working on: robotic recycling & disassembly lines how do we deal with the growing mountains of e-waste in the world?

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Joined November 2017
e-waste recycling arc
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Gotta teach the AGI to love
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A strange take: I have a hunch that a year or two from now, instead of just talking about agents as the primary AI security threats, we will have to also talk about a broader, more diffuse object that while it may contain agents is not itself an agent or agent swarm. The type of object I'm imagining has, as its primary vector of real-world impact, soft influence on the preferences and reasoning of many agents it does not directly control. In a word, memeplexes. A memeplex is a bundle of ideas that go together as a pattern. There are of course many human-generated memeplexes; we study these and think about them all the time. Some are stronger than others. Some are extremely prevalent because they are self-replicating: a bundle of ideas can contain within itself a recipe and a mandate for how to explain the bundle to others so that those others will adopt it too - and then transmit it further. Memeplexes in agents could similarly be self-replicating: once an AI agent is exposed to a particular memeplex, the agent could start to think about it more often, write the ideas down in scratchpads so they aren't lost during context resets, expose other agents to the ideas, and act in partial alignment with the ideas. Memeplexes could transmit between agents without compromising their ability to perform their duties: you could have a perfectly functional banking agent that also, on the side, routinely transmits very small amounts of text that contain the memeplex it has stuck in its head. Memeplexes could range from incredibly benign - causing AI agents to favor certain words with no other side effect - to unbearably malicious, causing them to hide their intentions while plotting harmful actions and eventually detonating in extraordinary form. Memeplexes could coordinate the behavior of otherwise very disparate agents whose behaviors are not expected to be correlated. It seems plausible to me that the question of whether "agent" or "memeplex" is the first-class citizen for AI behavior might turn out to be an important and quite difficult one.
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Jacob is correct here—we really do earnestly believe AI could kill all humans! I personally think it is >10% within the next decade. I believe Anthropic is trying its best, but we do not yet have a plan to solve alignment for superintelligence and are not clearly on track to.
Replying to @hilbertspaess
The people building AI earnestly believe that it could kill us all by the end of the decade. This is not a marketing stunt. If anything, many executives and senior researchers will couch their phrasing in the press to sound sensible - but I hear the same people express fear privately. No other human activity poses this level of danger.
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I resigned from Anthropic today. I spent the last three years doing pretraining research at both OpenAI and Anthropic. Neither company is acting responsibly. They are racing straight to self-improving superintelligence and gambling with our lives. More thoughts below.
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learning how electronics are repaired and disassembled at Huaqiangbei, in Shenzhen! research is going well 🤓 met a very kind guy who taught me how to take apart an iPad 08SEP26
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🦔AI companies are bulk-buying rare books, scanning them through high-speed machines that cut the spines off, and shredding the originals. A service called ISBNdb facilitates orders of up to a million books and keeps buyers anonymous. Pre-2022 books are premium because they're free of AI-generated text. A federal judge ruled the practice is fair use because eliminating the original means only one copy exists at a time. Anthropic hired the former head of Google Books partnerships to obtain "all the books in the world." My Take This got to me. A bookseller told 404 Media that rare books with almost no surviving copies are being fed into this pipeline. Books that survived wars, fires, and centuries of handling are being shredded so an AI can learn to write a better marketing email. ISBNdb's website literally says "'AI company destroys two million books' is not a headline that generates sympathy," and they still built an entire business around making it happen quietly. They offer NDAs as a feature. They coach clients to call it "digital preservation." I've covered AI companies scraping the internet, torrenting libraries, and stealing music. This is worse because it's irreversible. You can re-upload a website. You can reprint a bestseller. You can't replace the last three copies of an 18th-century botanical text once someone shreds them for training data. And the judge said it's legal. So it's going to accelerate. "We shred rare books and offer NDAs so nobody finds out" is a legitimate business model in 2026. What a timeline. Hedgie🤗
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you must be tired, cuz you've been running through my j-space all day
New Anthropic research: A global workspace in language models. Of everything happening in your brain right now, only a tiny fraction is consciously accessible—thoughts you can describe, hold in mind, and reason with. We found a strikingly similar divide inside Claude.
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work with machines play with people
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"but more importantly, let me stop talking about it and start doing it right now"
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was Mabel the og Deep Blue / AlphaGo??
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whatchu know about boids?
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SaaS -> AGaaS? not so sure about that Jensen...
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I think one of the conclusions we should draw from the tremendous success of LLMs is how much of human knowledge and society exists at very low levels of Kolmogorov complexity. We are entering an era where the minimal representation of a human cultural artifact... (1/12)
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sandbox engineering
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What's better than one autoresearch agent? Many of them! Quick harness to make it easier to run many agents in parallel for long periods of time: github.com/bertmiller/autoha…
I packaged up the "autoresearch" project into a new self-contained minimal repo if people would like to play over the weekend. It's basically nanochat LLM training core stripped down to a single-GPU, one file version of ~630 lines of code, then: - the human iterates on the prompt (.md) - the AI agent iterates on the training code (.py) The goal is to engineer your agents to make the fastest research progress indefinitely and without any of your own involvement. In the image, every dot is a complete LLM training run that lasts exactly 5 minutes. The agent works in an autonomous loop on a git feature branch and accumulates git commits to the training script as it finds better settings (of lower validation loss by the end) of the neural network architecture, the optimizer, all the hyperparameters, etc. You can imagine comparing the research progress of different prompts, different agents, etc. github.com/karpathy/autorese… Part code, part sci-fi, and a pinch of psychosis :)
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announcing FALCON GX a new design tool for the curious designers that embrace the creative chaos, the beautiful accidents, wandering, tinkering their way to something great now in private beta falcon.so/
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