They’re not gone. Most Chinese AI companies are still building on architectures derived from DeepSeek.
If you actually read the research papers, it’s obvious. Hype cycles move fast.
Architectural influence lasts much longer.
MACHINE LEARNING
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DeepSeek’s Architectural Legacy Dominates Chinese AI Development
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Machine Learning for Dummies (3rd Edition) Book Announcement
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"Machine Learning for Dummies", by @lucamassaron and John Paul Mueller, now in its 3rd Edition: http://
amzn.to/44b8WJJ 𝙇𝙚𝙖𝙧𝙣:
What machine learning is, what it can do, and what it can't do Basics of machine learning code and how it integrates with large datasets -
Discussion on Neural Radiance Fields (NeRFs) rendering capabilities
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Now that is a very wrenderable radiance field
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Human-in-the-Loop Review Workflows for LLM Applications and Agents
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Human-in-the-Loop Review Workflows for LLM Applications & Agents https://
buff.ly/Pt9EanI
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
Measuring Math Performance LLMs Without Chain of Thought
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Measuring no CoT math time horizon (single forward pass) https://
buff.ly/JOmZJ4w #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Domino Data Lab Wins Three Dresner Advisory Tech Innovation Awards
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Thrilled to announce @DominoDataLab is a THREE-time repeat @DresnerAdvisory Tech Innovation Award winner in: AI, Data Science & Machine Learning ModelOps This is a testament to the trust our customers place in us to help scale AI innovation. https://
domino.buzz/4tINNC2 -
Generative UI: Rich Custom Visual Interactive Experience
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Generative UI: A rich, custom, visual interactive user experience for any prompt https://
buff.ly/I7tIhvK
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
Deep Learning Interview Questions: Complete Guide to Key AI Topics
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Deep Learning job interview questions, fully solved & covering a wide range of key AI topics: https://
bit.ly/4bv6FL9 credit: @papers_daily -
Ming-Yu and Kimmonismus discuss Cosmos, robotics, and physical AI
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Join Ming‑Yu, Vice President of Research at @nvidia, and @kimmonismus from Superintelligence today at 9 AM Pacific Time for a live conversation on Cosmos, robotics, and the future of world foundation models!#Robotics #Cosmos https://t.co/JhVqvymRPE
— Helen Yu (@YuHelenYu) 10 février 2026Join Ming‑Yu, Vice President of Research at @nvidia, and @kimmonismus from Superintelligence today at 9 AM Pacific Time for a live conversation on Cosmos, robotics, and the future of world foundation models! #Robotics #Cosmos NVIDIA AI Developer (@NVIDIAAIDev) Explore where physical AI is headed next with the people shaping it. On Feb. 10 at 9 a.m. PT, join Ming‑Yu, Vice President of Research at NVIDIA, and @kimmonismus from Superintelligence, for a conversation on how NVIDIA Cosmos reframes AI for a world of robots, AVs, and vision-driven systems. We'll dig into: ✅ Cosmos' origins and designing models for the physical world ✅ The scientific ideas and architectures behind Cosmos and its open models ✅ How open, reasoning-capable physical AI is changing how teams prototype, deploy, and iterate ✅ What a future of AI systems that understand space, time, and causality could unlock If you’re thinking into real‑world AI, this is the conversation to catch ➡️ nvda.ws/4a7fTit — https://nitter.net/NVIDIAAIDev/status/2020939396640538690#m
→ View original post on X — @yuhelenyu, 2026-02-10 16:18 UTC
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Unsloth achieves 12× faster MoE model training with 35% less VRAM
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You can now train MoE models 12× faster with 35% less VRAM via our new Triton kernels (no accuracy loss). Train gpt-oss locally on 12.8GB VRAM. In collab with @HuggingFace, Unsloth trains DeepSeek, Qwen3, GLM faster. Repo: github.com/unslothai/unsloth Blog: unsloth.ai/docs/new/faster-m…
→ View original post on X — @abhi1thakur, 2026-02-10 15:25 UTC