But the VC path pushed them to increase costs more than they should. They didn’t need that money to deliver on the mandate of Deno, they had to inflate the vision to some grand cloud solution, which didn’t make much sense.

> then it is a failure as company

Perhaps it shouldn’t be a company at all. Private companies cannot attract the same support as open-source foundations do, since they are for-profit organizations.

In the space of such foundational technologies, there’s always been a vast gap between the number of private vs open-source projects that succeed. Even all the way back to proprietary compilers 40-50 years ago.

If they had stuck to being an open-source project, the kind of adoption and mindshare they achieved would have put them among the most successful ever. And I am sure they would have been able get their team paid very well sustainably. The unicorn model cannot fit every single venture.

That is an overstatement. Dutch is the primary language everywhere like the native language of any country. It is true that in major cities most people speak excellent English and you can definitely manage easily without speaking Dutch.

But Dutch is spoken absolutely everywhere and most signage is only in Dutch. Also, as soon as you get a bit outside of the big cities, you find many people with a middling level of English, similar to most other countries in Europe. Even in cities, many working class people and actually most immigrants from non English speaking countries only speak Dutch.

Of course that is terrible, but it is one of the worst examples you could have given to make your point.

The fact that we don't know why is a clue pointing at some area of math that we haven't discovered yet. The hope is always that it will uncover some hidden fertile valley that will lead to lots of new discoveries. But the proof of the conjecture itself, without understanding, is really not that valuable.

My point is that even if AI discovers many new truths, there's still plenty to do for the mathematical community, in dissecting it and building useful abstractions to understand it, abstractions that can be leveraged for further exploration and uncovering new questions.

What an intriguing thing to say :)

What are you referencing?

It may be true that regular agents trained for general purpose use do not behave this way, but they seem to be capable of learning such cheating behaviours when relentlessly being fine-tuned towards near-impossible objectives.

In this sense, it is not really fair to say that the agents found these solutions. It was the surrounding learning framework that achieved this, which is a much more powerful problem-solving mechanism. As users we do not have the capabilities or budgets to be able to tackle our own problems like that, we have to make due with the frozen behaviour the AI labs trained for us.

Individuals are unlikely to give up their control unless the alternative is clearly substantially better. And, as you say, there are other larger interests beyond individual preferences that need to be overcome too.

Regardless, as we have seen many times with other technologies, I think that convenience will be a much stronger driver of self-driving acceptance than the safety benefit.

People understandably prefer to keep control of their own safety, even if on average they are worse at it. Because individuals that do care about safety can actually do many things to lower the risks well below the statistics, and likely remain much better than self-driving.

There’s also the question of responsibility and liability. In society we have such pressures so that there’s an incentive to continually reduce risks. It is dangerous to shift the responsibility to fast-growth tech companies that will care much less about individual accidents than the drivers involved, and are more capable of absorbing liability without substantive remediation.

Safety is outsourced in many contexts (aviation, police, military…), but it has to be substantially better than what the individual can achieve on their own. For instance, due to the expertise required, or because you can achieve more through coordinated collective action. And there has to be very high trust in the companies involved, the regulatory systems around them, and the technologies employed.

> They're Made out of Meat

https://web.mit.edu/people/dpolicar/writing/prose/text/think...

For once it’s appropriately used.

If one attempts to have a single definition stretched over all the meanings, then you indeed get a definition that is way too broad that includes soups and sandwiches, which is ludicrous. But it's quite common for a single word to have multiple senses, let's just go with that.

- A wedge salad is right on the edge. It's a traditional salad except that the lettuce leaves are not separated. But if it was anything else in that form factor, like replacing the lettuce wedge with a potato, that's not a salad.

- A primarily cooked dish, particularly if it is cooked all together or is served warm, is definitely not a salad.

- An “untossed salad” is definitely not a salad.

- English speaking people add the term “salad” to a bunch of concoctions that are definitely not salads.

The time it takes to press a key is a reasonable target to aim at for API latency I suppose, but it is still an arbitrary target. Waiting to display until keyUp just adds more latency if your API is faster. Having it synced with keyUp doesn't make it feel more immediate to me.