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Engram Memory for Agents on OCI - Part 1. The Why and the What

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  Copyright: Sanjay Basu 1. Why Memory, and Why Now Long context is not memory. This is the sentence I keep wanting to staple to people’s foreheads at conferences. Yes, frontier models will happily accept two million tokens of input. No, that does not mean stuffing every prior conversation into the prompt is a good idea, even if you can afford the bill, which most companies cannot. The empirical case against the long-context-as-memory pattern is by now embarrassingly well documented. The original Lost in the Middle paper from Stanford showed that retrieval accuracy collapses when relevant facts are buried in the middle of a long context window. Every follow-up study since (NoLiMa, Michelangelo, RULER, the whole genre) has confirmed the same shape. Effective context length is much smaller than nominal context length. The model’s attention is not democratic. It cares about the beginning, it cares about the end, and the middle goes to the same place socks go in the dryer. Then yo...
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The Chip Designs Itself Now

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  Autonomous AI Agents Have Quietly Started Rewriting the Tools That Rewrite Silicon I first came across this particular kind of news that arrived without a press release. No keynote, no crowd in a dim auditorium in San Jose, no breathless CNBC segment. Just a PDF quietly parked on arXiv, the kind of paper that looks unremarkable until you read the abstract twice and realize what it actually says. Then, of course, the fireside chat that Anirudh had with Jensen. The paper in question is from NVIDIA Research and the University of Maryland, and its claim is modest in tone and enormous in implication. A team of large language model agents, they report, was pointed at ABC, the million-plus-line open-source logic synthesis system that has been the de facto academic and industrial backbone of chip design research for two decades. The agents were not asked to use ABC. They were asked to evolve it. To rewrite its C code. To improve the tool itself. After thirty-some cycles of automated comp...
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The Ghosts We Can’t Find

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  Copyright: Sanjay Basu Phantom particles, phantom minds, and the narrowing of scientific imagination. What happens when science’s most powerful tools make it harder to see? For twenty years, physicists chased a ghost. The sterile neutrino was a hypothetical particle that interacted with nothing, registered on no detector, and left behind exactly zero evidence of its physical existence. It was, by almost every empirical measure, not there. Physicists loved it anyway. They loved it the way you love a theory that is too elegant to be wrong, too mathematically tidy, too perfectly shaped to fill the exact holes in your understanding. This month, the last experiments that could have saved it reported back with devastating news. The sterile neutrino is dead. But its ghost, and the questions it raises about what we can and can’t find, is very much alive. Because here’s the thing. The sterile neutrino is not the only phantom haunting science right now. At the same moment particle physicis...
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