
We Asked People Around the World How They Feel About AI. Here’s What We Learned - joeyespo
https://foundation.mozilla.org/en/blog/we-asked-people-around-the-world-how-they-feel-about-artificial-intelligence-heres-what-we-learned/
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ohazi
I'm mostly just tired of all the hype, and at this point really wouldn't mind
another AI winter.

Machine learning ended up being a useful technique to add to the classical
computer vision toolbox to do things like object identification and semantic
segmentation. These things were almost impossible to do robustly before, and
now they're relatively straightforward, if still a bit challenging.

Same with audio identification and synthesis. It's a lot better than the old
Markov chain based systems for these specific tasks.

But that's about it - it's useful as a _tool_ for certain classes of highly
specific tasks, but has been largely crap everywhere else.

The promised super smart products that were end-to-end "AI" never really
materialized. Smart speakers are shitty and pointless. And IBM renamed all of
their products Watson.

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lettergram
The most interesting applications are what you don’t see.

For instance, you can do a lot of your engineering and even data science work
without ever touching real data (due to ML):

[https://medium.com/capital-one-tech/why-you-dont-
necessarily...](https://medium.com/capital-one-tech/why-you-dont-necessarily-
need-data-for-data-science-48d7bf503074)

Not saying it’s not over hyped, just that good AI would augment your life in
ways subtle, but hugely impactful.

Edit: Another thought - how are funds in the market allocated? Partially by
humans, largely augmented (if not explicitly allocated) by AI... meaning AI
determines which companies get funding and thus what you can buy / access is
determined by these algorithms

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gran_colombia
If you work primarily on synthetic data as a data scientist, you deserve to
get fired. The link is pretty cool though.

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lettergram
The argument is you can design a model, check that it runs, then submit the
job to train / evaluate the model on real data. The data scientist doesn't
necessarily need to touch the real data ever (especially if ML is used).

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tomrod
This is not a great setup if one requires a model that can extrapolate.

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gran_colombia
AI does not exist. There is no 'intelligence' in ML model.

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nscalf
I find that, if you look closely enough, there can never really be any
“intelligence”. Everything is just a model or a likely association or a
statistical model, etc. and it will always be that. This statement of there
being no intelligence really seems overly reductionist.

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Scarblac
10% of the world "well educated" about AI, that's not how I would usually use
that term.

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JaRail
Interesting to see how much more excitement there is for AI in the developing
world. They're the ones with the biggest problems so it makes sense. Seems
NA/Europe feels like they have the most to lose. While the reality should
hopefully be win-win, it does seem likely to level the playing field around
the world. But a hyper-capitalist country like the US is definitely going to
have the biggest social challenges adapting to job losses.

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wendyshu
Al who?

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corporateslave5
Open AI GPT-2 model is pure trash, and self driving cars don’t work. These
could be considered break throughs, or AI beyond what we’ve seen, if they
worked.

Until one of these two works as promised, AI is a failure and neural networks
are still just simple stacked linear regressions. They aren’t greater than the
sum of their parts.

