Advisors should be *advising*, not just being yes men to a megalomaniac.

The whole point is for the president to surround himself with experts and take their expertise into account, not to just have people to echo whatever he says.

Your stated experience and guess has to be weighed against Trump's usual motives.

Occam's razor would suggest it's like everything else he has done his entire life: it's about self enrichment and ego.

The ship has sailed though. So many work vehicles don't have rear windows anyway.

On the side mirrors, the thing I'd really like is some sort of gaze tracking to adjust the cameras. That's the biggest thing I'd see missing in a camera system, where it would probably be fixed positioned.

So I suppose the real point they want to make is that human consideration with GenAI input is better than GenAI alone, but there's some issues with the first bit about comparing 'pure human' to 'pure AI'.

The first sign is they are using Polymarket as a benchmark and distinct from "human prediction", but Polymarket is just comprised of human prediction. Polymarket is comprised of humans mostly, just a tendency to be humans that are more specifically informed about the topic they are betting on.

So we see "The human groups performed poorly, relying on instinct or whatever information had come across their feeds that morning", this suggests the humans were asked cold about random events they had not researched and further were not allowed to research, so all they had to go on was guessing on whatever they had happened to hear about beforehand. If you asked me who was going to win the presidential election in a country I've never heard of and demanded I don't look, well of course my answer is going to be garbage. You could include a totally made up name as a choice and I might pick that one because I just have no way of knowing.

I would have been much more interested if they were given a minute to do a quick internet search with AI results disabled to see how well they did versus GenAI results to see if the GenAI results improved their accuracy versus a quick internet search.

When the datacenter is kind of embedded in a larger business, or it's a business that has poor resiliency, then there's a reasonable amount of jobs.

Those are a dying breed, and the vast majority of things being discussed are isolated facilities with skeleton crews. You have a few months of construction type jobs, but the persistent job picture is pretty light compared to the impact on the local area.

Well the 'nice' thing about this sort of language is it can frequently be true multiple times. It's "better" but how close to "good enough" is unspecified.

The Anthropic one was interesting because the original person behind it was fairly nuanced and honest. The stunt needed an existing reference implementation as a basis as well as a boat load of unit tests and needed hand holding and still didn't quite pass the big test of compiling the kernel (needed to borrow missing bits that claude couldn't figure out). Then as many noted the compiler kind of sucked, compiled code that should have errorred, failed to compile code that should have. It was interesting that it could keep iterating, but the end game in the heavily tilted game remained elusive. The original post was pretty honest about this. Then an executive says "this says software development is already dead!" when the experiment was pretty much exactly the opposite, that even with the most capable LLM available, it needed a *lot* of human development aid to get to end game, even as it was given something that already worked to knock off *and* had certainly trained on multiple C compiler codebases.

Yes, but before, they wouldn't get greenlit and projects with a vague chance of progression would.

Now they precluded quite a few projects that actually could have progressed.

I tried to extract specifics to expose the ill conceived ones, but the other executives on the panel were still a fan of the slop ones, and preferred them over more grounded.

To make that, first we need a court to actually rule that 'training' can count that way. Currently everyone is operating under the philosophy that ingest to an LLM "doesn't count" somehow.

Well, no, that assumes exactly one implementation for a given feature in the wild.

Imagine generating a random string. Hundreds of codebases will have that same function. So this process may pull that from any of those codebases and not necessarily from the source codebase.

It's never generating fundamentally novel code, but it is drawing from a huge training data that includes the same thing done dozens or hundreds of times with technically distinct code.

IBM BIOS wasn't source available either. The precedent for 'clean room' involved reverse engineering binary code.

So while the current story emphasizes the loss of open source protections, the same principles would apply to LLM transforming binary and test cases to a specification.

But it's meant as a proof point of our current interpretation of LLM and copyright. So far this "counts" as clean room because courts have not said LLM ingest is a violation, and they are using the LLM to launder the code to an intermediate form and then to code based on the 'clean room' finding.

So while you are right in a sense, the point is from a court perspective this is "equivalent" to clean room unless new laws/court cases amend the status quo.

Anecdote to back this up, we have annual round of employee directed projects where people propose something they will do that no one asked for in hopes that they do something unexpected that's worthwhile. Generally it's a waste of time business wise, but at least people get to work on something they actually believe in.

Anyway, usually they at least usually manage to create a somewhat working demo of their concept, but this year most of them failed to do so, because most of the pitches were people that didn't know how to do the work, but GenAI was able to generate pitch material that convinced executives to approve them and largely drowned out the people with actionable proposals. So most of the final presentations were people just repeating their pitch and hoping people didn't notice they had no new material since their pitch a few months back.

Quite frankly a huge amount of skepticism is absolutely warranted. The AI tech companies are broadly worrisome, but Palantir takes the cake for outright villainous efforts.

To the extent they have shown ambition for a future, they haven't shown they have a whiff of folk's best interests at heart.

Nope...

Note the intent to "retrain" labor.

The AI dividend in their scenarios wawould be a trivial gimmick. They still want the labor force toiling, but a dividend to mollify concerns about AI displacement.

If this happened, I would bet maybe 100 or 200 dollars a month of "dividend". You'd still be expect to toil away under the capitalist rules to actually have a credible living.

In terms of what to change to doing, some of these folks already said that people need to return to manual labor. They really hope AI will work as a strategy to make educational an impractical choice and people just kind of stay uneducated and desperate to provide manual labor for sustenance.

This is a path for them to patch what they see as a problem in capitalism: some modicum of class mobility. Other than that possibility, capitalism works great for them. For communism as a core principle, then they need to go full authoritarian, and the power struggle among them to get there is a more dangerous one than a modified capitalism.