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Artificial-Intelligence Experts Are in High Demand

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Re: Artificial-Intelligence Experts Are in High Demand

#91

Post by protonfish »

one-more-minute wrote: post #84
protonfish wrote: post #79

Earlier quoted context omitted.

You are repeating the same mistake as before. The difference is significant between admitting we don't know what those lines are and claiming that they don't exist.

It's not a mistake – I see the difference and I am claiming that those lines don't exist. There's plenty of evidence for that, including the continuous range of intelligent behaviour from plants to humans. It's just an empirical fact that there's no hard line. Of course, that could be wrong – new evidence may come to light, after all. But even so, it doesn't make any sense to say that trying to understand and replica…

If you are going in the wrong direction, you won't get to your destination by going faster. You should stop and rethink and you won't do this unless you can admit that you might be wrong.

How much research had you done before you assertively proclaimed that those lines don't exist? Because it looks nothing like a smooth transition to me.

Re: Artificial-Intelligence Experts Are in High Demand

#92

Post by dantillberg »

jules wrote: post #56
Daishiman wrote: post #4

This is suspiciously close "data science" and "machine learning" experts. Can't we just be honest and say that most of these are applied statistics jobs with a specialty in large volumes of data? Or is "statistics" just not fashionable enough nowadays?

There is quite a big difference between statistics and machine learning. A lot of the most successful machine learning algorithms do not have a statistical grounding or did not when they were invented. E.g. neural networks, SVM, low rank matrix approximation, k-means, decision trees/forests. Statistics is one of the tools in the machine learning toolbox.

But, to look at one example: neural networks. Neural networks may have been inspired by attempts to recreate the structure of the biological nervous system, but the way in which they are used commonly, e.g. "learning" via back-propagation, is really just a statistical regression for a gigantic equation with many free variables.

My preferred term is "predictive analytics," which I feel kind of straddles statistics and machine learning, and also serves as a nod to a common difference -- "statistical" methods often yield understanding, while "machine learning" methods are often opaque to human insight but yield predictions.

Re: Artificial-Intelligence Experts Are in High Demand

#93

Post by sjg007 »

jkbyc wrote: post #26
Nvn wrote: post #22

Earlier quoted context omitted.

As mentioned in the article, AI is the broader field that encompasses Machine Learning, and to a large extent also Data science (and Computer vision, NLP, Pattern recognition, etc.). And while data science might utilize a lot of statistical techniques, it is a huge stretch to consider the whole AI field to be 'statistics'. In general, AI borrows many more techniques from mathematics than it does from statistics. Howe…

I believe the OP's point is that the demand is for applied statisticians and not for AI experts (in the sense exactly as defined by you).

I think there are two levels. On the one hand, many firms need big data experts who can reason statistically and apply machine learning techniques to their domain. This started out 15 years ago as predicting shopping cart basket items etc..

On the other side the big tech companies are investing heavily in Deep Learning for things like NLP, Speech, Vision, Siri, and wherever else these neural net approaches may work etc...

Re: Artificial-Intelligence Experts Are in High Demand

#94

Post by sjg007 »

rayalez wrote: post #62

The big thing that prevents me from getting into AI is the lack of practical projects that I can build. It is a very interestimg field, but as a self-taught programmer I'm used to learning by building things, and it's hard for me to come up with some project that would be practically useful and yet doable. Does anyone have any ideas?

Try to build a Siri clone, or try any of the Kaggle projects using neural networks.

Re: Artificial-Intelligence Experts Are in High Demand

#95

Post by pjungwir »

rayalez wrote: post #62

The big thing that prevents me from getting into AI is the lack of practical projects that I can build. It is a very interestimg field, but as a self-taught programmer I'm used to learning by building things, and it's hard for me to come up with some project that would be practically useful and yet doable. Does anyone have any ideas?

- Politics: Predict which candidates/bill will do well. Or predict which bills you might care about. Identify the strongest features. Publish a writeup with nice maps/charts. Inputs: FEC donor data, vote history.

- Sports: Predict game outcomes, player performance. Make money playing fantasy sports?

- Real estate: Build a better tool for house assessments that identifies "comps" and predicts what the house should cost.

- Astronomy: Something about exoplanets?

- Amazon prices: Find opportunities to buy/sell.

- Stock prices: Inputs are news/Twitter, outputs are predictions of closing price.

I'd start with your hobbies and go from there!

Re: Artificial-Intelligence Experts Are in High Demand

#96

Post by Dn_Ab »

jules wrote: post #56
Daishiman wrote: post #4

This is suspiciously close "data science" and "machine learning" experts. Can't we just be honest and say that most of these are applied statistics jobs with a specialty in large volumes of data? Or is "statistics" just not fashionable enough nowadays?

