about AI. Sundance is an annual gathering of filmmakers and movie buffs that serves as the premier showcase for independent films in the United States. Knowing that many people in Hollywood are extremely uncomfortable about AI, I decided to immerse myself for a day in this community to learn about their anxieties and build bridges. I’m grateful to Daniel Dae Kim @danieldaekim, an actor/producer/director I’ve come to respect deeply for his artistic and social work, for organizing the panel, which also included Daniel, Dan Kwan, Jonathan Wang, and Janet Yang. I found myself surrounded by award-winning filmmakers and definitely felt like the odd person out! First, Hollywood has many reasons to be uncomfortable with AI. People from the entertainment industry come from a very different culture than many who work in tech, and this drives deep differences in what we focus on and what we value. A significant subset of Hollywood is concerned that: – AI companies are taking their work to learn from it without consent and compensation. Whereas the software industry is used to open source and the open internet, Hollywood focuses much more on intellectual property, which underlies the core economic engines of the entertainment industry. – Powerful unions like SAG-AFTRA (Screen Actors Guild-American Federation of Television and Radio Artists) are deeply concerned about protecting the jobs of their members. When AI technology (or any other force) threatens the livelihoods of their members — like voice actors — they will fight mightily against potential job losses. – This wave of technological change feels forced on them more than previous waves, where they felt more free to adopt or reject the technology. For example, celebrities felt like it was up to them whether to use social media. In contrast, negative messaging from some AI leaders who present the technology as unstoppable, perhaps even a dangerous force that will wipe out many jobs, has not encouraged enthusiastic adoption. Having said that, Hollywood is under no illusions that AI will change entertainment, and that if Hollywood does not adapt, perhaps some other place will become the new center for entertainment. The entertainment industry is no stranger to technology change. Radio, TV, computer graphics special effects, video streaming, and social media transformed the industry. But the path to navigating AI’s transformation is still unclear, and organizations like the new Creators Coalition on AI are trying to stake out positions. Unfortunately, Hollywood’s negative sentiment toward AI also means it will produce a lot more Terminator-like movies that portray AI as more dangerous than helpful, and this hurts beneficial AI adoption as well. The interests of AI and Hollywood are not always aligned. (Every time I speak in a group like this as the “AI representative,” I can count on being asked very hard questions.) Most of us in tech would prefer a more open internet and more permissive use of creative works. But there is also much common ground, for example in wanting guardrails against deepfakes and a smooth transition for those whose jobs are displaced, perhaps via upskilling. Storytelling is hard. I’m optimistic that AI tools like Veo, Sora, Runway, Kling, Ray, Hailuo, and many others can make video creation easier for millions of people. I hope Hollywood and AI developers will find more opportunities to collaborate, find more common ground, and also steer our projects toward outcomes that are win-win for as many parties as possible. [Original text: deeplearning.ai/the-batch/is… ]
→ View original post on X — @andrewyng, 2026-02-13 16:22 UTC
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AI Forces Education Redesign but Impact Measurement Takes Years
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I hadn't thought about this, but it's true: we need to redesign how a lot of education works now that we can't evaluate student progress with essays and tests… but it takes years to reliably measure the real-world impact of any new changes we try
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AI Web Browsing Risks: Understanding the Pitfalls
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Letting AI Browse the Web for You Sounds Great — Until It Goes Wrong AI web browsing can save time, but things can quickly go awry — this article highlights the pitfalls and what you need to be aware of. Read more https://
bernardmarr.com/letting-ai-bro
wse-the-web-for-you-sounds-great-until-it-goes-wrong/
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OpenAI Policy Role Shift Away From Safety Alignment
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I had a very similar thought and wondered if I was overthinking it. Also, the fact that the role was announced via OpenAI’s DC-focused Substack blog makes me think it’s more of a policy & comms-focused role vs being truly a safety/alignment role like the team used to be.
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AI Programme Success Requires Strong Organizational Fundamentals
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Most AI programmes fail for the same reason sports teams lose, weak fundamentals. AI does not fail because the models are weak. It fails because organisations skip the basics, clear ownership, consistent training, good habits, and a way to measure progress that people trust.
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Competitor 90-Day AI Activity Analysis Template
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Step 1 – Data Collection (Gemini) Prompt: Analyze [COMPETITOR]'s last 90 days of activity: 1. Product launches or updates
2. Pricing changes
3. New hires (executive level)
4. Customer complaints (Reddit, Twitter, G2)
5. Website changes (new pages, messaging shifts) Format as