mrdrozdov

No.

This is such a click-bait title and has nothing to do with scalability.

This paper the article refers to is fantastic! I think it's a work most in ML research should become familiar with. And if you believe in the power of benchmarks and data, then this holds even more true. Investing in diversity in datasets is likely an impactful way to make progress in AI/ML.

Minor typo in this article...

ARTICLE: Among their findings – based on core data from the Facebook-led community project Papers With Code (PWC) – the authors contend that ‘widely-used datasets are introduced by only a handful of elite institutions’, and that this ‘consolidation’ has increased to 80% in recent years.

...but right after, they quote the paper and clearly it is 50% not 80%. See the quote from the paper:

PAPER: ‘[We] find that there is increasing inequality in dataset usage globally, and that more than 50% of all dataset usages in our sample of 43,140 corresponded to datasets introduced by twelve elite, primarily Western, institutions.’

...and the article is leaving out this relevant quote from the paper:

PAPER: Moreover, this concentration on elite institutions as measured through Gini has increased to over 0.80 in recent years (Figure 3 right red). This trend is also observed in Gini concentration on datasets in PWC more generally (Figure 3 right black).

...and in general the article is right that inequality is increasing over time, but Gini is a specific metric to measure inequality, and 0.80 is not the same as 80% inequality.

Ocean's Eleven bitcoin edition...

Adding a few more from HBO and Amazon...

  Greenland
  The Little Things
  The Conjuring
  Killerman
  Ghost in the Shell (live action)
  Redline
  Sputnik

I don’t know. I watch a similar amount of movies each year, and I still enjoy it. If anyone is looking for some more obscure recommendations, can check out The Dreamers, and Stilyagi.

EDIT: I have to add that I reference movies a lot in conversation. Often, I’ll watch a movie then immediately call a family or friend to discuss some finer point. This happens frequently, sometimes for a fairly mundane movie detail.

EDIT2: Now I really want to make a list of movies just from this year, since my number has definitely gone up since COVID. I think I’d easily break 100 in 2021 alone.

EDIT3: Here’s a list from my Netflix history since June 1. Mix of TV and movies. I added Justice League Extended Edition and Replica even though they’re HBO because I watched them recently (within the last week). This isn’t really a representative list of my watching, plus I tend to watch a bunch of similar movies/shows, then switch to a new cluster. This group is particularly action heavy because I was playing a lot in the background recently while doing other work. All of these were fun! Even if I don’t think they are the best ever :))

  Movies 2021 June-July

  Zack Snyder’s Justice League
  Replica
  The Take
  Darc
  American Assassin
  S.W.A.T.
  Sniper Legacy
  The Interpreter
  Redemption
  Extraction
  Spenser Confidential

  TV

  Biohackers
  Shooter
  Quantico
  Sweet Tooth
  Record of Ragnorak
  Bodyguard
  Hollywood

I think the core argument has much more to do about plagiarism than learning.

Sure, if I use some code as inspiration for solving a problem at work, that seems fine.

But if I copy verbatim some licensed code then put it in my commercial product, that's the issue.

It's a lot easier to imagine for other applications like generating music. If I trained a music model on publicly available Youtube music videos, then my model generates music identical to Interstellar Love by The Avalanches and I use the "generated" music in my product, that's clearly a use that is against the intent of the law.

As others have mentioned, this hacker news headline is deceptive. The valuation is with respect to ByteDance, which has a business suite beyond TikTok. Even the article headline mentions this: "TikTok Owner’s Value Exceeds $100 Billion in Private Markets"

There are other facts about ByteDance such as having nearly 100k employees and a moderately size AI research lab that makes this news less surprising.