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Comment by dennybritz | Hacker News Reader

I agree. The point I was trying to make is not whether it is impressive or not (it is impressive!), but that the general press hype about "AI breakthroughs that will soon kill us all and need regulation" is over the top and misleading. The probably massive engineering effort that went into this is, to me, more impressive than the algorithmic innovation, if any.

Progress is made with small incremental improvements, including this one, and there have been few real algorithmic "breakthroughts" over the past few years. That's why I think it is important to give some perspective to the hype.

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I feel that you are missing the whole point of "AI breakthroughs that will soon kill us all and need regulation". It's not about AI becoming self-aware and start to proactively taking over humanity starting from a Dota game, it's how we are finally capable of putting AI anywhere.

The point Elon Musk was trying to show is that nowadays, we have the technology and the research to replace humans by AI for making judgement calls, no matter how difficult it is. And this was proven with a "simple" game of Dota. And if we are able to build a system to play Dota, we are also able to build AIs for anything at all.

You claim that there had not been any real breakthroughs over the past years but truth to be told, today we have AI playing Go, AI managing self driving systems, AI playing games of Dota against the top players. All of this happened over the last few years, 5 years ago this all felt like a distant future.

> AI playing games of Dota against the top players

This example weakens your argument. As TFA explains, the bot can only play a very restricted version of Dota - much simpler than chess - which means it was thinkable ever since the '90s, when Deep Blue beat Kasparov.

Self-driving cars have been around since the 1980s.

"nowadays, we have the technology and the research to replace humans by AI for making judgement calls, no matter how difficult it is"

"if we are able to build a system to play Dota, we are also able to build AIs for anything at all"

These are stated like facts, but are not facts.

There are decisions made by humans which no AI system today can make well, and there are problems for which we have no idea how to build even mediocre AIs. The claim that someday we will have AGI is plausible but not yet certain to be true.

"There are decisions made by humans which no AI system today can make well, (...)"

Exactly, that is precisely the point. Companies and business will just rush to implement the next big neural network to boost their business, no matter how immature the technology is.

And the claim is not about AGI, it's more about the little things. For some reason people like to think really big and exaggerated scenarios when it comes to AI.

Let's take web apps as an example. We can all agree that the state of the art of the current web programming is very poor: JavaScript, NodeJS, Electron, CSS, etc. The technologies are bloated, they are slow, full of hacks and workarounds, and so on. And yet... people use them for everything, it's like the Atwood's law described: "any application that can be written in JavaScript, will eventually be written in JavaScript"

I imagine that a similar scenario will happen with AI and neural networks. Can you imagine, for example, start dealing with an AI instead of an human when it comes to customer service? Maybe it is already happening, if you look for stories about Google's customer service in the internet, you would think everything is run by some sort of AI there.

Another example, look at Microsoft is doing with Visual Studio's telemetry data: https://blogs.msdn.microsoft.com/dotnet/2017/07/21/what-weve...

I wouldn't be surprised if they built a neural network to feed all that data to and to have it to produce a UX "optimized" for mass consumption.

We are getting into a time in which everything will be powered by "AI" and I think that's what OpenAI is trying to regulate before we get every single business pestered with an half-assed implementation of neural network and data analytics.

When should people attempt to regulate AI, when it's too late? Stopping a problem before it happens is called foresight. And if you pay attention to the press, it's not about killing us all, it's about disrupting the world, i.e. destroying jobs.

The reason I don't buy the "destroying jobs" argument is that we have tens of thousands of jobs just in the small country where I live that could be automated away by 1980s technology. For a US-specific example, look at the way you submit your taxes. That shit could be 99% automated away, like it is in many European countries already, and you have several large companies that would come crashing down, together with many thousands of government employees suddenly without a job. There's no AI required. Why hasn't it been done already? Why should AI change that?

Those jobs exist due to regulatory capture and the difficulty of changing tax law in a bitterly divided nation, just because a few industries found a way to use government to prevent progress and automation doesn't mean progress and automation isn't a danger; most industries won't be protected by regulatory capture. The "destroying jobs" thing is not an argument, it's a fact, it's what automation does, there's nothing to "buy", you either understand it or you don't.

> most industries won't be protected by regulatory capture.

And that's s good thing. It's unfortunate for those whose jobs are automated away, but without automation, goods and services can't keep up with the increase in population and demand. What's needed isn't prevention of automation, but how to increase the number of people with enough education to implement even more automation.

I agree that it's a good thing, but your last statement is simply not in accordance with reality. The median IQ is 100, half the population is of below average intelligence, the problem we face is what to do when labor is no longer valued because machines do it all and half the population or more has no skills of value to the market. Education helps the top few percent stay ahead of the machines, it does nothing for the bulk of society who are not and will not ever be smart. Thus it's an economic problem of resource distribution, we must move away from a labor based economy if we allow automation to continue. We cannot handle massive automation with our current economic system.

> bulk of society who are not and will not ever be smart.

It used to be that most people are illiterate, and cant do maths either. I'm sure if you measure IQ back then, it'd be quite low. And yet, the population got education, and lo and behold, the avg IQ increased.

Making the assumption that intelligence remains constant is wrong. I'd even suggest that most people are capable of doing things that you might consider require high intelligence, like writing code, or doing research, or designing solutions. Those who currently can't are merely so because of lack of opportunity (especially during formative years).

Making the money to increase the level of education will have the indirect effect of curbing the automation and unemployment problem.

> the problem we face is what to do when labor is no longer valued because machines do it all and half the population or more has no skills of value to the market

Need anything be done? You said it yourself: that portion of the population has no skills of value to the market. They're worthless.

I somewhat agree with that but I think the biggest (underappreciated) algorithmic improvement recently was MaskRCNN. The ability to do Segmentation and Detection in the same net is huge.

But isn't that slow? It doesn't parallelize well for real time processing, because it goes sequentially pixel by pixel while CNNs process all pixels in parallel.

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