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Comment by ben_w | Hacker News Reader

My disagreement is something this article half-acknowledges:

> The brain has the potential for a petaflop per second of processing power. However, the measured performance of conscious processing is only about 50 bits per second.

Why assume that either training or playing Go involves only conscious decision making? Anything that we call “common sense”, “gut feeling”, “aesthetically pleasing” etc. is something we can’t (or cannot easily) generate a conscious rationale for.

Of course, that’s doesn’t mean humans don’t beat computers at all; last I checked, humans can make acceptable quality inferences from far fewer examples than an A.I.

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Exactly this. Conscious information processing constitutes only a tiny part of the processing within the brain. Real computational power of the brain is in the order of petaflops to exaflops 1).

On the other hand, AZ used a lot more than 1E18 calculations of training to beat human level play, so that part is also wrong. In fact, the total processing power of the 5000 TPU's used are in the order of 1E17 operations per second.

Still, since 1E17 flops is comparable (within 1-2 orders of magnitude) to the human brain's raw capacity, and AZ could reach superhuman level in GO in less than 10 hours, that means that AZ can be seen as more efficient than human brains at GO (in terms of learning rate/calculation, not necessarily per watt)

This should also not be surprising. After all, GO (like chess) is a very abstract game, far removed from the tasks that the biological brain has evolved to do well.

For tasks that the brain does well, such as pattern recognition in the environment that humans live, the human brain is still much more efficient. A human can learn to drive a car in 10's of hours, while AI's still require millions of hours of training, and they still end up inferior.

So, in the end, the title is correct (and also common knowledge for anyone following this development), even if almost all of the content in the article is way off.

Was this a high school essay?

1) http://hplusmagazine.com/2009/04/07/brain-chip/

> A human can learn to drive a car in 10's of hours, while AI's still require millions of hours of training, and they still end up inferior.

I think it's a bit unrealistic to compare these numbers. A human learning to drive has usually started with 16-18 years of learning how the world works before the 10 hours of transfer learning.

1 million hours ~= 114 years. At best, humans are still a factor of 10 better in terms of necessary training examples.

The brain does however have the advantage of evolution optimising the hardware for specific tasks. That's been going on for a while.

Agreed. I think the next two steps in this thread would be:

* Driving isn’t natural, it is movement which involves mostly fine motor skills combined with situational awareness of unnaturally shaped objects, which are 20 times out mass, moving 5 times as fast as we normally do, in an unnatural environment (roads, traffic, street furniture)

* Yes, but (1) evolution still helped us get the basics, and (2) our designs are based on what our minds can cope with, the ones which we can’t cope with are either unpopular or get banned

But that's still an advantage humans have over AI isn't it? Humans have the capacity to transfer learned knowledge and behaviors to relatively unrelated domains with immediate utility. Show me an ANN which can do that.

You are right, and there is a whole area of AI research called Transfer Learning attempting to replicate this with machines.

https://en.m.wikipedia.org/wiki/Transfer_learning

I once played in two poker tournaments on back to back weekends.

Tournament 1 on adderall. Tournament 2 without adderall.

Tournament 1 my consciousness and subconscious seemed to be working in tandom. I knew what action to take, and why I was taking that action.

Tournament 2 my subconscious seemed to play a bigger role being off the adderall. I was making the right decisions for the most part same as the week before while on adderall, but I was not consciously completely sure of my reasoning for most decisions until several seconds, minutes, or even hours after I had reflected on my decision making.

A little food for thought

So which version worked for you better financially?

I wonder if that's part of what's going on with autism-spectrum-disorders: i.e. an autistic mind doesn't set the threshold of what's worthy of conscious thought at as high a level as neurotypical people, so they get more caught-up in the low-level details.

>Why assume that either training or playing Go involves only conscious decision making?

The author doesn't -- assume that. They just state that "the measured performance of conscious processing is only about 50 bits per second".

Not only they do not make any explicit assumption that that (conscious processing) is the only processing going on, but also by spelling out that 50 bits is just the "conscious" part, they already imply that there's is/might be also subconscious processing going...

> humans can make acceptable quality inferences from far fewer examples than an A.I.

Perhaps the fact that we think we can do this isn't the greatest strength. While a lot can be said about the flaws of "Thinking Fast and Slow", one of the things that is certain is that many people reach an inference point and stop, but these inferences are often wrong.

The fact that an AI will be able to develop inferences with so much data in so little time is a real strength that we aren't going to be able to match.

I don't think that it's necessarily useful to compare the human brain with computers, because we have to apply distraction filtration to the system that a computer doesn't need to worry about much, and I'll bet that takes up tons of processing. I would argue that any computing system is an extension of your own mind, and with the data that it can compute and display it can be used to improve a broken decision making process.

>many people reach an inference point and stop, but these inferences are often wrong.

Still good enough for us to be top dogs on the planet and even reach space. Where's the AI doing that?

And soon we'll be top dogs on a smoldering rock. We're doing really well.

Every dog has its day.

Well sure, but that’s a completely different measure of performance, and sometimes ‘number of examples needed’ is the important one — we don’t always have the luxury of Big Data, as some experiments are just too expensive.

> humans can make acceptable quality inferences from far fewer examples than an A.I.

Is this actually true? If I show you a bunch of shapes and ask you to make an inference, you're unavoidably drawing from an entire lifetime of experience.

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