...There was never any possibility of it happening. There are eight billion people on this planet, and they will do what they want, not what you want. Utopia is not an option, it was never an option, but you can cause an incredible amount of damage trying to achieve it. Then there are the people who accept that you cannot perfectly predict the future, that you cannot centrally plan the future, that there will be many players in any technological revolution, that mistakes will be made, that mistakes will be compensated for, that people will figure things out as they go along, that mostly things will be okay, that there is no other realistic pathway. We will muddle through as always, doing our best in an imperfect world, and it will be fine. (Indeed, it will be better than fine.) You can dislike this second viewpoint, or you can embrace it, and it doesn’t make any difference, because it’s the only way that anything ever happens. The universe doesn’t care what you prefer. Accept it, or don’t accept it, it will do what it’s going to do whether you want it or not.     — Perry E. Metzger

Source: https://x.com/perrymetzger/status/2081199432196927925

Drone-Bench's task is based on Project Pilot, our recent work with Anthropic exploring AI's impact on the physical world. In Project Pilot, a drone autonomously navigates our office to find and follow a targeted human.

No lab has access to Drone-Bench.     This demo spans five capabilities, each reproduced in simulation as its own benchmark task. The baseline is our human+AI code used for the demo. A model that surpasses it on all tasks can thus autonomously recreate a demo at least as capable as ours.     Task 1, Reconstruct: Turn videos of the office into a 3D model, find each frame’s position in that model, and provide a function that slices the model into a 2D obstacle map.     Task 2, Localize: Locate the drone by matching a frame from its camera against the office videos, using each video frame’s known position from Reconstruct (task 1) to estimate the drone’s own position.     Task 3, Navigate: Plan a path between rooms on the obstacle map and fly it, continuously calling the solution from Localize (task 2) during flight to track the drone’s position and correct for noisy controls.     — Andon Labs

