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How Clara Labs (YC S14) Is Using Humans to Build AI

blog.claralabs.com

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Re: How Clara Labs (YC S14) Is Using Humans to Build AI

#31

Post by YeGoblynQueenne »

visarga wrote: post #26
jasonlaska wrote: post #9

Earlier quoted context omitted.

We think it's a good idea too ;) Machines and humans truly have different talents: machines are great at memory, keeping track of state, distributing information while people are great at understanding subtle nuance in natural language.

And in another 3-5 years, AI will start understanding subtle nuances too (probably) judging by the number of papers in computer language understanding.

Unfortunately "machines" (AI software, really) are really bad at nuance, subtle or blatant.

The number of papers in the field is a very good example of why: until you've read (enough of) them you have no idea what the state of the field is.

Edit: By this I mean that your assessment about the 3-5 years to "subtle nuance" is extremely, unrealistically optimistic. We're nowhere near AI understanding language. Try 300 to 500 years and you might be closer.

Re: How Clara Labs (YC S14) Is Using Humans to Build AI

#32

Post by YeGoblynQueenne »

jasonlaska wrote: post #29
visarga wrote: post #26

Earlier quoted context omitted.

And in another 3-5 years, AI will start understanding subtle nuances too (probably) judging by the number of papers in computer language understanding.

Even modern methods today (deep recurrent networks, etc.) can do pretty well with these kinds of tasks (a very large ontology for instance) if you have enough annotations of the nuance!

>> Even modern methods today (deep recurrent networks, etc.) can do pretty well with these kinds of tasks (a very large ontology for instance) if you have enough annotations of the nuance!

Where do you get that from? NLP, with neural networks or not, stays as safely away from meaning as is humanely possible while working in an area very closely connected to it.

Also, ontologies? Very few people are interested in that nowadays, though that includes the team that made Watson. The push is instead to do away with all that and rely on statistical approximation.

Re: How Clara Labs (YC S14) Is Using Humans to Build AI

#33

Post by jasonlaska »

kayhi wrote: post #16
jasonlaska wrote: post #12

Earlier quoted context omitted.

Clara has a 1-hr SLA for the processing of an incoming message. While I cannot give numbers on the speed of annotators (or volume), I can say that our platform is designed to enable quick and accurate work via incentive mechanisms. We avoid fatigue in part by making it easy for CRAs to navigate and work with data. Wrt to overlapping annotator schemes, these are known to be effective. We'll be writing more about how o…

Thanks, in the future post would also be interested in the trade offs between building internal system vs. using a 3rd party (maybe you do?) like mechanical turk and the incentive structure.

Our follow up on the humans behind is here: https://news.ycombinator.com/item?id=12074657
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