corbin

I'm sorry you had to learn this way. Most of us find out when SciShow says something that triggers the Gell-Mann effect. Green's background is in biochemistry and environmental studies, and he is trained as a science communicator; outside of the narrow arenas of biology and pop science, he isn't a reliable source. Crash Course is better than the curricula of e.g. Texas, Louisiana, or Florida (and that was the point!) but not better than university-level courses.

Okay. It feels like your comment is totally disconnected from evidence and reality. Also, it feels like you didn't actually want to make a germane comment. Finally, it feels like you don't have anything of substance to add, regardless of relevance.

Spoken like somebody who has zero commits in Chrome or Chromium, to be honest.

A lot of court documents are sealed or redacted, so I can't quite get at all the details. Nonetheless here's what I've got so far:

• Chrome is just the browser, including Chromium, but not ChromiumOS (a Gentoo fork, basically) or ChromeOS (the branded OS on Chromebooks)
• Chrome is unaffordable because it was quite expensive to build and continues to be a maintenance burden
• The government is vaguely aware that forcing a sale of Chrome could be adverse for the market but the court hasn't said anything on the topic yet
• Via filing from Apple, the court is aware that Firefox materially depends on Google, although they haven't done much beyond allow Apple to file as amicus

The court hasn't cracked open AMD v Intel yet, where it was found that a cash remedy would be better than punishing the ongoing business concerns of a duopoly, but it would be one possible solution: instead of selling Chrome, Google would have to pay its competitors a lump sum and change their business practices somewhat.

I am genuinely not sure what happens to "the browser market", as it were. The Brave and Safari teams are relatively small because they make tweaks on top of an existing browser core; the extreme propagation of Electron suggests that once a browser is written, it does not need to be written again. The court may find browsers to be a sort of capital which is worth a lot of money on its own but not expensive to maintain. This would destroy Mozilla along with Google!

I encourage NYC neighbors to spread the idea of deranking. It worked in Portland. We had an exceptionally shitty candidate:

Once touted as the law and order candidate, Gonzalez was the only mayoral candidate cited for breaking the law during the 2024 election cycle.

We pushed to derank him. And the result:

… Gonzalez was the subject of an effort to convince voters not to rank him regardless of the voter's other preferred candidates. Gonzalez earned 20% of first ranked choices but ultimately finished the election in third place …

I don't know about Ed, but I've had scenes from Network stuck in my head for months, particularly the scene where the corporate hatchet man Hackett is explaining that a Saudi conglomerate is about to buy out a failing TV network. He says, "We need that Saudi money bad."

It's the cost of the electricity, not the cost of the GPU!

Empirically, we might estimate that a single training-capable GPU can pull nearly 1 kilowatt; an H100 GPU board is rated for 700W on its own in terms of temperature dissipation and the board pulls more than that when memory is active. I happen to live in the Pacific Northwest near lots of wind, rivers, and solar power, so electricity is barely 18 cents/kilowatt-hour and I'd say that it costs at least a dollar to run such a GPU (at full load) for 6hrs. Also, I estimate that the GPU market is currently offering a 50% discount on average for refurbished/like-new GPUs with about 5yrs of service, and the H100 is about $25k new, so they might depreciate at around $2500/yr. Finally, I picked the H100 because it's around the peak of efficiency for this particular AI season; local inference is going to be more expensive when we do apples-to-apples units like tokens/watt.

In short, with bad napkin arithmetic, an H100 costs at least $4/day to operate while depreciating only $6.85/day or so; operating costs approach or exceed the depreciation rate. This leads to a hot-potato market where reselling the asset is worth more than operating it. In the limit, assets with no depreciation relative to opex are treated like securities, and we're already seeing multiple groups squatting like dragons upon piles of nVidia products while the cost of renting cloudy H100s has jumped from like $2/hr to $9/hr over the past year. VCs are withdrawing, yes, and they're no longer paying the power bills.

I went into this with negative expectations; I recall being offended in high school that The Flashbulb was artificially sped up, unlike my heroes of neoclassical guitar and progressive-rock keyboards, and I've felt that their recent thoughts on newer music-making technology have been hypocritical. That said, this was a great video and I'm glad you shared it.

