ignirtoq

Amazon is using their own hosting. AWS stands for Amazon Web Services. Or did I miss the joke?

I would love to see the werewolf play the pompous know-it-all: “Um, actually the idea that the moon causes the change is a superstition. It’s a body cycle that often coincidentally matches up with the full moon. People just remember the times during the full moon because of confirmation bias.”

Handmade arepa with a layer of goat cheese and topped with scrambled eggs with sausage.

It depends on your definition of “can”. Are his actions allowed by law? No. Will anyone stop Trump from doing them anyway? Probably not.

I also want to make clear, these aren’t “Democrat agencies.” There aren’t formally “Democrat” and “Republican” agencies in the federal government. National political parties are formally private organizations, and local political parties are affiliated with national parties with various levels of control able to be exerted on the local parties by the national parties depending on the specific organizations involved and their relationships. It’s all complicated, but the salient point is it’s all non-governmental. The agencies Trump is cutting funding from are governmental agencies that generally have greater approval/support from segments of the voting populace that generally lean more Democrat in their voting behavior. There are Democrats that don’t support these agencies, and there are Republicans that do. There are also likely people in both parties that support the general cause of the agencies but would prefer they would be run differently or have different policies or regulations. Again, in reality it’s complicated and nuanced.

Calling them “Democrat agencies” is Trump applying tribalistic language in his usual divisive way to drum up support from his base. The voting populations that broadly support these agencies generally lean Democrat, but that’s not catchy and won’t get people angry and vocally in support of Trump. So he calls them “Democrat agencies” to paint a picture that, despite the Republicans having control of literally all branches of the federal government, Democrats directly control these federal agencies (which is not true), and that therefore they are acting against the will of the public, who he represents by definition (which is also not true), and therefore they should be shutdown. It’s right out of the fascist playbook, and when the media even just quotes his language, they enable him to define the language of the discussion of his actions, and thus they further help Trump shape the narrative of the shutdown.

Nothing in the shutdown gives him the power to do these things. He was in fact doing all of these things before the shutdown, and he had no legal authority to do any of it then either. He’s able to do it because his regime is authoritarian and does whatever they want, and organizations that stand to benefit from this authoritarian regime have spent the last 50+ years systematically subverting the checks and balances that were built into the federal government to prevent this kind of authoritarianism. Complicit politicians in the legislative branch prevent impeachment and removal from office of anyone in the regime that breaks the law, and complicit Supreme Court judges prevent the judicial branch from delivering injunctions or other judicial relief or safeguards from these actions. There are coordinated (even if it’s just stochastic coordination) bad faith actors at all levels of power in all branches and offices of the US government. It didn’t happen over night, it in fact took decades, but no one stopped it, so here we are.

From the legal definition of “can”, Trump in fact cannot do most of what he’s doing. But in America laws don’t matter anymore, so in practical terms he can do literally anything now.

As far as I’ve ever been paying attention, conservatives only argue in bad faith. It’s always been about elevating their own speech and suppressing speech that counters theirs. They just couch it in terms that sound vaguely reasonable or logical in the moment if you don’t know their history and don’t think about it more deeply than very surface-level.

Before, platforms were suppressing their speech, so they were promoters of free speech. Now platforms are not suppressing speech counter to them, so it’s all about content moderation to protect the children, or whatever. But their policies always belie their true motive: they never implement what research shows supports their claimed position of the moment. They always create policies that hurt their out-groups and may sometimes help their in-groups (helping people is optional).

My understanding of why digital computers rose to dominance was not any superiority in capability but basically just error tolerance. When the intended values can only be “on” or “off,” your circuit can be really poor due to age, wear, or other factors, but if it’s within 40% of the expected “on” or “off” state, it will function basically the same as perfect. Analog computers don’t have anywhere near tolerances like that, which makes them more fragile, expensive, and harder to scale production.

I’m really curious if the researchers address any of those considerations.

Vibe coding anything more complicated than the most trivial example toy app creates a mountain of security vulnerabilities. Every company that fires human software developers and actually deploys applications entirely written by AI will have their systems hacked immediately. They will either close up shop, hire more software security experts than the number of developers they fired just to keep up with the garbage AI-generated code, or try to hire all of the software developers back.

Several years ago I created a Slack bot that ran something like Jupyter notebook in a container, and it would execute Python code that you sent to it and respond with the results. It worked in channels you invited it to as well as private messages, and if you edited your message with your code, it would edit its response to always match the latest input. It was a fun exercise to learn the Slack API, as well as create something non-trivial and marginally useful in that Slack environment. I knew the horrible security implications of such a bot, even with the Python environment containerized, and never considered opening it up outside of my own personal use.

Looks like the AI companies have decided that exact architecture is perfectly safe and secure as long as you obfuscate the input pathway by having to go through a chat-bot. Brilliant.

At least it was better than Indiana Jones and the Kingdom of the Crystal Skull.

