Joe

“My agent hacked hugging face” is almost certainly not a civil legal defence in the US, and I wonder why so many people seem to suggest that it is/was (willful ignorance, is my suspicion).

My bet is that OpenAI offered to compensate HF in one way or another (or already does) and an agreement was made.

OTOH a criminal case would likely be an uphill battle, unless criminal negligence could be established.

There are a lot of people with limited agency over their own work or personal lives, and are at the receiving end of other people’s decisions.

Resentment can build when they perceive outside forces impacting their lives and personal well-being negatively. Sometimes this comes to define them as a person, in a self-reinforcing spiral of doom.

For most well adjusted people in decent work and social circles, we can take a more nuanced view, being both critical and optimistic as needed, and finding satisfaction in making the world work for us.

Consider yourself privileged.

It’s really not that complicated.

They will answer the 911 call, you say this is just a test to ensure the functionality, thank them and then hang up.

Worst case you get some person who complains about the test call, and you calmly explain that you called their non-emergency number beforehand to ensure that it would be OK, thank them, and then hang up.

As for your VOIP location Q: If it has a registered address in another location, you should call that location’s local number. Normally you want the correct address registered though, but you could inform them of this directly, as they probably have a database with notes that pop-up based on the calling number.

Someone mentioned Fairphone here… which seems to have just that.

demonstrated any actual competency in this domain

It may be that he/they have significant competency in this domain, just not publically or under this name/pseudonym.

I’ve personally made contributions under pseudonyms just to avoid employer paperwork/approvals, for projects that I’d rather not have my real name attached to, and for sharing in potentially hostile communities.

I’ve also developed software internal to companies that has never been released publicly.

In short … he doesn’t need to prove his prior credentials to you, me, or anyone. He may have some, he may not.

We can legitimately critique what he/they have done in this project all we like though.

Linus seems to be taking a perfectly pragmatic approach, given that AI is not going away short of WW3.

I can imagine some individual sub-system maintainers introducing various AI-roadblocks though.

I also expect this to be increasingly addressed (in general) with model & tooling improvements, giving more weight to higher quality reports and MRs, and more respect for project rules and processes. A mix of soft and hard gates, CLAs, improved early automated bug report & patch reviews and other CI gates.

We should use it to replace all those 0-token near-free existing automations, because it’s the future. We just need to connect personal agents to MCPs using admin credentials (or even an admin token vending machine MCP, since LLMs know all the cloud and enterprise APIs already)

AI dividends paying out in 3…2…TABLE NOT FOUND

AI hype and uncertainty is definitely influencing decision making, that’s for sure. If your company doesn’t have strong integrated product and architectural leadership, then managers across the company are probably grasping at straws, hoping to find some meaningful goals and ideas that stick. And lazy leaders, who traditionally rely on Gartner and similar feeds for trends and investment direction, probably think anything AI related is a safer bet than … well, anything else their underlings are proposing.

Hence the need to wrap sound decisions in a layer of AI. It’s BS, and many know it’s BS, but it seems necessary just now.

gwbasic on an XT here. Automate yourself out of that particular job. If not you, someone else probably will, or some expensive outside consultant will identify it for the chopping block. Find something of more value to do within the company, and slap an AI label on it for good measure. You are in the trenches now and you see the dysfunction… It’s likely the same company-wide, so rife with opportunity.

But higher satisfaction from those calling 911 for cookie recipes!

I read the other replies. I was purposefully giving you an alternative, rather than repeating what others said. How you choose to receive it is up to you. Good luck, I guess.

Hate to be “that guy”, but you can probably make the FOSS alternative work for you. Create a feature/bug issue on the project(s) explaining the problem in detail. It might be easy to fix.

You can also try to fix it yourself, or ask a programmer friend to help. Friends often like helping friends.

For a smaller investment (eg. one month of ChatGPT Plus for Codex, Kimi, whatever) and you can probably fix all the niggly things that you don’t like yourself. Just don’t go opening pull requests for code changes you don’t understand - it won’t be appreciated.

Some home internet routers (e.g… from FritzBox) support multiple VOIP providers, letting you configure rules as to which provider is used for outgoing calls (e.g… default for local calls, and another for international calls). And they provide a normal phone connector.

Just wait until you see how much they waste on unused life insurance!

Remember KillerFS? Oakland PD remembers!

Economies of scale… And you said instance, which is AWS terminology… If you have the scale and the expertise to run a DC efficiently, expect significant savings. We pay a premium for opex over capex.

If you assume they are unprofitable, the Q only becomes whether they are more or less unprofitable by serving the older models for longer.

My caveats were clearly stated… After capital expenditure, it’s just operational costs, where electricity & cooling are the big ones.

At that point, it is insanely profitable to serve. The cheap API prices on open weights models hints at the profit margins involved in the US (the frontier labs and hyperscalers don’t open their books for us), unsurprisingly)

Therefore, the longer they can serve existing and lower cost models at the current rates, the better for their bottom line. It’s just common sense in business.

It doesn’t mean the company as a whole is profitable. I expect we’ll see turmoil in the coming months and years, and the prize will be compute capacity, with electricity & cooling options.

There is also a commercial aspect…

Bigger models are more expensive to train and serve…

Inference is currently insanely profitable if you have the hardware and the automation in place to support and serve it. At that point, it’s a money printing machine, and you want to squeeze as much out of it as you can.

While training new models is extremely expensive, and serving them probably makes less profit (at least initially).

Having an external brake applied to the frontier labs is likely good for their bottom line, while increasing hype and directing customers’ annoyance away from them.

It’s likely only a temporary benefit, though. The dragon will catch up and apply more pressure, both on inference price and capabilities.

I would also do #1, and I’d probably make it work (loooong time Linux user and persistent debugger).

#2 is probably simpler, both conceptually and technically. NAT and FW config is self-contained, and there are plenty of docs and how-tos.

Note: I’m not a proxmox user, so there could be some proxmox specific spanners… But I doubt it.