So RL is true AI. Alpha GO did make moves inconceivable to the best human mind on the subject. There was no curve to fit into.
It's curve-fitting with a few extra steps. You can do a lot with curve-fitting though.
AI is mostly about curve fitting (2018)
31–40 of 192 posts
Re: AI is mostly about curve fitting (2018)
#32To me, this debate is akin to wondering whether the essence of computing resides in the lower-level, Turing-like operations of a microprocessor or rather in the higher-level constructs and abstractions that we're able to build way "above" them. Whatever it is, intelligence, whether implemented artificially or embodied in the substrate of a living being, is likely built on a ladder of subsystems interoperating at different levels of abstraction.
Re: AI is mostly about curve fitting (2018)
#33"Machine learning" used to be a safe haven. You could flee there to escape the Terminators and brain-on-a-chip graphics. Business PR deliberately killed that. They wanted their ML algorithms to be refered to as AI, so they could fully ride the hype train.
AI used to be a tight quirky community. Having the brain as inspiration led to all sorts of anthropomorphizing. This was ok. Researchers understood what was meant with "learning", "intelligence", "to perceive" in the context of AI. Nowadays, it is almost irresponsible to do this, not because you'll confuse your co-researchers, but because popular tech articles will write about chatbots inventing their own language and having to be shutdown.
Still, as a business research lab, it is good to get your name out there, so all the wrong incentives are there: Careful researchers avoid anthropomorphizing, and lose their source of inspiration -- you can not be careful with difficult unsolved problems, you need to be a little crazy and "out there". Meanwhile, profit-seeking business engineers and their PR departments, obfuscate their progress and basic techniques, all to get that juicy article with "an AI taught itself to X and you won't believe what happened next".
The researchers actually busy solving the hard problems of vision, natural language understanding, and common sense, do not have time to write books about how AI is not yet general. Nobody from the research community ever claimed that, nobody came forward to claim they've solved these decade-old problems. It is people selling books railing against the popular reporting of AI. Boring, self-serving, and predictive, and you do not need to fit a curve to see that.
All this quarreling about definitions and Venn diagrams and well-known limitations is dust in the wind. Go figure out what to call it on your Powerpoint presentation by yourself, and quit bothering the community.
Re: AI is mostly about curve fitting (2018)
#34Re: AI is mostly about curve fitting (2018)
#35Depending on how complex a curve, and how many dimensions it is in, couldn't you argues that is essentially what our brains do as well? Not that I am defending the massive hype field that is ML today, but curve fitting is a form of intelligence.
First, no AI that I know of has at its disposal a full blown model of the world it operates in, whereas most human brains do, and even if the model is imperfect, it is capable of producing fairly accurate simulations (what-if scenarios). Second, deep learning model, however much we'd like to think they do, aren't capable of doing proper causal inference in a general setting (that is, within the confines of the model)…
It's all pretty meaningless semantics and guesswork.
Curve fitting means adaptive computation in networks of fairly simple units that allow for fairly general computation, i.e. traversing program space to find a good solution, or equivalently, intelligence is about evolving/searching a program that solves a wide array of tasks. It is about finding programs that maps from sensory space to the space of action sequences, maximizing reward.
But you need the right prior structure such that learning and producing action sequences is efficient or even feasible/reachable. You can see any additional program structure that aids e.g. generation and recall of memories and planning (production of output targeted at solving a goal) as prior structure that limits and defines the searched program space. You can even regard a planning module as part of the curve fitting as it simply concerns the last step of producing the output. Therefore, intelligence is "curve fitting".
So the actual question is: How much additional structure over just a large number of simple repeated units is necessary? Nobody knows. Possibly not much. Possibly quite a bit.
Re: AI is mostly about curve fitting (2018)
#36Curve fitting is a useful tool, even in non ML contexts like a simple linear regression. There's the hype, which will eventually die, and then there's the business/engineering aspect, which will likely stick around.
Re: AI is mostly about curve fitting (2018)
#37Is it feasible to create AI on top of a bunch of other AI?
Current AIs seem more like specific, fairly simple, brain regions. Maybe we need a level up.
Re: AI is mostly about curve fitting (2018)
#38I think intelligence has for some time already been boiled down to curve fitting, even for humans. Our current accepted definition of intelligence in schools is to get a score that is higher than the average to be considered sufficiently intelligent to proceed to the next grade.
I feel anything that we develop for AI would fundamentally always be inspired by our own experiences and hence curve fitting is something we understand to be the best metric to optimize for.
Re: AI is mostly about curve fitting (2018)
#39Is it feasible to create AI on top of a bunch of other AI? Current AIs seem more like specific, fairly simple, brain regions. Maybe we need a level up.
This is kinda just what libraries like pytorch and tensorflow make easy. Architecting neural networks at a higher level and gluing them together.
Re: AI is mostly about curve fitting (2018)
#40I'm pretty sure that I'm just a curve trying to fit what it means to survive as a human.