Huge! Google just proved Image Generators are Generalist Vision Learners! They introduce Vision Banana, a model built by instruction-tuning a base image generator (Nano Banana Pro). Instead of using special systems for different tasks, they reframe every vision problem—like
GENERATIVE AI
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Replit restricts manual coding education to GenAI projects
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Hey my kid was using Replit to learn *manual* coding, but it seems like now it’s only possible to create GenAI projects. Is that true?
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ChatGPT Images 2.0 Review: Best Model Currently Available
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NEW VIDEO in the LAB! Here I bring you a video testing, experimenting with, and judging ChatGPT Images 2.0's new image model The best model currently?
Well, I'll save you from watching the video: Yes, it is. Although it has a problem… Link below -
LFMs Enable Speech and Reasoning Directly in Vehicle Edge
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LFMs powering speech, language understanding, and reasoning directly inside the vehicle Very exciting times for edge models!
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Efficiency as Competitive Weapon Automating Away Competition
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Efficiency is becoming a weapon for the ambitious. When a top-tier worker can do most of a colleague's job in a fraction of the time, they are essentially automating away their own competition.
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Jensen’s Physics-Breaking Promises: A Critical Interview Analysis
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The Dwarkesh interview with Jensen is a testament to Dwarkesh's journalistic skill and dedication, while Jensen comes across as a coked up hustler who is promising to break the laws of physics and willing to sell his grandmother to China if it helps Nvidia's bottom line
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Sol-RL: Train AI Image Generators 4x Faster
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What if you could train AI image generators 4x faster without losing quality?
— 机器之心 JIQIZHIXIN (@jiqizhixin) 23 avril 2026
NVIDIA, HKU, and MIT researchers present Sol-RL.
They use a clever two-stage process: first, a super-fast, low-precision search creates a huge pool of image candidates. Then, they regenerate only the… pic.twitter.com/KokLk4tmr9What if you could train AI image generators 4x faster without losing quality? NVIDIA, HKU, and MIT researchers present Sol-RL. They use a clever two-stage process: first, a super-fast, low-precision search creates a huge pool of image candidates. Then, they regenerate only the
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Deep Research Token Usage and Billing Models
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Deep Research does use a lot of tokens, and it bills directly to the underlying models it uses behind the scenes (flash and pro).
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Taste as the Final Frontier: AI as a Tool for Vision Execution
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Taste is the final frontier of human value. If you don't bother with that final 10%, you are just a prompt operator; if you do, you are using the AI as a high-powered brush to execute a specific vision.
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Rising Expectations, Flat Grounding in AI Models
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Expectations are rising while grounding stays flat. For high-stakes local queries, the models are still just high-speed prediction engines that favor sounding professional over being actually correct.