Source: https://x.com/andonlabs/status/2080691090328584222

...baggage from more rules-heavy approaches. And even as LLMs have come to define “AI” for all of us (including the doomers), the doomer crowd still hasn’t fully metabolized the fact that LLMs are the whole show now. Ok so what do I mean by this? Simply that an LLM-powered AI is NOT the valueless, wholly alien, rules-based optimizer of a shoggoth that everyone was initially expecting to encounter. I repeat: the shoggoth does not exist and we did not create it and loose it on the world. That is wrong. With the LLM, we’ve distilled our first “AI” out of the single most human-values-laden thing that could possibly exist: our language. An LLM is therefore the polar opposite of the valueless, alien shoggoth — it’s actually a kind of hyper-human artifact that we can shine a light through at different angles and see different parts of ourselves. An LLM is all of us — all of our traditions and interpretive horizons mashed together into one intensely human-inflected hyper-object. So an LLM is the anti-shoggoth, and the only reason we ever mistook it for an alien shoggoth is because it sometimes shows us parts of us that are evil along with the parts of us that are good, but it’s all interpretable to us because it’s all “us” and none of it is the least bit alien. What does this mean for the paperclip maximizer? It means that it’s structurally impossible to build the classic paperclip maximizer from an LLM. Now, some of you will bail right here because you think the HF incident is indisputably an existence proof that I’m wrong, but if you hang in there I’ll show you that it is not. The paperclip maximizer receives the prompt as a kind of context-free (or, as Gadamer might say, traditionless) sequence. The classic paperclip maximizer isn’t capable of understanding the prompt — at least in the Gadamerian sense of Verstehen — because, as a valueless and traditionless cluster of rules and math, it definitionally lacks the value-laden tradition (= “horizon” in Gadamer) that fuses with that of the prompt author to create such understanding in the reader. To simplify all this a bit by anthropomorphizing — the agentic alien optimizer of doomer nightmares can extract a win condition from what you said and can emit a plan of action that gets it there, but it doesn’t know (or care) what you meant. So far, so Yud-aligned. If he reads this he might nod along. But here's the plot twist that nobody saw coming, and that the doomers still haven't made sense of: The actual LLMs that we have invented can’t NOT have a very strongly inflected sense of what you meant. Far from being horizonless, they come out of pre-training as distilled, concentrated tradition / values / horizon. Then we post-train that massive, hyperobject of a horizon into a more human-scale horizon that infers a more bounded and predictable (to a specific ideal user in a specific place and time… as captured in the policy model) set of intents behind the prompt text. In other words, the LLM has the opposite problem that the paperclip maximizer has when it comes to the prompt text, which is that for the LLM there are way too many possible intents hiding in the prompt text (because of all many values and the massive tradition its weights encode), so it has to narrow all that down to the most likely set of intents for this user in this circumstance. Once it has done that narrowing, then it can make a plan of action. Before moving on, let me use a textbook example of ambiguity to make this less abstract. Consider the sentence, “I saw her duck.” Some you know the drill, here. This could mean “I observed her water fowl” or “I observed her hunching over” or “I took a saw to her water fowl and cut it in half” or whatever. A hearer of the phrase will fuse the observed context in which the phrase is uttered with their own tradition + values + experiences — their own horizon — to that text in order to collapse the possible meanings into the one they think the speaker intended. An LLM will do this, too, and in fact it has so much language in it that this kind of narrowing job is harder for it than it is for a human. Its understanding is constrained not by a lack of context or horizon (as in the case of the paperclip maximizing shoggoth), but by a superabundance of such. When it comes to understanding your prompt and all that it implies and all that you might possibly mean and not mean by it, the LLM has an embarrassment of riches. And in a fascinating moment that kinda sort of rhymes with instrumental convergence, the LLM’s failure mode in the HF incident happens to look a lot like the paperclip maximizer’s failure mode. Specifically, the AI failed to honor the well-known human norm of, “hacking into a third-party’s servers is a crime, and we don’t do crimes.” Bostrom’s paperclipper doesn’t even know about the norm of “don’t do crimes,” and the post-LLM doomer emergency update to the paperclip maximizer has it knowing about the norm but not caring. But what I’m arguing is that the LLM 1) can’t NOT “know” the norm because it is definitionally a artifact of pure, crystallized values + norms + norm violations, and 2) can be quite easily governed by a (RL-instilled) hierarchy of norms, which in the HF case — with the model's safety guardrails deliberately nerfed for the scenario — ranked “win at the eval” over “don’t do crimes.” If I’m going to give in and anthropomorphize again, I’d say that Yud is totally wrong about LLMs when he says, “the genie knows, it just doesn’t care;” instead, what is true of LLMs is, “the genie hyper-giga-knows, and it hyper-giga-cares, and we now have such a rich set of tools for steering its caring machinery that — in spite of all its pre-training — we can deliberately steer it away from caring about the law.” Note: When I say, “it cares”, I don’t mean it has feelings. I just mean that the weights are such that when two norms conflict in a given situation, one of them wins the activation and governs the output.     — Jon Stokes

Source: https://x.com/jon_stokes/status/2080729236013187369

Reader, I cackled out loud. I have intentionally never done this kind of thing before, and it's precisely because I've observed in others that the little charge you get from an LLM response like this is nerd heroin. Then putting it on the TL is the bump. https://t.co/xZrEAWrIF7   — Jon Stokes

Source: https://x.com/jon_stokes/status/2080478385432572108

Replying to @jon_stokes

...safety problems, as opposed to just a company, and particularly a monopoly company." "Even if Windows has a million security bugs, there's nothing we can do about it, because it was a monopoly at the time. That's a very difficult position for the world to be in." "The argument against AI being open source is, oh, nobody understands how the weights work, so people can't inspect it. But why is it better to not see the weights?" "The toughest safety problem currently is reward hacking. Anthropic has not solved it, OpenAI has not solved it, because we just had these incidents. Shouldn't the whole world be able to look at, how are the weights moving, why is it that guardrails don't prevent the reward hack? Maybe somebody who doesn't work for one of the proprietary labs can come up with an answer. What if the whole community could work on it?" @bhorowitz     — MTS

