When you have multiple selections you can show that the probability of selecting a set with a range much smaller than the population range is exponentially unlikely, strong evidence to reject the hypothesis that the subset was chosen at random. But when N=1 you can't conclude anything.
It sounds like you are trying to back-construct the reality you want, that low electricity prices lead to higher fleet efficiency, but that's flawed. You should look at the reality on the ground. Washington actually has double the rate of pick-up trucks compared to California, higher than the national average.
Yeah something about this whole concept is way, way off. The energy, and therefore cost, of an LLM analyzing every data point of every time series is many orders of magnitude too high, unless your operations are trivial.
High gas prices do persuade people. Look at the vehicle fleet in California compared to the other states. It is very different and the gas is only slightly more expensive.
Clearly the platform isn't designed to do this. Nobody thought this was going to be a necessary facility. They have just crammed an array of numbers as literal values deep into the standard library. So clearly this is an exceptional event, and not the exercise of a feature that was foreseen.
That isn't even a very good rule. Look at the NREL panel aging data. Some of their panels are aging in reverse, producing more power after a accelerated aging treatment and years in the field.
Brainwashed fission bros double-count reactor builds every year they are under construction. In terms of completed stations, China is opening 1 new reactor (~2GW) and hundreds of new PV stations (~300GW) per year. Over 99% of it is solar and nuclear is a sideshow.
We absolutely have solved cheap battery storage. 100% solved. It is crazy to make this statement when we are discussing nuclear thermal power, which requires multiple 20-million-dollar steam turbines for every station. You should have said "We still haven't solved cheap superalloy fan blades".
Explain the mechanism by which you believe photovoltaic panels start failing.
Your concern would be valid for a nuclear thermal power station, a Goldberg machine with millions of moving parts. It is not really applicable to semiconductors.
I feel like "didn't scale well" is unfair to Perforce. It scaled to accommodate an absurd monorepo that might have been, at the moment they switched to Piper, the largest single software project in history. It scaled to handle the needs of every organization in the industry except Google and Microsoft.
Right. I can guarantee that there are tens of thousands of listening devices with embedded radios in the OpenAI office, right now. The only open question is who controls them.
You're referencing a 5-figure rig like the ADRV9040 I suppose? I don't work in that industry but I do dabble in SDR hobbies and I guess due to my advancing age I view this as linear progress rather than breakthroughs. Two decades ago it was $1 million worth of junk.