DARPA Tackles Machine Learning

coondoggie writes "Researchers at DARPA want to take the science of machine learning — teaching computers to automatically understand data, manage results and surmise insights — up a couple notches. Machine learning, DARPA says, is already at the heart of many cutting edge technologies today, like email spam filters, smartphone personal assistants and self-driving cars. 'Unfortunately, even as the demand for these capabilities is accelerating, every new application requires a Herculean effort. Even a team of specially-trained machine learning experts makes only painfully slow progress due to the lack of tools to build these systems,' DARPA says."

Comments

Re:This headline pops up every few years

[Spottywot]

I think that learning how the biological brain does it before building a learning machine is the wrong way around. I think that the person/team that builds the first genuinely successful learning machine will give the biological researchers a clue about potential mechanisms for learning, it will take a genuine leap of imagination as well as the type of grunt work the DARPA guys are doing.

We need data, not algorithms

[Anonymous Coward]

There are a ton of off-the-shelf machine learning toolkits that are sufficient for 90% of possible use cases. The problem is getting annotated data to feed into these tools so they can learn the appropriate patterns. But all that requires is a host of annotators (i.e. undergrads and interns), not machine learning experts.

Good luck with that

[Black Parrot]

Sounds like the 1990s fetish for making programming languages so simple that even your boss could make reports and do other stuff for himself. Unfortunately, programming language syntax wasn't the primary hurdle: I've had bosses request reports that would add pounds of product and shipping costs.

For ML, it takes a good bit of training just to know what kinds of problems you can apply it to. A cookbook toolkit isn't going to reduce the need for expertise very much.

Re:Good luck with that

[Black Parrot]

Here's an analogy: We've had sophisticated, easy-to-use statistics software packages for decades. What percentage of the population can use them correctly for anything non-trivial?

Tools are nice, but some stuff just inherently takes training. No tool is going to make me a competent oceanographer or particle physicist.