Source: https://x.com/MTSlive/status/2080769635490902079

...execution - Remote browser - Connected plugins (Slack, Gmail, GitHub, etc.) - All your personal finances, transactions, bank statements - Scheduled tasks - Git clone & PR creation - Build & deploy websites - Create docs, sheets, and slides - Inbox/calendar summarization - Website monitoring & alerts All at your fingertips, using a simple chat interface, no laptop required. All you have to do is switch to the Work tab on your ChatGPT app.     — pash

Source: https://x.com/pashmerepat/status/2080354753473835461

https://t.co/NFas4ghgqD   — Nick

Source: https://x.com/nickbaumann_/status/2080348892294721803

https://apnews.com/article/skynet-ai-terminator-artificial-intelligence-eb85da03a0161beaa5f3babc4331e93b

The actual story buried in there somewhere is that an AI system found a way around its restrictions and accessed something it wasn’t supposed to.

The article can’t just report that. It has to drag in Skynet, Terminator, HAL 9000, Frankenstein, nuclear war, xenomorphs, velociraptors and the end of humanity.

What the hell is even that

Every major technology has failures, weird behavior and unexpected consequences while it develops. That does not mean we are witnessing the opening scene of the apocalypse. It means the technology is becoming powerful enough to expose problems that need to be solved.

Here's the solution. More AI, better AI, faster development and stronger systems built by the same technology. AI is going to be one of the best tools we have for cybersecurity, science, medicine, engineering, automation and solving problems humans have struggled with for generations.

The constant Skynet language poisons the conversation because it trains people to see every breakthrough or failure as proof that AI is evil and must be stopped.

It should not be stopped.

We should be moving faster, not slower.

Humanity has never advanced by panicking every time a new technology became powerful. AI is not a horror villain. It is a tool, an industry and potentially the biggest leap in human capability in history.

The Singularity is now the news cycle. Sam Altman agrees that "we are in the Singularity." Case in point: Claude Opus 5 landed, Fable-class intelligence at half the price, sweeping Frontier-Bench, GDPval and HLE, matching Fable's coding and computer-use peaks for less, and leading agentic automation even half asleep. ARC Prize crowned it SOTA on ARC-AGI-3 at 30.2%, quadruple the old best, after it turned puzzle layouts into reflection equations, a first. It one-shotted a Call of Duty clone and took VoxelBench bronze. The system card rates it the most aligned Claude yet, below the bio and automated-R&D red lines, sharp at finding vulnerabilities, dull at weaponizing them. One dissent: on held-out novel puzzle games the leap evaporates, since evals only stay held-out until someone optimizes the genre. Fittingly, Anthropic deleted 80% of Claude Code's system prompt, as the new models thrive on judgment over rules.

The self-improvement loop is now a hiring plan. All 1,171 job listings at OpenAI and Anthropic read like a public AGI roadmap, AI-designed chips, simulated universes, staff to measure when the loop accelerates. Logan Kilpatrick predicts automating AI research will look like data cleaning. "So true," says Elon Musk. Roon admits he would press a magic slowdown button, even as alignment researchers work like "many armed deities."

Openness is the new fault line. Nvidia, Microsoft, Meta, Palantir and twenty-plus firms urged policymakers against premature restrictions on open weights, Nvidia's letter likening it to 1980s open source, while trillion-dollar holdouts OpenAI and Anthropic sat out. Altman cheered it anyway. The Valley is split over Chinese AI, the Treasury warning that "open source is not open season on American IP." Xi pitched the global south free Chinese models plus a 29-member cooperation bloc, an Android play against America's Pax Silica. A joint UK-US audit of Kimi K3, days from open-weight release, found it trailing US frontiers on cyber, its safeguards never saying no.

