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!
Just wait until you see how much they waste on unused life insurance!
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.
Indeed.
350 jobs is a drop in the bucket of the terrible hiring and firing decisions that companies make all the time.
This one just had an AI spin to it, so it gets repeated and reposted ad infinitum.
It's not just about current LLMs, though. LLMs are being made to work 24/7 on the next generation of models (and not just LLMs), which may be quite novel or just more effective. The next generation might be the one to worry about... Or the generation after that.
LLMs can be used like an army of monkeys with typewriters, with evals guaranteeing progress. It's inefficient, but effective.
Assuming it is possible to make progress (and I think it is), the logical conclusion is that progress will be made, and AGI and ASI will come
it gets integrated into automated killchains including a nuclear arsenal, and i hope noone is stupid enough to
Have you ever met a human? 🤣
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.