https://x.com/nadzi_mouad/status/2008078841734942973?s=20

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Oh what a year its been, AI edition https://simonwillison.net/2025/Dec/31/the-year-in-llms/

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Need a quick summary of an article that is too verbose or confusing? Use the following prompt: > Summarise this article using Barbara Minto's situation complication question answer (SCQA) format, <article URL> Example: > Summarise this article using Barbara Minto's situation complication question answer (SCQA) format, https://psyche.co/ideas/the-existential-balm-of-seeing-yourself-as-a-verb-not-a-noun

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yOu CaAn leRn A L0tt aT NeURips

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The Gemini watermark 😂 https://x.com/512x512/status/1993099213627138124?t=D9rqdl8teaYj-wLOE11Pzw&s=19

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Cool new model for 2D still to 3D model.

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Towards deterministic LLM inference https://youtu.be/BbI8n9XZJo4?si=Q0CleVkaIydIzVMT

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When Vishal Sikka was infosys ceo he wanted to make investment in OpenAI around 2015-2016, which didn’t happen and he was out as CEO after some time. One of the biggest fumbles I guess https://timesofindia.indiatimes.com/technology/tech-news/45-billion-ai-opportunity-lost-ca-reveals-how-narayana-murthy-and-vishal-sikka-clash-blocked-infosys-2015-openai-bet-and-indias-tech-future/amp_articleshow/124064414.cms https://x.com/alokgoyal1971/status/1986782778231603302

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"We predict that the impact of superhuman AI over the next decade will be enormous, exceeding that of the Industrial Revolution. We wrote a scenario that represents our best guess about what that might look like. It’s informed by trend extrapolations, wargames, expert feedback, experience at OpenAI, and previous forecasting successes." https://ai-2027.com/race

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How is Tensorflow doing across the community? Or has PyTorch like completely won the ML lib competition? It really looks like most innovation by very far get done on PyTorch now. Has TF any edge remaining? Perhaps on embedded or massively parallel configurations?

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Type this into your favourite ai chatbot. > You know me quite well now, smoke out any obvious flaws in my reasoning, describe them and suggest approaches to address them.

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Any recommended material to learn about the rational behind diffusion models like DDPM and other noise-based generators?

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Extropic is getting its probabilistic computer out. "We have three announcements to make: * We designed the world's first scalable probabilistic computer. * We fabricated probabilistic circuits that perform sampling tasks using orders of magnitude less energy than the current state of the art. * We have developed a new generative AI algorithm for our hardware that can use orders of magnitude less energy than existing algorithms." https://extropic.ai/writing/thermodynamic-computing-from-zero-to-one

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https://www.oneusefulthing.org/p/an-opinionated-guide-to-using-ai

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What is your experience with LLM-augmented colleagues at work? Mine is for now pretty much aligned with this: https://hbr.org/2025/09/ai-generated-workslop-is-destroying-productivity At the same time Google claims this week 90% of tech workers there use AI (did not look into the detail). https://ground.news/article/google-says-90-of-tech-workers-are-now-using-ai-at-work_2c7e21

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