Optimizing for ChatGPT and Perplexity search on top of Google is the move nobody’s thinking about yet. Good to see a tool already doing this out of the box.
INNOVATION
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OpenAI’s Sam Altman: token usage scaled 1 million times in 6 years
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OpenAI's @sama on scaling challenges: 6 years ago the top tokenmaxxer in the world was using 100k toks/mo, now that's the world median and top tokenmaxxer is > 100B toks/mo.
— Latent.Space (@latentspacepod) 3 juin 2026
That's a 1,000,000x in 6 years.
We think there's another 1,000,000x and global average usage of 100B… https://t.co/wMhihMvaEv pic.twitter.com/S5cvw3RcXfOpenAI's @sama on scaling challenges: 6 years ago the top tokenmaxxer in the world was using 100k toks/mo, now that's the world median and top tokenmaxxer is > 100B toks/mo. That's a 1,000,000x in 6 years. We think there's another 1,000,000x and global average usage of 100B
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Nitrosend: One Prompt Writes, Designs, and Sends to 10,000
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This is the part nobody saw coming. You don't log into Nitrosend, you just tell it what you want and the email lands in 10,000 inboxes.
— AI Highlight (@AIHighlight) 3 juin 2026
One prompt did the writing, the design, and the send. The dashboard is officially extinct. https://t.co/n5dFsooyWBThis is the part nobody saw coming. You don't log into Nitrosend, you just tell it what you want and the email lands in 10,000 inboxes. One prompt did the writing, the design, and the send. The dashboard is officially extinct.
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Vibe coding enables AI site, but change is inevitable
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I couldn't have built https://
alignednews.com/ai without vibe coding. It might be gone in 24 months. Change is constant. But vibe coding is real and is just at the beginning. -
Capabilities learned not inherited: building from ground up
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The phrase “capabilities should be learned, not inherited” is doing a lot of work here. It draws a clear line between imitating intelligence through distillation and building the internal machinery to generate, evaluate, and improve capabilities from the ground up. That
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Microsoft AI’s MAI-Thinking-1: Progress is a model-improving machine
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AI progress is not a model. It is a machine that keeps improving models. That is the core idea behind Microsoft AI’s new technical report: MAI-Thinking-1: Building a Hill-Climbing Machine This is not just a model release. It is a blueprint for turning frontier model
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Microsoft AI’s MAI-Thinking-1: A Hill-Climbing Machine for Frontier Models
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AI progress is not a model. It is a machine that keeps improving models. That is the core idea behind Microsoft AI’s new technical report: MAI-Thinking-1: Building a Hill-Climbing Machine This is not just a model release. It is a blueprint for turning frontier model
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DeepSeek Sparse Attention reduces complexity from O(L²) to O(Lk)
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3) DeepSeek Sparse Attention (DSA) DeepSeek’s recently released V3.2 model introduced DeepSeek Sparse Attention (DSA), which brought complexity down from O(L²) to O(Lk), where k is fixed. How it works: A lightweight Lightning Indexer scores which tokens actually matter for
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20 of 25 Top AI Researchers Say AI Will Soon Build AI
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20 of 25 top AI researchers say AI will soon build AI. For decades, humans built every AI system from scratch. That assumption is quietly breaking down inside frontier labs. A new paper interviewed 25 top researchers from Stanford, OpenAI, Google DeepMind, and Anthropic.
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Photoshop fakes OpenAI image model results, mocking its frontend performance
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Of course. And in Photoshop we can even reveal the usual grain pattern of OpenAI's image model. It amuses me, because nothing says more about the performance that your tool offers for frontends than not using its results, but instead trying to fake them with images.