Hacker News Reader

Comment by fxtentacle | Hacker News Reader

You sound like an NVIDIA salesperson trying to sell me on a $3000 Titan ;)

There is no doubt in my mind that an AI with billions of parameters will be excellent at memorizing stuff.

I also have no doubt that research activity has exploded, which might be related to the generous hardware grants being handed out...

But all that research has produced surprisingly little progress over algorithms from 2004 in the field of optical flow.

The papers I looked at were the top-ranked optical flow algorithms on Sintel and KITTY. So those were the AIs that work best in practice and better than 99% of the other AI solutions.

View on HN

While it's not my area of expertise, I am a bit wary of contest results. It seems like an exercise in overfitting via multiple comparisons? Maybe some algorithms with a slightly lower rank are actually more robust?

If it's as bad as you say, it seems like a critical evaluation would be pretty interesting and advance the field.

I wonder how many solutions within the AI field could just be categorized as "Automation"

All of them. That's how AI works. Not by making smarter machines, but by destroying intelligence by smashing it into machine-digestible bits.

That's what caused the first "AI Winter": Rules-based "AI" engines became what we call "Business Rules". AI didn't go away - it just stopped being an over-valued set of if-then logic and slots (value-driven triggers) with a cool set of GUI tools to build rule networks.

Source: Used to work for an 80s-era "AI Company"

>There is no doubt in my mind that an AI with billions of parameters will be excellent at memorizing stuff

We're way past memorization. We're into interpolation and extrapolation in high D spaces with Bayesian parameters. Sentiment analysis and contextual searches - search by idea, not keyword. Heuristic decision making. Massively accelerated 3D modeling with 99% accuracy. Generative nets for text, music, scientific models...

Sorry, but you're behind the times, and that's ok - one of us will be proven right in the next 1-5 years. Based solely on the work we're doing at the startup I'm working for, we're on the cusp of an ML revolution. Time will tell, but personally I'm pretty excited. And don't worry, I'm not working in adtech or anything useless.

That said, the driving problem seems to be quite far from being solved, I agree though it is outside my expertise; but I think the primary issue is that this is an application where error must be unrealistically low, a constraint which does not apply to many other domains. You can get away with a couple percent of uncertainty when people's lives aren't on the line!

Would you be willing to link to some papers and cite some specific algos to play with? The above cited specific algos. What are the new versions of these named algorithms?

Reply on news.ycombinator.com