An article featuring an interview with Sakana AI's Rujikorn Charakorn and Robert Lange, who led the development of the new technology "Doc-to-LoRA" that enables LLMs to reflect document content without additional training, has been published in Nikkei Cross Tech @nikkeibpITpro
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GENERATIVE AI
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Sakana AI Develops Doc-to-LoRA for LLMs Without Additional Training
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AI Training Shifting from Real Data to Synthetic Sources
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Jensen: AI training is shifting from real-world data to synthetic. Most information we share is already created, not natural. As AI enhances this synthetic data, training will soon be limited by compute power, not data availability. pic.twitter.com/cXgs2kp4pt
— Chubby♨️ (@kimmonismus) 24 mars 2026Jensen: AI training is shifting from real-world data to synthetic. Most information we share is already created, not natural. As AI enhances this synthetic data, training will soon be limited by compute power, not data availability.
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Google DeepMind and Agile Robots Partner for Advanced Robots
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Google DeepMind 🤝 Agile Robots Our new research partnership will integrate the Gemini foundation models with their hardware to help build the next generation of more helpful and useful robots. Find out more → goo.gle/4lKu7de [Translated from EN to English]
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AI CEO warns entry-level professionals face displacement within years
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Anthropic CEO:
— CG (@cgtwts) 24 mars 2026
“50% of all entry-level Lawyers, Consultants, and Finance Professionals will be completely wiped out within the next 1–5 years."
grad students and junior hires are cooked. https://t.co/mmDHhj6pOl pic.twitter.com/LGpi7kUl1yAnthropic CEO: “50% of all entry-level Lawyers, Consultants, and Finance Professionals will be completely wiped out within the next 1–5 years." grad students and junior hires are cooked. Claude (@claudeai) You can now enable Claude to use your computer to complete tasks. It opens your apps, navigates your browser, fills in spreadsheets—anything you'd do sitting at your desk. Research preview in Claude Cowork and Claude Code, macOS only. — https://nitter.net/claudeai/status/2036195789601374705#m
→ View original post on X — @mfordfuture, 2026-03-24 11:02 UTC
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DM0: Embodied-Native VLA Framework for Physical Understanding
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How do we build AI that truly understands the physical world from the ground up, not as an afterthought? A team from Dexmal & @StepFun_ai just unveiled DM0, a groundbreaking Embodied-Native Vision-Language-Action (VLA) framework. Unlike adapting web-trained models, DM0 learns
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Anthropic Rapidly Develops Competing Version of OpenClaw
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One has to admit, Anthropic sees a trend (openClaw) and develops their own version. The speed of their releases is insane. Presumably 100% code written by Claude.
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Multimodality Integration: The Real Upgrade for Production AI Systems
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My takeaway: The real upgrade is not just multimodality. It is collapsing text, vision, long context, and reasoning into one coherent workflow. That is how you move from demos to production-grade AI systems. I break it all down in my new video on Kimi K2.5 by Moonshot AI.
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Claude’s Operational Features: Thinking Mode, Speed, and Cost Control
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I also like the operational thinking behind it. You get: → Thinking mode for deeper reasoning and multi-step tool calls
→ Faster mode when latency matters
→ JSON mode, streaming, file-based Q&A
→ Token estimation so you can predict cost before heavy vision jobs And it is -
True Multimodal AI: Moonshot’s Native Text-Vision Integration
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Most “multimodal” AI is just duct tape.
— Ronald van Loon (@Ronald_vanLoon) 24 mars 2026
One model for text.
Another for vision.
A pipeline to glue it together.
But what happens when text + vision are native in the same model, with a 256K context window?
That is what Moonshot AI just changed.
A thread on what I learned from… pic.twitter.com/CmnuE9FNJxMost “multimodal” AI is just duct tape. One model for text.
Another for vision.
A pipeline to glue it together. But what happens when text + vision are native in the same model, with a 256K context window? That is what Moonshot AI just changed. A thread on what I learned from -
Native Multimodal Models: Architectural Shift in AI Integration
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The biggest shift is architectural. This is not text routed to a vision model. It is a native multimodal model. → Send base64 images or even videos directly into a chat completion request
→ Reason across text and visuals in the same workflow
→ No fragile orchestration layer