As someone who's capable of implementing and understanding many of the most fashionable tools in AI, I don't know what to do with the current economy. I think there is far too much attention being paid to the pie-in-the-sky research, and even though wealthy investors think the things that they don't understand and I do are capable of accomplishing things that they think can be accomplished and I don't, the problem is that they want to pay people like me to chase their dream. And while I do love money, I also love the idea of living a meaningful and fulfilling existence by pursing technologies that will advance mankind.
Can other people who've actually seen real promise in their AI research chime in and help convince me that we are actually on the precipice of something meaningful? Not just more classification problems and leveraging the use of more advanced hardware to do more complicated tasks.
I don't think we are on the precipice of general AI, perhaps we are not even close.
But we don't need fully general AI to have a huge transformative impact on society and the economy. Think about the full spectrum of jobs that exist in the modern world: doctor, teacher, construction worker, truck driver, chef, waiter, hair dresser, and so on. How many of those jobs actually require the full power of human intelligence? In my view, almost none. Maybe the intelligence required is still more general than what a computer can do, but probably a determined research effort could be enough to make up the gap for any specific task (say, to cut someone's hair, you need to have good visual understanding of the shape of the head, and very good scissor-manipulation skills, and a good UI so that the customer can select a style. It hardly seems like an insurmountable technical challenge).
> I don't think we are on the precipice of general AI, perhaps we are not even close.
In all probability, I want to agree with you.
However, deep learning unnerves me. Seriously, how many people who evolved the deep-learning-trained models actually understand how those models work? But the models produce good-to-great results.
So there could be a small chance that general AI could randomly and spontaneously come into existence. Either we are too close to general AI or infinitely far from it. We can't tell it because we are not sure if intelligence is a evolved goal oriented function or an engineered substance. Being an atheist, I believe the first part - and thats what deep-learning based AI looks like.
A major difference here is that humans don't have user defined stimuli.
Human intelligence evolved because of the need to survive which evolved because of the need for genetic replication. Our need to survive lead to a nervous system which created the need for a central management platform (the brain).
People do understand the deep-learning models they create. They're based on a user defined limit for error which is the mathematical distance between what is and what is not.
I think that until we have an algorithm that can rewrite itself optimizing for existence (bug-less-ness and a continuous power supply?), we won't even scratch the surface of general AI.
They train a model that translates signals from the motor cortex to directly stimulate the patient's forearm muscles. It is the first case of a quadriplegic man being able to control his arm directly with his mind.
That is really cool. Just like it was really cool when we learned how to translate neural signals farther away from the motor cortex to do similar things a decade ago. But I'm failing to see the evidence of revolutionary AI. I see a really well-researched piece of hardware paired with a solid understanding of anatomy and probably a few great data scientists to assist in it all.
And the consensus in the Neuroscience community, from what I understand, is that this is two things (1) a great feat of engineering and (2) a great demonstration of the brain's ability to learn and adapt.
Given the OpenAI initiative and the explicit intention of "democratizing" AI, it seems they're interested in funding application, not more research.
I think the results seen from deep learning along with recent developments in commodity hardware(GPUs have made major leaps in the past two years) to run them in a reasonable amount of time has kicked off a frenzy. IMO it does seem a little overhyped in the same way the internet was -- its a tool that enables ideas beyond our imagination, so VCs throw money at companies on a dart board hoping one takes off. In the end, the internet was a revolution but it wasn't as quick as everyone thought.
TL;DR - AI is becoming a tool that can be used by anyone.
>> AI is becoming a tool that can be used by anyone.
The fact that I can do it should be evidence enough for that statement. ;)
As far as the bulk of your comment goes, maybe. That's a prediction, but I can't say that I feel especially confident in the prospects of it. But who knows. Cold fusion looked like a lock for a revolution 60 years ago, and social media looked like a fad a decade ago.
Robotic technology has improved greatly over the last few decades. Just over the last decade, smartphones have created a bunch of innovation in sensors, mobile processors, batteries, etc. And reduced the cost of those things greatly.
But robots haven't really proliferated outside of narrow applications. The main thing holding them back is they are blind and dumb. They can only do very simple rote tasks over and over again. They can't identify objects in an image. They can't figure out how to pick something up. They can't learn from trial and error.
ML has improved massively over the last few years. It's now possible to do machine vision at (arguably) super-human levels on certain tasks. When you see videos of reinforcement learners learning to play video games; that's not a huge stretch from controlling a robot. There have been similar jumps in ability in many other areas. From machine translation to speech recognition.
Sure, there may be lots of over-inflated expectations. But I think a vast increase in automation is well within the limits of what is possible in the near future. You may not get Jarvis. But we will get robots that can understand simple orders and learn to do simple tasks.
That's huge. That's replacing most human jobs huge. It will completely change our economy and our way of life.
If you're worried AI is having no impact at all, some of the places I can think of where it's already had an impact are Google Search, Palantir, and driver assistance (as in Tesla's Autopilot).
So the tools we have now aren't total frauds, and there's probably more to be discovered.
What all three of those examples have in common is that they involve an AI assisting human decision-making. I think that this will be the most lucrative area in the future as well. If you have a set of data a human can't even look at, like a million web pages, the AI doesn't have to be that good at processing it to be useful, since it has no competition from humans. On the other hand, it's rare that you ever need to come up with a million new concepts - you probably just need one. So humans easily outcompete AI at coming up with new ideas. Maybe it's a bit vague what "new ideas" means, but certainly if you're capable of generating new ideas, then you're at least generating turing-complete outputs. Nobody is even trying to do that right now. In the case of image recognition, there are some complex ideas needed to make it work, but at the end you're just outputting a label, getting your model to use the most basic DSL possible.
They are actually very public about the fact they are not a machine learning company and are more or less opposed to machine learning. Their goal has always been to wrangle data and make it useful to human decision makers. not automate decision making.
You don't think that progress in both qualification, vision, and robot control can lead to robots that can replace people in tasks like packaging, assembling, painting or cooking?
What would you say is the missing piece for a robot that knows how to wrap a football for amazon, (and knows what do if the ball falls down, and if there are people around?)
Can other people who've actually seen real promise in their AI research chime in and help convince me that we are actually on the precipice of something meaningful? Not just more classification problems and leveraging the use of more advanced hardware to do more complicated tasks.