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The AI tools you use every day — Claude, ChatGPT, Gemini — are, in a meaningful sense, frozen in time. They learned everything they know during a multi-month training run, and then the learning stopped. New research published in 2025 and 2026 is attacking this problem from five different angles simultaneously. Here’s what’s actually working,…
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SciPy 1.0 was published in February 2020. In the twelve months ending October 2025 it was cited 1,731 times. That is a five-year-old methods paper picking up roughly five new citations per day, with the rate still climbing. Its acceleration over the prior year is +94 per month, the third highest in the entire top-300…
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Most “trending papers” lists are annual cuts: how many times a paper got cited this year versus last. That misses the shape of the curve. A paper that quietly clocked 200 citations evenly across twelve months looks identical to one that went from 5 per month to 40 per month. The second is actually taking…
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In 2023 the European Society of Cardiology published its first comprehensive guideline on cardiomyopathies. OpenAlex has already logged more than 2,100 citations to that single document, a pace that puts it among the fastest-accelerating clinical papers of 2024. The guideline itself is not the story. The story is what it quietly codified: a drug class…
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Steven Pinker’s Enlightenment Now proves that, on a 200-year baseline, almost everything is up and to the right. Peter Thiel’s The End of the Future argues that, since 1973, almost nothing in the physical world is. Both can be true. The trick is to plot each metric on its own longest available baseline and see…
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Peter Thiel said in 2011 that the future had stalled. Ray Kurzweil said in 2005 that the future was on schedule. Reading both texts now, with a 9.3-million-patent corpus running underneath them, the answer is that they were arguing about different decades — and that the inflection between those decades happened, with disconcerting precision, the…
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What started as a search for hidden innovation in medical devices turned into something bigger — a vision for how AI-driven R&D will need to coordinate across fields, and the infrastructure that doesn’t exist yet.
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Kurzweil’s 2005 defense of speech recognition got every claim right and the architecture wrong: HMMs lost to transformers, but the destination arrived bigger than promised.
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Two patents, one mile of rock, and a Berkeley father-daughter team plan to take a nuclear reactor critical inside a Kansas industrial park on July 4.
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Kurzweil bet machine-rights litigation would lead. Idaho and Utah passed statutes to block it. The cloud he expected to distribute concentrated instead.
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For sixty years, MEG required a copper-and-steel shielded room. The latest atomic-vapor magnetometer patents are quietly making the vault optional.
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Twenty years on, the anatomy survived. The grand cognitive theories did not.
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Apple killed its decade-long microLED display project in 2024. The same year, a Sunnyvale startup hit 200 femtojoules per bit shooting data between AI chips with the same physics — and now holds 84% of US patents in the niche.
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Kurzweil called the curves on connectomics and brain decoding. He missed on the wires — optic nerve, spindle cells, and millisecond fMRI.
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79 US grants for direct-to-cell satellite tech issued in 2025. Twenty-three belong to Qualcomm. Zero belong to SpaceX or AST SpaceMobile.
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Twenty years after Kurzweil predicted gray goo, blue goo, and brain-replacing nanobots, the threat model evaporated and a different nanotech stack — DNA origami, monocyte-piggybacking implants, stentrode brain interfaces — quietly delivered the medicine he didn’t predict.