... that wetware has vulnerabilities too?

Or to put it another way: "Oops, I didn't mean to do that, sorry."

The use case I envisioned is experts who COULD do the work by hand use AI as a tool to be more efficient. This assumes they are expert-enough that will recognize if their AI of choice is giving a false-positive rate that makes their work harder, not easier. It also assumes that since they are being paid for their time (but perhaps only a pittance or not at all if they are students), they will be paid by their employers or funders as much for reviewing the AI's output as they are for the other parts of their research.

... the usual caveats apply: An expert human, or team of humans, needs to look at what the AI is suggesting, understand what it is suggesting, test it with the same or more rigor they would give to the same suggestion if a human had come up with it, and not "sign off" on it until they are satisfied that it is what they say it is.

It's the humans who are putting their professional reputation and, in some cases, their professional licenses on the line if they get it wrong. The AI is incapable of caring if it's correct or not.

You are young. I remember the older days when you had to set up an external modem to connect to a university mainframe that MIGHT have internet. With no pictures.

No ftp or telnet from your actual home computer. If you wanted to download files, kermit, xmodem, and the mainframe's equivalent of 'cat' were your friend.

An AI that can parse my query and give me a useful result faster than me reading through several pages of documentation is a good thing. But this means the AI and its training data have to be suited for the task. There also needs to be two "escape hatches" - one to give me the pre-AI way of doing things and another that will get me to a human being, at least during business hours.

As for how Google runs its support pages, I don't have enough experience to comment. If the existing documentation is poor, I wouldn't expect better from an AI.

In the long term - 5+ years down the road - big projects like these will want on-site or near-site power or at least on-site battery storage so they can buy power when it's the cheapest.

On-site power should also be attractive to investors: If the data center flops, you still have a power plant that can sell power back to the grid.

--

By the mid-'30s, on-site base-load power may mean small nuclear plants. There are logistical, regulatory, and political/NIMBY reasons why that's not a good solution for the 2020s.

How much of this data needed to be "live" and how much of it should've been in "near-line" storage or in offline storage to reduce the risk of bulk-exfiltration?

If selling becomes economically less viable than leasing or renting or a library-subscription, then selling will no longer be offered by vendors.

you will not.

OS/2 Warp 3.0 could technically run in I think 4MB, yes MB. "Run" being a euphemism for "boot and get to a desktop in less than 72 hours."

... so their advertisements play smoother.

The Thing?

True digital sovereignty means having the resources in-country to manage your digital infrastructure. That means having the source and the skill-set to maintain it.

Not even the United States has that, not completely anyway.

But, like hand grenades and horseshoes, close actually counts.

>It's cheap and easy to audit OSS for malicious code with AI these days.

Economically feasible, perhaps. Cheap and easy? Perhaps for a sufficiently loose definition of "cheap and easy" but not by my dictionary.

If the AI model is trained on public-domain material or "commodity" material that doesn't contain real creative content along with creative content developed in-house or with the blessing/license from the creator/owner, that's fine.

But if it's importing creative and unique content from elsewhere without permission, that's a lawsuit waiting to happen. Probably lots of lawsuits.

Plus, a significant fraction of the game-buying public is looking to support creators financially, rather than just "buying a game."