Also consider that while the OP looks like a skilled, experienced individual, all too often the documentation is being written by someone with that context, but rather someone unskilled, and with read empathy. Quality is quite often very poor, to the point where as shitty as genai can be, it is still an improvement. Bad UX and writing outnumbers the good. The successes of big companies and the most well known government services are the exception.

The common thread is that people are bad and saving and delayed gratification. The easiest path to instant gratification wins more often than not.

Depends on the service, and timeframes. For geforcenow, you also need to consider the upgrade cycle - how often would you need to upgrade to play a newer game? I'm not sure but probably at least once within that 8 years. Buying a new car, or almost new car, and driving it until it falls apart is a better financial option than leasing. But if you want a new car every year or two, leasing is more affordable - for that scenario. Also it depends on usage. My brother in law probably plays a video game once every other month. At that point, on demand pricing (or borrowing for me) is much better than purchase or consistent subscription. You need to run the numbers.

Already happening at the in vitro level, might be possible in vivo as well. Neither require the more abusive approaches from the first eugenics era.

Honestly it feels like what I, or many of my colleagues would do if given the assignment. Take the current front page, or a summary of the top tropes or recurring topics, revise them for 1 or 2 steps of technical progress and call it a day. It isn't assignment to predict the future, it is an assignment to predict HN, which is a narrower thing.

Right, because you would read the teacher and realize they don't want you to actually complete the assignment to the letter. So you would do jokes in response to a request for prediction.

Is anything objectively amazing? Seems like an inherently subjective quality to evaluate.

Depends on worldview. If you believe in God, amazing has many dimensions for evaluations. What teaches us more about the the world He created, things that create beauty by expressing righteous thoughts for others to experience, or that which strengthens family.

LLMs certainly teach us far more about the nature of thought and language. Like all tools, it can also be used for evil or good, and serves as an amplification for human intent. Greater good, greater evil. The righteousness of each society will determine which prevails in their communities and polities.

If you're a secular materialist, agreed, nothing is objectively amazing.

The cycle repeats frequently in industry. New waves of startups address a problem with better UX, and maybe some other details like increased automated and speed using more modern architectures. But feature-creep eventually makes the UX cumbersome, the complexity makes it hard to migrate to new paradigms or at least doing so without a ton of baggage, so they in turn are displaced by new startups.

If the last part was true, Autodesk and Adobe would have had to go under a decade ago.

Right - the quality of your locks matter a lot less if your average 5-year-old tee-baller can through brick through the wind and climb in. One always needs to consider their threat model when considering what security to invest in getting.

Bang on. LPL himself uses a slightly modified Kwikset lock. The modification seizes the lock if someone tries to pick it. I'm the video, he says it isn't to stop all break-ins, but to stop non-destructive break-ins.

So a tamper-evident system not a (particularly) tamper-resistant one.

It is a focus, data, and benchmarking problem. If someone comes up with good benchmarks, which means having a good dataset, and gets some publicility around, they can attract the frontier labs attention to focus training and optimization effort on making the models better for that benchmark. This is how most the capabilities we have today have become useful. Maybe there is some emergent initial detection of utility, but the refinement comes from labs beating others on the benchmarks. So we need a slideshow benchmark and I think we'd see rapid improvement. LLMs are actually ok at a building html decks, not great, but ok. Enough so that if we there was some good objective criteria to tune things toward I think the last-mile kinks would get worked out (formats, object/text overlaps). the raw content is mainly a function of the core intelligence of model, so that wouldn't be impacted (if you get get it to build a good bullet-point markdown of you presentation today it would be just a good as a prezo, but maybe not as visually compelling as you like. Also this might need to be an agentic benchmark to allow for both text and image creation and other considerations like data sourcing. Which is why everyone doing this ends up building their own mini framework.

A ton of the reinforcement type training work really just aligning the vague commands a user would give to the same capability a model would produce with a much more flushed out prompt.

We've reach a point of price stabilization and longevity for smartphones now that didn't exist for the first 10 year ramp. When every new model added fundamental capability, you always want to upgrade, with the sweet spot often being every other year. But now, with better build quality, batteries, and stabilization of features people will keep their phones for much longer. Or buy "new" models that are of older versions since the price/features have been acceptable to run most of the apps they care about for years now. Plenty of people still want the top end for similar reasons to why people buy design clothing, but we've reached a feature plateau. We hopefully are getting close to that with EVs. Seems like around 300 mile range standard was the key thing. Though improved AI driving could change that again.

The main issue with smartphones is software support, as it essentially acts like a built-in time bomb.

Buying an older-generation flagship model to get better features than a current-generation midrange model of the same market price isn't very attractive when it'll have to be replaced after 2 years instead of 5 years.