Hacker News Reader

Comment by skohan | Hacker News Reader

Deep learning has produced a lot of interesting results over the past few years, but we're still miles away from anything that even approximates human intelligence. When I hear someone like Elon Musk say something like "Autonomous vehicles can drive without Lidar because humans can drive without Lidar" it makes me cringe.

The human brain is unimaginably complex. Even if we created a neural network on the order of the 100 trillion or so connections in the central nervous system we would still not even be close. Each one of those synapse is a complex, constantly adapting chemical computer which is sensitive to the interaction of dozens of neurotransmitters. Gradient descent is to neural adaptation as minecraft is to photorealism.

The idea that artificial intelligence will be achieved by adding a few layers to a "deep" neural network, or by throwing more data at it is laughable.

View on HN

>"Autonomous vehicles can drive without Lidar because humans can drive without Lidar"

I have another reason to hate this. If we could give humans lidar to make their driving even better why shouldn't we?

Why should we deny an AI extra senses that can help it do its job better than we can?

There is such a thing as being crippled by information.

> Each one of those synapse is a complex, constantly adapting chemical computer which is sensitive to the interaction of dozens of neurotransmitters.

Granted. On the other hand, electric signals can propagate across a chip several orders of magnitude faster than the chemical-electrical signals neurons use to communicate. So while our current path won't lead us to an artificial brain that works exactly like the human brain, it might still make one that's just as smart through pure brute force.

A biologist in 1902 could very reasonably have scoffed at the heavier-than-air flight enthusiasts who pointed at birds as a proof of concept. The biologist could point out that the complex, many-part motion of a bird's flapping wing was far beyond the crude mechanical processes inventors were trying to use to replicate it. And they'd be right. But in a much more important way, they'd be wrong.

I have no idea whether we're on the path to AGI or not, but I do think that "we're not building machines that work exactly like the brain does" is a poor counterargument.

> "we're not building machines that work exactly like the brain does" is a poor counterargument.

It's not that artificial intelligence has to work exactly like human intelligence; my point is that the system that produces human intelligence is many orders of magnitude more complex than what passes for AI these days.

I think there's an idea out there that because deep learning allows computers to solve some problems that we thought were in the exclusive domain of humanity even a few years ago, that the refinement of these technologies and Moore's law will steadily close the gap between AI and human intelligence. I would venture to guess there are a lot of hard, novel problems left to solve before we get anywhere close.

edit:

It's also not the first time we've thought we had intelligence "figured out". In the middle of last century, there was a lot of hubris around the field of neuroscience as we started to understand the brain's topology, and could map specific functions to brain regions. The feeling at the time was that we would refine our map, and sooner or later once we figured out what all the parts did, we would have a total understanding of the human mind.

This paradigm led to some horrifically misguided practices. For instance the use of lobotomy to treat psychiatric disorders: if the brain is just a collection of functional regions, why not just cut out the bad bits right? Turns out it's not that simple.

It may not be necessary for a system to be as complex as the human brain to reach the raw intelligence levels of the human brain.

You don't need to make a vehicle as complex as a cheetah for it to move as quickly as cheetah. You just strap a rocket to a box and you're there.

Granted a rough solution like that is not as good or as agile as a live cheetah in a lot of ways, but it depends on what you're optimizing for.

You can also train a horse to tap it's foot once for "yes" and twice for "no". You can ask it a bunch of questions, and it can seem like you're having a conversation, but it turns out the horse is just paying attention to a few details about your body language and performing the action you gave it carrots for. It might seem like intelligence, even to the trainer, but it's a parlor trick.

Once the horse starts tapping its foot to accurately detect cancer better than humans, then, parlor trick or not, you've got a fine horse there.

I don't mean to diminish the power and value provided by deep learning, but it doesn't change the fact that pattern recognition is not equivalent to intelligence.

I don't disagree that pattern recognition and intelligence are (probably?) different things.

But if they're functionality equivalent, I'm cool with that.

Heck, it might turn out that humans are already just pattern recognition machines and nothing but. I'm cool with that too.

Perhaps Elon meant to reason the following: if humans can drive without Lidar, then it is possible to drive without Lidar, then it is possible to build an autonomous car that doesn't use an expensive piece of equipment such as Lidar.

Being possible and being a good idea are different. I have also driven a car w/o brakes. Or a motorcycle w/o a working clutch.

The human brain was not designed, but evolved. Why do you think we can't do better when in fact we have done exactly that repeatedly, focusing both on aspects of human biology and other non-human biological systems.

I'm not saying we can't, I'm saying we're not anywhere close yet.

To really grasp how insanely complex the brain is, I recommend videos about "connectomics" by Jeff Lichtman from Harvard. Real eye opener.

> The idea that artificial intelligence will be achieved by adding a few layers to a "deep" neural network, or by throwing more data at it is laughable.

It's called "cargo cult science" and it's an important part of the AI hype train to keep funding coming.

Reply on news.ycombinator.com