pedrosorio

> For some of those solutions we'll try to figure out if they would work, if they handle the edge cases, spot bugs

Most of the solutions will have been posted after submitting to the platform and passing hundreds of test cases, so you'd have to pick a very specific problem and solution to find any bugs/not handling edge cases.

In a "have you memorized the code to solve this problem" interview? Probably.

In a "can you solve this new leetcode problem that just came out and is not in the training data"? Awful.

Maybe you just need to find something you enjoy doing, programming might not be "it"?

Or do you do well solving the problems on your own and just have trouble when being interviewed?

> And then these PhDs will be Research Engineers and such in DeepMind, OpenAI, etc.

Research Scientists. You don't need all that pedigree to work as a Research Engineer.

I don't know about a philosophy. But people with graduate degrees in Zoology seems to be doing well:

https://cew.georgetown.edu/cew-reports/valueofcollegemajors/

For some reason it groups "philosophy and religious studies" and the latter might not lead to very high paying careers, so it's hard to tell what that means for "just" philosophy.

The report [0] has them below the median of all "humanities and liberal arts" majors.

[0] https://cew.georgetown.edu/wp-content/uploads/The-Economic-V...

Why would the ones who control the robots keep you and your descendants alive and enjoying the wealth generated from the robot work if you provide no value to them?

> The solution is to have universal catastrophic insurance for all citizens automatically

> It is not as easy as that because supply is heavily constrained

I don't think this argument works when the data shows 90%+ of the population has health insurance.

Replace Western with Russian and foreign with American and you have Snowden.

The asymmetry you imply does not exist.

The only scenario where this makes sense is if the "all H1B team" is all from the same country / speaks the same language. The issue is not "all H1B", it's the lack of diversity in the team.

This is tough, but there is an easy solution: delivery apps provide a way to communicate with the delivery worker, explain your situation, potentially offer a better tip for the service. They will come to your door.

The natural solution to that problem that eventually develops from your line of thinking is extended unpaid internships. No thanks.

I regret to inform you, I don’t think it’s the same set of people. Writing a cute “Transformers are SVMs” paper and “building chatGPT” are not the same skillset.

“Engineers who like to pretend to be mathematicians” - I heard once.

> but even if they don't one would imagine a quality hire would be able to get a short term loan at a very good rate

Instead of just accepting a job that doesn't have weird staircase salary structures? Good luck finding this unicorn quality hire.

> To me, adding a constant to all edges seems like an obvious idea to try

Yeah, as you explained that is not useful because it does not preserve the shortest-path of the original graph (which is the reason we are making all edges non-negative in the first place).

That is why Johnson's algorithm adds an edge-dependent weight to each of the edges.

here is what I get: track&field, chess, some music

personalized RLHF is the keyword

> But the discriminator of having to "pay an intelligent professional otherwise" sets the bar very high. That implies AGI

I believe they were using that discriminator to classify AI, not AGI.

And their creators?

The original statement:

> "gifted kids are far more likely to contribute significantly to our future"

didn't say anything about gifted kids being far more likely to be "wildly successful with mansions and all that" or "starting many businesses, hustling and selling".

It read "contribute significantly to our future".

Insert "not with that attitude" meme.

> They claim that instead of a real-world accuracy, they wanted to find the “max” accuracy that their classifier was statistically capable of

Yeah, I read this on the GitHub issue a week ago and couldn't believe it. Ideally, their profile(1) should allow them to quickly admit they were wrong on such a simple issue. Pursuit of truth and knowledge, etc.

(1) a young PhD from a prestigious university

> For example, I think a neural network is capable of achieving a “max” accuracy of 100%

Why reach for such powerful tools? f(x) = random(num_classes), achieves 100% "upper bound" accuracy.

> Since their academic background is so relevant

If their academic background were relevant, they would have provided specific negative outcomes that may result from the usage of Llama 2, rather than a vague "the history of this company's choices does not inspire confidence".

What, of the many open source software releases by that company in the ML/AI field "does not inspire confidence"?

See my sibling comment. Very unlikely the author has any familiarity with Meta's history of releasing open source software for ML/AI.

> He is an associate professor in Language and Communication at the Centre for Language Studies of Radboud University Nijmegen. Dingemanse obtained a MA degree in African Languages and Cultures at Leiden University in 2006, and a PhD degree in arts in 2011 at Radboud University Nijmegen

https://en.wikipedia.org/wiki/Mark_Dingemanse

This co-author? Given the relevance of their academic background, I'd take their opinion on "the dangers of using LLMs released by the untrustworthy Meta" with a grain of salt.

> find them entertaining

I also find them entertaining. That doesn’t mean I believe them.

> The explanation is very simple: they simply didn't think it through

Something I rely on to predict the future is the kind of thing I would want to think through. That’s particularly hard to believe of “intelligent people” when checking that it’s nonsense takes very little effort.

There may be an education-intelligence gap that explains why astrology is not evidently false to those people though.

This seems like a counterintuitive idea.

Older people helping to make more products/services is a downside to society at large?

I would understand if “working” was a competition for limited resources. But if it is, in fact, a value generating activity, how does it harm society at large?

e.g. Having more doctors work until later, if they are capable, is not a net positive for our society’s ability to provide healthcare?

> They also have a hard cap on the number of allowed users you may have using your Llama-based product above which you must seek further Meta approval.

This is not what the Llama 2 license says [0]. There is a cap on the number of active users of products (any products, not just ones that may make use of Llama) by the company who plans to use Llama 2 as of Llama 2 release date.

Not a “future cap on number of users of your Llama2-based product”. Also, the cap is 700 million users.

> If, on the Llama 2 version release date, the monthly active users of the products or services made available by or for Licensee, or Licensee's affiliates, is greater than 700 million monthly active users in the preceding calendar month, you must request a license from Meta

[0] https://github.com/facebookresearch/llama/blob/main/LICENSE

I’ve seen so many of these on Twitter since chat GPT came out.

> Look at this amazing capability, it gets it perfectly! (screenshot of interaction with clear flaws/outright wrong answer)

Middle age is generally not defined as 50% of your life expectancy: https://en.wikipedia.org/wiki/Middle_age