To do research at this scale, we used Anthropic Interviewer—a version of Claude prompted to conduct a conversational interview. We heard from people across 159 countries in 70 different languages. Browse some of their quotes here: https://
anthropic.com/features/81k-i
nterviews#quotes
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RESEARCH
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Anthropic Conducts 81K Global Interviews Using Claude AI
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Unit Economics of Inference in AI Models
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Unit economics of inference is something I wish more people talked about. Will give this a listen!
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LangChain at GTC: Open Models Panel with Industry Leaders
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We're at GTC all week! Come say hello to the LangChain team at the NVIDIA booth Today at 12:30 PM at GTC, Harrison will join the panel “Open Models: Where We Are and Where We’re Headed,” alongside Jensen and the CEOs of Cursor, Thinking Machines Lab, Perplexity, and others.
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Xiaomi Launches Reasoning Model with Efficient Parameter Activation
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Xiaomi entering the reasoning model space is interesting. 15B active out of 309B is a nice efficiency ratio, curious how it performs on real-world coding tasks.
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Chaos Agents: Multiple AI Systems Unpredictable Interactions
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Chaos Agents: When Multiple AI Systems Interact in Unpredictable Ways
— Satya Mallick (@LearnOpenCV) 18 mars 2026
In this episode of Artificial Intelligence: Papers and Concepts, we explore Chaos Agents, a concept that examines what happens when multiple AI agents interact, collaborate, or compete within the same… pic.twitter.com/ZdJuoPb31YChaos Agents: When Multiple AI Systems Interact in Unpredictable Ways In this episode of Artificial Intelligence: Papers and Concepts, we explore Chaos Agents, a concept that examines what happens when multiple AI agents interact, collaborate, or compete within the same
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Scaling AI at the Edge: Axelera AI’s MWC Barcelona Insights
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Scaling AI at the Edge: Insights from MWC Barcelona
— Axelera AI (@AxeleraAI) 18 mars 2026
Most AI today is still tethered to the cloud. Why? Because the industry has lacked a solution that combines high performance with the price efficiency needed for true edge deployment.
At MWC Barcelona, our CEO and Co-Founder,… pic.twitter.com/XYjGGj9tl3Scaling AI at the Edge: Insights from MWC Barcelona Most AI today is still tethered to the cloud. Why? Because the industry has lacked a solution that combines high performance with the price efficiency needed for true edge deployment. At MWC Barcelona, our CEO and Co-Founder, Fabrizio Del Maffeo, shared how Axelera AI is changing this narrative. By building a hardware architecture from the neural network up, we are enabling enterprises to run powerful AI efficiently right where the data is created. Key Takeaways: Digital In-Memory Computing: Our unique architecture merges memory and computing on a single chip to deliver high throughput and low cost. The Power of Ecosystems: Real-world AI success isn't just about the chip. It requires a synergy of hardware, software, and strong partnerships with industry leaders like Dell Technologies, HP, and Lenovo. What’s Next: We are preparing for a future where world models and advanced sensing will redefine how devices interact with the world. Watch the highlights below to see how we're bringing the future of computer vision and edge inference to life. #EdgeAI #AIInference #ComputerVision #MWC26 #AxeleraAI #Innovation
→ View original post on X — @axeleraai, 2026-03-18 15:25 UTC
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User Experiences and Evaluations of AI Models Discussed
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it's a good model, would be interested to hear how your experience/ evals/ vibes with the models so far!
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Open Source Attribution and Compensation Models in AI Development
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Tough one. Open source gave us everything we build on today. I think we need better attribution and compensation models rather than pulling back entirely.
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Research Papers Predict Future Products Years in Advance
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Yet another dude who doesn't realize that before you get a product in your hands, there may be 5 years of technology development preceded by 10 years of fundamental research. Want to know what products will become available in a few years? Read research papers.
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Real-time Video Generation Breakthrough with NVIDIA Hardware
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A breakthrough in real-time video generation.
— Runway (@runwayml) 18 mars 2026
As a research preview developed with @NVIDIA and shared at @NVIDIAGTC this week, we trained a new real-time video model running on Vera Rubin. HD videos generate instantly, with time-to-first-frame under 100ms. Unlocking an entirely… pic.twitter.com/juafjvk0wmA breakthrough in real-time video generation. As a research preview developed with @NVIDIA and shared at @NVIDIAGTC this week, we trained a new real-time video model running on Vera Rubin. HD videos generate instantly, with time-to-first-frame under 100ms. Unlocking an entirely