Depending how you count, parent comment is accurate. Hardware doesn't just appear. 4 years of planning and R&D for the first generation chip is probably right.
I wonder if this also applies to people that live urban environments that don't drive and have to navigate walking or using the subway.
From my anecdotal evidence, it does seem that the average elderly person in NYC is way more active and social than an elderly person in the suburbs. But of course, it could be that people that live in cities self-select.
There is a lot of snark here. My non-cynical take is that they are aping the practices of top AI labs. OpenAI, Google DeepMind, Anthropic, and many other AI startup darlings have a culture of in-office work. People in non-hub offices are encouraged to travel a lot.
Yes, it will take a lot more than RTO to create an innovative culture like paying more for one, but one can reasonably hypothesize that working physically together is a necessary but not sufficient condition.
Yes, but the ability to identify prodigies and give them the resources to realize their full potential is part of an education system, too. I don't know the full details of the IMO participants, but the team is geographically diverse.
Of course, another aspect of the education system are the resources given to the average student, and I don't think there is much debate that the US could do better here.
At the very top, the US excels at math. We consistently place at the top or near the top in the IMO for instance (https://maa.org/news/usa-first-at-imo/). Yes the team is largely children of immigrants, but they are Americans, too.
As an American with Southeast Asian immigrant parents, they will live in a way that most Americans would find intolerable. Whole families in a 1 bedroom, very long commutes, taking buses, and living apart from their children (CPS, I know).
To be clear, I did not grow up like this, but I know many that did.
This is just (neurotypical?) human programming to be considerate of others. The driver feels this, too. I'd assume that the CEO of Uber Dara can manage his emotions and boundaries, well. But he mentions
> Some experiences made him feel slighted, such as when riders discussed personal problems and company secrets on speakerphone, as if there was no one else present.
The blog post (https://ai.meta.com/blog/segment-anything-2/) mentions tracking as a use case. Similar objects is known to be challenging and they mention it in the Limitations section. In that video, I only used one frame, but in some other tests even when I prompted in several frames as recommended, it didn't really work, still.
Awesome work environment for one person can be not ideal for another.
Pretty much all the top AI labs are both intensely competitive and collaborative. They consist of many former IMO and IOI medalists. They don't believe in remote work, either. Even if you work at Google DeepMind, you really need to be in London for this project.
You can break your sequence into two parts. One part goes through the encoder and the other goes through the decoder, so each token only goes through one transformer stack.
You can see the thoughts in AI Studio UI as per https://ai.google.dev/gemini-api/docs/thinking#debugging-and....