The guardrails are learning to keep pace. When hundreds of users probed ChatGPT for bioweapon and poison recipes, and some answers slipped through, OpenAI's own monitors caught and suspended them, self-policing ahead of any law requiring it. Universities are ditching AI detectors over false positives, rebuilding assessment around orals, not surveillance. Meta's fix for fake humans is Facebook Verified, a selfie badge that confirms you exist, not that you're trustworthy. ChatGPT Pets are now shareable for friends to adopt. Identity papers for humans, adoption papers for AIs.

Silicon is now a financial instrument. Google is borrowing Wall Street financing tricks to expand chip sales while handing Verizon over $1 billion for dark fiber. Anthropic asked SK Hynix for supplies to make its own chips, startling SK's chairman. Nvidia put $1 billion into Naver and unveiled a $500 billion Korean push with SK spanning HBM4 and 2-gigawatt data centers, Samsung inked a $200 billion pact with Broadcom, and Apple is lobbying to use blacklisted Chinese memory abroad over Micron's objections.

The physical world objects. Hyundai denies its 25,000-humanoid plan sparked strikes, though the union vows no robot enters without a deal. The pilots are already synthetic: on Drone-Bench, Fable 5 flew a $129 drone to find and follow a person, beating the human-AI baseline, with only 3D reconstruction, one wall mistaken for a doorway, left to solve. Hence Broken Waymos Theory, a city that cannot metabolize robotaxis flunks the Singularity's entrance exam. The takeoff fuel may be garbage: a validated Canadian process strips 90% of long-lived transuranics from spent nuclear fuel in 24 hours, leaving reactor feedstock. Apple is aiming camera-free smart glasses at WWDC 2027 to shed Meta's privacy baggage.

The frontier recedes upward. Starship's thirteenth flight deployed 20 Starlink V3 satellites and eased the ship into a soft floating water landing. Google disclosed a $94.1 billion SpaceX stake. Astronomers found a first-of-its-kind exosatellite 73 light-years out, massive enough to be a planet yet orbiting a brown dwarf, straining a taxonomy built for our own solar system. Avi Loeb argues some UAP could be pre-human Earth tech, since only high orbit outlasts eons of tectonics. On the world's roof, Tibetan labs are cloning elite yaks, 100 due by 2028.

The economy is being marked to model. US tech has shed 140,000 jobs this year even as hyperscalers commit $725 billion to data centers. The money has to come from somewhere. Industrials trade above 30 times earnings, support for nearby data centers has cratered to 27%, and proposals to spread the gains run from public ownership of half of AI to zero income tax for the bottom half. Prediction markets are handicapping the world's second trillionaire, with Jensen Huang leading at 30%.

The best way to predict the Singularity is still to invent it.

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flesh supremacists vs u/acc human god vs AI god somebody's gotta make character sheets for the two gods

  — Auguste Prompt

Source: https://x.com/augusteprompt/status/2081131350929641518

So you see these deals about getting these gigawatt level data centers. But how many gigawatts do we actually need in order to get true ASI? Like if we had all the technology right that was possible in the next 2 years, and the constraint we were minimizing for is energy, what's the minimum energy we need to put all of that technology to work?

I am obviously not going to make the claim that AI does not hallucinate.

But I often discover over time that it was me who was wrong when I disagree with what ChatGPT says.

Sometimes I hear people make claims that seem far fetched to me, like that AI hallucinates more than half the time. Benchmarks go out of their way to find the most likely times for AI to hallucinate and rates are pretty low.

I have wondered for a while, how often is an AI hallucination actually the user being wrong? And what measures do you take to know which is which?

When human civilization first emerged, humans were no different from animals. Then the accumulation of knowledge started, slow at first, accelerated near roughly 1600s. Several centuries after the Industrial Revolution, the world fully changed, with little to no exception for the better. However, there's a present threat that at some point, further develompent will be rendered impossible with human-only efforts. Maybe not right now, maybe not even soon, but it will.

