I'd argue that while you might be gaining something here (time) you could also losing something and that is expertise.

If you aren't reading the documentation yourself, then you aren't absorbing things that could be valuable later (even though they might not be relevant to the particular task you are doing now) and are therefore "stupider" at least by that definition.

All the time I'm involved in conversations where it is useful to have information in my head to either
- immediately answer a question (and avoid a follow up meeting), or
- prevent time being wasted on some course of action that isn't viable, or
- to suggest a neat solution I am aware of
all because of some detail I have read that hasn't previously mattered.

Of course, perhaps you are reading the documentation first, then pointing the AI at the relevant bits so it can complete some task and then reviewing the output for sanity, in which case I think you probably aren't losing out.

In the real world though I am seeing more and more information coming my way where it is pretty obvious that the person presenting it hasn't actually done their homework and doesn't really understand what they are proposing or working with.

You're less than a couple of years away from being in a Russian oligarchy.

You're optimistic, I was thinking more like North Korea....

I have probably read something they published in the last decade, but I just looked at their website

I do love posts that just start off, "I, an ignoramus, think...."

I don't mind articles mentioning AI when it's relevant but using that generic term over and over again without mentioning which specific tool just smacks of a writer more interested in hitting buzzwords than conveying information.

From the article published in Cell it seems to be Alphafold and the structure it reveals seems vital to being able understand how PHGDH could be interacting biologically and therefore be a critical part of the discovery, so a shame the uscd.edu article doesn't mention it by name.

Long term, they will pay the 500% tariff because this tariff level is not enough to induce American manufacturers to compete with the Chinese on low margin products.

I am not sure that is quite true, there will definitely be a threshold where it would become more than viable for American manufacturers to compete.

However, the investment involved is only going to be made in an environment where there is some predictability. If anyone believed that the tariffs would stay at that high level for years then they might invest, but no one in their right mind would believe these tariffs will stay the same next week, let alone past the end of the Trump presidency.

Did you actually see the chart of tariffs that every other country had in place before any of this started.

Would you like to buy a bridge?

amid efforts by the Trump administration to grant Moscow concessions to end the war in Ukraine

Even Trump isn't such a bad negotiator that he'd be handing over the concessions before the deal is made.
Clearly the West Wing's full title is now the "West Wing of the Kremlin"?

Was that post written by AI?

I am glad I was here for the good old days, when computers were at least supposed to do something a certain way and if they didn't it was a bug someone could permanently fix.

In the brave new world when they make a mistake it's now everyone else's job to just deal with it....

Wait till they find out he has parents who like suing educational institutions!

I have to wonder how much of the negativity towards the game comes from people who's motivations are tangential to the games actual quality. Reviews seem reasonable and people who played the beta seemed to indicate that the game did a few interesting/unique things compared to others in the genre, but the game was suffering massive negativity well before anyone got their hands on the game.

I think it's a big extra risk for multiplayer games (particularly co-op games).

With single player games if a certain group of people react negatively to a game for non-gameplay reasons it doesn't really matter too much, people who do like it can just play it regardless. With multiplayer games buy-in from other people is vital for a game to be good for you, both generally and from your cohort if you play in a friends group.

Personally I think Sony are kinda bonkers to even try to go into this space in such a big way, but perhaps the potential upside is enough to justify the risk, even if it didn't work this time.

It basically updates your code to work to be compatible with most recent major versions of libraries/frameworks and uplifts some deprecated functions usage. IIRC it is leveraging Openrewrite underneath.

We have used it to upgrade some old code with a bunch of dependencies as as a trial and It did a good job, but mostly in the sense of doing something dull and uninventive quickly and well. Doing in an hour or so what would have probably taken a few days of boring iterative work for a developer otherwise.

HPV and Hep B are known to cause cancers and can be prevented by vaccine.
There is some limited evidence that HPV may be involved in some brain tumors.
Several other viruses that are suspected to cause brain cancer which a vaccine could help prevent.

Just let the model interact with the world and other models and us.

This seems to miss the point. The problem is models interacting with each other without a strong evaluator for quality once models are generating more content than humans.

We are used to language changing at human scales, we have just enough rizz to more or less keep up with whatever skibidi things the kids are inventing these days.

But what happens when LLMs are generating and consuming orders of magnitude more information with each other? The signal for "quality" as a human would perceive it is drowned out.

What? AlphaZero, it learned Go, chess and shogi from scratch to superhuman level. It was not feeding on its own data, but rather acting on the board against an opponent.

It was very much feeding on it's own data (playing versions of itself) to improve.

That is a very different sort of problem though. Chess and Go have clear rules and win conditions so even when it's playing itself it has a strong external evaluation mechanism. That sort of problem probably stretches to things like protein folding (the feedback loop is slower, but absolute correctness and distance from it can be evaluated).

But LLMs face a much different hurdle as absolute correctness cannot be easily evaluated. (It may be easy to identify a solid subset of "awful" fairly easily, but pushing the quality mark to "better" is a much more difficult assessment).

The rush to deploy LLMs risks the enshittification of the training data set faster than improvements can be made to the models, potentially getting to the point where an LLM may perform excellently on pre 2023 knowledge but anything new post 2024 will be hopelessly messy because the source data is fucked. Ironically, in the long term it is the AI companies who might benefit from a "created by LLM" watermark on any generated output, but that is obviously a pipe dream.

I expect LLMs will continue to improve in terms of things like efficiency, speed, cost and cross-media capability, but it's far harder to be optimistic that we are going to see big steps forward in quality.