subject4056

Yeah. IME if things aren't working the way the docs say they're supposed to (i.e. when you need support) the agent is just totally useless. Sales too, if the happy path doesn't work you're not buying a plan from them. My suspicion is that they don't care if 0.5% of people ditch them because they're approximately the only game in town, and it's not worth their time to task a person with this.

You know I took the wrong conclusions from frog/rat developmental studies in space. As far as I can tell low gravity isn't known to be a killer, just that the whole process hasn't been studied (no mammal recorded to give birth in space).

As to whether or not that makes Mars hard, I think it doesn't matter how well you can control the climate if you can't have a second generation of people to live there.

Mars doesn't make a ton of sense as a backup earth because gravity there is too weak to carry a fetus to term. If we had the tech and the urgency to terraform mars, it would probably make more sense to put those resources into space stations where we could control the environment better (and less risk from losing any one station). Mars in this scenario is sort of like an offshore oil rig that people work on for some months at a time and then go back to their life in space (again provided we can't live on earth for some reason).

I expect lots of humans to not be able to make you laugh on command, so no it's probably not a good test

Among other reasons, if you turn temperature down to 0, llms stop working. Like they don't give natural language answers to natural language questions any more, they just halt immediately. Temperature gives the model wiggle room to emit something plausible sounding rather than clam up when presented an input that wasn't verbatim in the training data (such as the system prompt).

I don't think so. Primarily because if you can ask that question instead of just being dead, then it's not the fast takeoff.

On a less drastic note, if AI were autonomously cannibalizing the economy, you'd run into more things and go "huh I guess that's run by AI now" instead of "ah godammit why did they shove an LLM in this workflow".

I don't think adding 20 bytes to every response, which are never read in practice, will improve the energy efficiency of the internet. Not to be mean, there's just a lot of stuff in most responses that effectively nothing acts on.

We're not it's competition in the same way chimpanzees aren't our competition. Some fraction of us are interested in their well-being for aesthetic reasons, but a lot of the time this fraction loses to a not particularly powerful faction in direct competition for territory. And if there is any serious conflict of interest, there is no contest and the chimps lose. If we get lucky some fraction of superintelligence will look on us the way we look at ground apes, but that's far from a given.

I don't think it's right that Airbnb solved short term rentals - outside of a few dozens prestige markets that they monitor with humans, it's really a race to the bottom. Reputation at scale remains unsolved, and so it's still a market for lemons.

You could get healthcare from someone who doesn't have to go $100ks in debt first, and then expects to make more than you do. If no such person with that profile exists, then yeah you're stuck paying the rate of the system that trained and employs them.

At the end of the day, much like housing cannot be both affordable and a good investment, healthcare cannot be both affordable and a lucrative career. Avoid going to an MD if you can get the same care from someone else.

Kanban operates on a known product with a known manufacturing process. Many software products are undefined even at time of public release, and evolve continuously. "Deciding what to build", while explicitly highlighted in the agile software manifesto, is the weak link.

Put another way, lean manufacturing improves metrics for the margianal unit of goods. No one, customer or dev, is interested in the margianal unit of software.

I would guess not. An important feature of compilers is that they are guaranteed to emit code with certain properties in response to specific inputs (memory safety guarantees, asymptotic performance, calling convention, etc.). If they don't do that, you can file a bug report.

You cannot file a bug report against an LLM that it produced an unexpected output, because there is no expected output; The core feature of an LLM is that neither you nor the LLM developer knows what it will output for a wide range of inputs. I think there are a wide range of applications for which LLMs core value proposition of "no-one knows a priori what this tool will emit" is disqualifying.

Audio and video are encoded, compressed, and transmitted differently because of how humans audially/visually decode them. We fare better dropping late video frames than degrading their quality, where the opposite is true for audio. As we transmit the two as separate, asynchronous signals, it's unsurprising that they are frequently out of sync.