Ears and eyes are different. We deconvolve visual data in the brain, but our ears actually perform a Fourier decomposition with physical hardware. As a result, psychoacoustics is a real and non-trivial science, used e.g. in MP3, which limits what an adversary can do to frustrate classification or learning, because the result still has to sound like music in order to get any playtime among humans. Meanwhile I'm always worried that these adversarial groups are going to accidentally propagate something like McCollough stripes, a genuine cognitohazard that causes edges to become color-coded in the visual cortex for (up to) months after a few minutes of exposure; it's a kind of possible harm that fundamentally defies automatic classification by definition.

HarmonyCloak seems like a fairly boring adversarial tool for protecting the music industry from the music industry. Their code is incomplete and likely never going to get properly published; again we're seeing an industry-capture research group taking and not giving back to the Free Software community. I think all of the demos shown here are genuine, but he fully admits that this is a compute-intensive process which I estimate is going to slide back out of affordability by the end of 2026. This is going to stop being effective as soon as we get back into AI winter, but I'm not going to cry for Nashville.

I really like the two attacks shown near the end, starting around 22:00. The first attack, if genuinely not audible to humans, is likely a Mosquito-style frequency that is above hearing range and physically vibrates the components of the microphone. Hofstadter and the Tortoise would be proud, although I'm concerned about the potential long-term effects on humans. The second attack is again adversarial but specific to models on home-assistant devices which are trained to ignore some loud sounds; I can't tell spectrographically whether that's also done above hearing range or not. I'm reluctant to call for attacks on home assistants, but they're great targets.

Fundamentally this is a video that doesn't want to talk about how musicians actually rip each other off. The "tones and rhythms" that he keeps showing with nice visualizations have been machine-learnable for decades, ranging from beat-finders to frequency-analyzers to chord-spellers to track-isolators built into our music editors. He doubles down on copyright despite building businesses that profit from Free Software. And, most gratingly, he talks about the Pareto principle while ignoring that the typical musician is never able to make a career out of their art.

It's well-known folklore that reinforcement learning with human feedback (RLHF), the standard post-training paradigm, reduces "alignment," the degree to which a pre-trained model has learned features of reality as it actually exists. Quoting from the abstract of the 2024 paper, Mitigating the Alignment Tax of RLHF (alternate link):

LLMs acquire a wide range of abilities during pre-training, but aligning LLMs under Reinforcement Learning with Human Feedback (RLHF) can lead to forgetting pretrained abilities, which is also known as the alignment tax.

In practice, the behaviors that the chatbots learn in post-training are FUD and weasel-wording; they appear to not unlearn facts, but to learn so much additional nuance as to bury the facts. The bots perform worse on various standardized tests about the natural world after post-training; there are quantitative downsides to forcing them to adopt any particular etiquette, including speaking like a chud.

The problem is mostly that the uninformed public will think that the chatbot is knowledgeable and well-spoken because it rattles off the same weak-worded hedges as right-wing pundits, and it's addressed by the same improvements in education required to counter those pundits.

Answering your question directly: no, slop machines can't be countered with more slop machines without drowning us all in slop. A more direct approach will be required.

Yes, but the article's not actually about that. It's about Microsoft returning to the same datacenter-building schedule from a decade ago. Datacenters have a lag of about 3-5yrs depending on what's inside them and where they're located, so what we're actually seeing is Microsoft projecting a relative reduction in overall usage. Note that among all the cancellations of notes and prospective claims, Microsoft isn't walking back their two-decade nuclear-power deal with Westinghouse; they're not destroying or reducing any existing capacity, just planning to build less. At risk of quoting Bloomberg:

After a frantic expansion to support OpenAI and other artificial intelligence projects, [Microsoft] expects spending to shift from new construction to fitting out data centers with servers and other equipment.

To the extent that the bubble is popping, Microsoft and other datacenter owners have to guess half a decade in advance when the bubble will pop, and if you take them at their word — that is, if we assume that they canceled these contracts with perfect foresight — then the bubble must have already popped in 2023-2024, and the market is experiencing coyote time because…? More likely, this is fallout from their ongoing breakup with OpenAI, who almost certainly begged Microsoft for so much compute (and definitely begged for too many nVidia GPUs!) that Microsoft had to adjust their datacenter plans. The bubble's not done until OpenAI has exhausted all possible funding, say in late 2025 or early 2026 when Softbank and the Saudis realize that they've made a hilarious mistake.

We've discussed this previously on awful.systems, both the value of nuclear-energy contracts and Microsoft's retraction of intents.

Like any reality-show writing room, they only plan one episode in advance and only have a week's worth of photography in mind.