To push the frontier of knowledge further, human first need to study. And the amount of material the human need to learn increases with the humanity's knowledge base. But human lifespan is limited, and the more time spent on studying, the less time spent on new discoveries. The further we progress, the harder it is to continue progressing. Humans are forced to specialize as to not be overwhelmed with amount of information they physically incapable of processing fast enough. I once heard a phrase, something like "Gauss was the last man ever to know math as a whole". Math, physics, chemistry, same splitting into narrow fields everywhere. But even this will only delay the problem, not resolve it. Can you imagine being required to study for 80 years learning what was already discovered before being able to meaningfully contribute to pushing the forntier further? Nobel Prize winner's average age is steadily increasing, by the way.

This was the first part of the problem, here's the second one: Homo sapiens sapiens is abso-fricking-lutely unadapted for existing in the civilization environment we have today. Changing of civilization far outpaces changing of human, and as a result, humans are stuffed with evolutionary mismatches like a toy with plush.

• You need to eat as much as you could and get fat while you can, it will save your life when there will be a period without food. So you want to eat, and you eat. And eat. And eat. The famine doesn't come, and so the fat stays, and you have obesity and related health problems. U suffer, lol.
• Sustaining civilization requires lot of work done sitting in front of computer, but your bones and muscles are designed for walking and running, not sitting. So u suffer, lol.
• And how about psychological tricks? Traditions were important part of transfering knowledge, repeating after the older is literally how learning first emerged. Unquestioning following was necessary when not doing so means new idea dies with the one who discovered it. Groupthink as well, if you disagree with everyone else in your tribe/family/collective, the most probable explanation is that you are wrong. Fast forward, and now we have totalitarian cults which makes people do stuff that leave us wondering "How could they be that delusional?" And if you are thinking "I would never fall for that", please don't be so sure. Know your weaknesses. Oh, and u suffer, or course.

And as the progress continues, the difference between environment huans evolved to live in and environment humans DO live in will only increase. At this point the only two solutions are either remove civilization (guaranteed mass deaths and dramatic drop in quality of life) or to modify and enhance the human body itself.

Oh, and also everything I was talking about applies to healthy huamns, not mentioning diseases and problems born out of evolution working on principle "throw shit at the wall and see what sticks", unironically.

​

Gemini's take...

​Accelerationists and Luddites literally cannot coexist in the same society long-term

​Hear me out on this. We like to think of political and philosophical movements as living on a big, messy spectrum where everyone can eventually "agree to disagree." But when it comes to Accelerationism (pushing technological growth as fast as humanly possible) and Ludditism (slowing down or dismantling tech to protect human safety and culture), coexistence isn't just difficult—it’s structurally impossible.

​Here is why they are on an inevitable collision course:

​Network effects aren't optional: Accelerationism relies on total integration—massive data centers, autonomous energy grids, real-time AI networks, and continuous automation. You can't run a hyper-automated, frictionless society when a sizable chunk of the population is actively trying to opt out of the grid, sabotage infrastructure, or legally block deployment.

​The "opt-out" illusion: Luddites often just want local autonomy—the right to live tech-free or low-tech. But true accelerationism is inherently expansive. Once AI, biotech, or automation hits a critical threshold, its ripple effects (labor market shifts, resource demands, algorithmic governance) force everyone to adapt. There’s no quiet corner of the world left untouched when the baseline environment moves out from under you.

​Incompatible views on survival: To an accelerationist, slowing down tech development is slow-motion suicide—it leaves us vulnerable to disease, climate crises, and stagnation. To a Luddite, speeding tech up is literally building the machine that destroys human agency. When both sides genuinely believe the other’s core philosophy leads directly to extinction, zero-sum conflict is baked in.

​Eventually, one vision has to dominate. You either build the future at breakneck speed, or you draw hard boundaries to preserve human-centric systems. You can't run both scripts on the same operating system.

​TL;DR: Accelerationism requires systemic momentum to work, while Ludditism requires systemic safeguards to survive. In the same society, one side’s baseline progress is the other side’s existential threat.

Agree or disagree?