Well, yeah. It’s sometimes referred to as ‘tact’.

“Ahaha. Yeah…”

Wow, framing the debate much?

Totally nailed it!

Nice! Good job, Mozilla!

Well, yes. But it’s hard to imagine being more efficient with space or energy consumption than that. Single Cell (Organic) Protein production from yeast (or fungus) isn’t a sci-fi concept taken from Cyberpunk. Cyberpunk took it from the real world. The general process has been known since 1781, although research into its use as animal feed was only kicked off by Max Delbrück much later. It was used by Germany during WWI to counteract food shortages, and later by many others, notably the Soviet Union for the same purpose.

Maybe shouldn’t have listened to BP’s “great” idea of using paraffin refined from oil as the feedstock though. Turns out - surprise! - that the residual alkanes are more than a little unhealthy.

For more information: https://en.wikipedia.org/wiki/Single-cell_protein#History

Frankly, this is the first time I’ve ever heard of yeast oil, although I’m certainly glad that a more ecologically sound (and likely healthier) alternative to palm oil exists.

Not that I was eating anything with palm oil in it as it is, but I’ll be happy to try this ever I ever see it around.

It really doesn’t. I highly doubt there isn’t office politics going on inside Microsoft, Apple and Google, but unlike them, Linux development is all public. If anything, that’s likely to curtail a lot of bad behavior rather than encourage it.

Ah yes, the printing press: Likely the most cumulatively subversive memetic infection vector ever conceived.

Here I’m imprecisely using “LLM” as a general stand-in for “machine learning”. The only role I see for LLMs in that kind of endeavor is to allow researchers to ask natural questions about the dataset and get results. But with that correction made, yes, even simple polynomial partitioning of hyper-dimensional datasets is incredibly good at detecting clustering/corelations/patterns no human would ever be able to perceive, and is helpful in other ways - predicting (i.e. guessing) at properties for hitherto unknown compounds or alloys based on known properties of existing ones, which has been very helpful in everything from chemistry over material sciences to plasma physics. Point is, there’s plenty of useful and constructive uses for these technologies, but those are not the ones actually being funded. What investors are throwing money at is either tools that rip off other people’s work without compensation, enable positive (in the bad cybernetic sense) feedback loops with users or aim to replace large amounts of the workforce with nothing to replace the jobs lost, which will obviously do nothing good for societal or economic stability.

Define ‘mind-control’. Trans-cranial magnetic stimulation has been perfectly capable of changing people’s broad moods since 1985 and is being actively used to treat depression right now. The underlying technology is only going to get more precise, especially as more research on spintronics is done for other purposes. Sure, right now our understanding of how what goes on in a given brain translates to ‘thoughts’ is insufficient to change those thoughts in any reliable way, but there’s little doubt that when we do, the technology to make it happen will almost certainly be around.

Yeah. While I agree that “Europe isn’t the US” and that we definitely need “smarter AI rules”, I highly doubt my idea of what that means matches that of those corporate entities.

By all means, use a LLM to chew through huge scientific datasets to search for correlations a human would never have noticed or come up with a 400 page mathematical “proof” that can at least inform a human-driven refinement process to achieve actual understanding, but practically ever other use of “AI” I’ve seen so far is a blursed waste of power at best and societally corrosive at worst.