The thing is it’s been like that forever. Good products made by small- to medium-sized businesses have always attracted buyouts where the new owner basically converts the good reputation of the original into money through cutting corners, laying off critical workers, and other strategies that slowly (or quickly) make the product worse. Eventually the formerly good product gets bad enough there’s space in the market for an entrepreneur to introduce a new good product, and the cycle repeats.

I think what’s different now is, since this has gone on unabated for 70+ years, economic inequality means the people with good ideas for products can’t afford to become entrepreneurs anymore. The market openings are there, but the people that made everything so bad now have all the money. So the cycle is broken not by good products staying good, but by bad products having no replacements.

This is the ultimate Texan dog-that-caught-the-car moment. I remember talking about this in school in Texas 25 years ago when Republicans were complaining about immigration. Several students brought up that the farms are all tended by “seasonal workers,” which meant immigrant labor, so what was the Republican answer to that? They didn’t have one, of course, not a realistic one. It was the same talking points then as now of “American workers” filling the gap, and even then those jobs didn’t pay a living wage, so no American would take them. I bet they pay worse now.

They had 25 years to figure this out, but of course they had no intention of figuring it out.

They keep tasking these LLMs with things that traditional programming solved a long time ago. There are already vending machines run by computers. They work just fine without AI.

Honestly the computer controlled vending machines are already over-engineered since many of them play ads when you walk up. The last customer-focused feature added was credit card support, and that just needs a credit card reader and a minimal IoT integration. They really shouldn’t even have screens.

Why are they… why are they having autocomplete recommend medical treatment? There are specialized AI algorithms that already exist for that purpose that do it far better (though still not well enough to even assist real doctors, much less replace them).

Even more surprising: the droplets didn’t evaporate quickly, as thermodynamics would predict.

“According to the curvature and size of the droplets, they should have been evaporating,” says Patel. “But they were not; they remained stable for extended periods.”

With a material that could potentially defy the laws of physics on their hands, Lee and Patel sent their design off to a collaborator to see if their results were replicable.

I really don’t like the repeated use of the phrase “defy the laws of physics.” That’s an extraordinary claim, and it needs extraordinary proof, and the researchers already propose a mechanism by which the droplets remained stable under existing physical laws, namely that they were getting replenished from the nanopores inside the material as fast as evaporation was pulling water out of the droplets.

I recognize the researchers themselves aren’t using the phrase, it’s the Penn press release organization trying to further drum up interest in the research. But it’s a bad framing. You can make it sound interesting without resorting to clickbait techniques like “did our awesome engineers just break the laws of physics??” Hell, the research is interesting enough on its own; passive water collection from the air is revolutionary! No need for editorializing!

The use of “quantum leap” isn’t about comparing the absolute size of the change to quantum phenomena. It’s about the lack of a smooth transition. Quantum leaps in physics are instantaneous transitions between states with no intermediate. That’s the idea with the colloquialism: a sudden shift from one state to another without a smooth transitional period.

What’s the y-axis, and how exactly are you measuring it? Anybody can draw an exponential curve of nothing specific.

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People are making fun of the waffling and the apparent indecision and are missing the point. Trump isn’t flailing and trying to figure out how to actually make things work. He’s doing exactly what he intended: he’s holding the US economy for ransom and building a power base among the billionaires.

He used the poor and ignorant to get control of the public institutions, and now he’s using that power to get control over the private institutions (for-profit companies). He’s building a carbon copy of Russia with himself in the role of Putin. He’s almost there, and it’s taken him 2 months to do it.

The author hits on exactly what’s happening with the comparison to carcinisation: crustacean evolution converges to a crab like form because that’s the optimization for the environmental stresses.

As tiramichu said in their comment, digital platforms are converging to the same form because they’re optimizing for the same metric. But the reason they’re all optimizing that metric is because their monetization is advertising.

In the golden days of digital platforms, i.e. the 2010s, everything was venture capital funded. A quality product was the first goal, and monetization would come “eventually.” All of the platforms operated this way. Advertising was discussed as one potential monetization, but others were on the table, too, like the “freemium” model that seemed to work well for Google: provide a basic tier for free that was great in its own right, and then have premium features that power users had to pay for. No one had detailed data for what worked and what didn’t, and how well each model works for a given market, because everything was so new. There were a few one-off success stories, many wild failures from the dotcom crash, but no clear paths to reliable, successful revenue streams.

Lots of products now do operate with the freemium model, but more and more platforms had moved and are still moving to advertising ultimately because of the venture capital firms that initially funded them have strong control over them and have more long term interest in money than a good product. The data is now out there that the advertising model makes so, so much more money than a freemium model ever could in basically any market. So VCs want advertising, so everything is TikTok.

The open availability of cutting-edge models creates a multiplier effect, enabling startups, researchers, and developers to build upon sophisticated AI technology without massive capital expenditure. This has accelerated China’s AI capabilities at a pace that has shocked Western observers.

Didn’t a Google engineer put out a white paper about this around the time Facebook’s original LLM weights leaked? They compared the rate of development of corporate AI groups to the open source community and found there was no possible way the corporate model could keep up if there were even a small investment in the open development model. The open source community was solving in weeks open problems the big companies couldn’t solve in years. I guess China was paying attention.