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> I only wonder though, how long this economy is going to last, i.e. how long until AI is so commoditized that the value of data goes towards 0 as well Well, f
by bunderbunder 7y ago
> I only wonder though, how long this economy is going to last, i.e. how long until AI is so commoditized that the value of data goes towards 0 as well
Well, first - AI in general is not very commoditized at all. It's just machine learning that is becoming commoditized. And the distinction is meaningful.
Going from that - data is the stuff you use to build ML models, and it's absolutely essential to doing better ML. ML becoming commoditized increases the value of (good) data, because it's an essential ingredient for any ML company trying to gain an edge in an increasingly competitive market. It's not entirely unlike how oil being a commodity does not mean that oil drilling equipment is cheap.
We see this play out in the companies that are big users of machine learning. Facebook, Microsoft, Google, etc. are all quite happy to publish the software they use to build their models. But the data is kept under lock and key and buried under the bottom of the sea. And a huge, huge, huge amount of their competition is centered around attracting the people who produce that data, because it's the ability to generate more data that gives them a competitive edge.
- m_mueller 7y agoI absolutely see the point about the value of data going up, and again, that's the paradigm we're living in now. It's just that I'm not sure this is going to last for long. What's new in ML is, at its core, increasingly powerful pattern matching. But with even some moderately strong cognitive functions on top of that, the data processing monster could start feeding on itself, i.e. go out to get new data on its own. We don't have enough images of donkeys feeding on grass for our object recognizer to match against? Let me coordinate with our drone network to go get a couple of terrabytes...
- codesushi42 7y agoThat's not how ML works. You need to acquire labeled data to train on.
- m_mueller 7y agoAgain, I'm talking about possible future technology. What if you can infer labels some other way? The fundamental element you need is not labels but a cost function - that could e.g. be curiosity and fear (of disappointing the end user). The most fundamental part that ML is missing to be AI, is to have a model of the world, with which such a cost function could evolve organically. Once you have that, AI can go and explore on its own.
- walterbell 7y agoUntil humans stop providing free input to their machine (AI) adversary, e.g. because of new business models that pay some humans for high quality feedback. That will leave parasitic AIs competing for low quality signals.
- bunderbunder 7y agoIf you can accurately, inexpensively, and automatically figure out what the labels on the classifier's training data should be, then you have no need for the classifier.
- codesushi42 7y agoThat makes no sense. If you can already infer the labels beforehand, then you already have a working model, right? The job of the model is to infer those labels. The model needs to be trained to accurately predict those labels by using examples that were labeled beforehand.
- m_mueller 7y agoBy model of the world I mean something much more than what's called an ML model today. I mean the cognitive ability to predict the past and future of some part of the real world based on observation. Most simple example: Seeing two video frames of a massive object moving in front of a reference background and predicting the curve it's going to do, and where it came from. Only having such an understanding of the world (physical laws, human interactions with it etc.) allows to program in much more general cost functions that can get the system to explore on its own, not just within a given rule set, but the rule set itself.