There is quite a big difference between statistics and machine learning. A lot of the most successful machine learning algorithms do not have a statistical grounding or did not when they were invented. E.g. neural networks, SVM, low rank matrix approximation, k-means, decision trees/forests. Statistics is one of the tools in the machine learning toolbox.

SVMs were invented by a couple statisticians/mathematicians in the 60s. k-means also harkens back to the 60s, by mathematicians and control theorists. Decision Trees and Random forests were invented by a famous statistician, with the latter related to bootstrapping, a statstical technique. PCA and factor analysis, forms of or closely related to low rank matrix approximation, were pioneered in the early 1900s, by some of the most famous statisticians ever.

Re: Artificial-Intelligence Experts Are in High Demand

#97

Post by jfoutz »

protonfish wrote: post #89
jfoutz wrote: post #83

Earlier quoted context omitted.

So, what's holding you up exactly? RC cars are cheap, people have done cool stuff with old android phones for sensor packages. If you need more horsepower, stream the data back to a PC, you've got wifi on the phone. New industrial arms are expensive, but you can scrounge one, or get a hobby one. sparkfun had a uArm that would probably work for you.

Because I am a software developer and intelligence hobbyist (from the biology/ethology camp.) I don't know a damn thing about RC cars or android phones nor do I have the time or desire to learn. Sadly, the hardware tinkerers don't know a damn thing about programming intelligent behavior. Until there is some sort of API to connect hardware to a software environment programmable by specialists in that domain, hobbyist…

Hmm. There are a few options. You could get a roomba, and put a laptop on top of it, use the laptop camera to sense, and the serial port to command the motors. I kinda think you could use python to glue everything together.

Mindstorms are really easy to get started with if you want more control over what the robot will look like, but you'll be facing more mechanical engineering problems.

diydrones has a lot of good information about getting things connected. Most people look to RC cars because they're so inexpensive.

So, the big thing with hardware is it kind of sucks. It always feels like using a butterknife to tighten screws. Things are challenging in ways you don't expect. With software, if you make a mistake, you fix it and recompile. With hardware, you hope nothing breaks.

I too wish it were easy. It's not, it's complicated in ways that suck. If you have money to throw at the problem, i bet you can find a nice industrial platform that's built like a tank that has a nice API. That kind of stuff is thousands of dollars, and i'm not familiar with it.

Re: Artificial-Intelligence Experts Are in High Demand

#98

Post by nkassis »

netcan wrote: post #34
julianpye wrote: post #30

This trend is in most companies business-driven, in others it is technical-driven. Few companies have technical leadership that can manage true AI resources. If you remember the ML courses from Uni and experts in that field, you can imagine why. In many universities AI departments are assigned to schools of psychology and philosophy. Only companies with a deep engineering culture as those mentioned here can build up…

What's the potential path forward (say projecting 10 years ahead) from the current growth in demand for data mining centric people? I mean people go and study in response to demand. They learn data mining and AI at Universities. I think it's often people with backgrounds or aptitude in maths. What will the 22 year old with an aptitude for maths that is learning R, SQL, AI-for-business and such be doing in 10 years? I…

I doubt the 22 year old you are referring too will run out of problems to solve. I also feel at some point it will be like a lot of software engineering is today. Working for companies implementing solutions similar to what already exists but tailored to the context of that companies specific needs. As of now I feel that this field is so young that a lot of the solutions are almost completely custom built to the problem at hand and that a lot of work is needed to abstract away those solutions into higher level reusable pieces.

Re: Artificial-Intelligence Experts Are in High Demand

#99

Post by eli_gottlieb »

one-more-minute wrote: post #73
protonfish wrote: post #69

Earlier quoted context omitted.

Just because you don't see the hard lines doesn't mean they aren't there. We are deluding ourselves by avoiding a hard definition of intelligence so we can keep believing that we are creating AI when its really nothing of the sort.

Just because you can't see unicorns doesn't mean they aren't there, but at some point you have to give up the search. It's fine to talk about how, broadly speaking, rats are more intelligent than ants, plants or microbes (which are basically I/O rules with a body), chimpanzees more so than rats, humans more so than than chimps etc. But in general there's a ton of overlap and the qualities we associate with intelligen…

Well I would say that "intelligence" is learning and inference with causal models rather than just predictive or correlative models. You can then cash it all out into a few different branches of cognition, like perception (distinguishing/classifying which available causal models best match the feature data under observation), learning (taking observed feature data and using it to refine causal models for greater accuracy), inference (using causal models to make predictions under counterfactual conditions, which can include planning as a special case), and the occasional act of conceptual refinement/reduction (in which a model is found of how one model can predict the free parameters of another).

Re: Artificial-Intelligence Experts Are in High Demand

#100

Post by eli_gottlieb »

raverbashing wrote: post #16
jsweojtj wrote: post #14

Earlier quoted context omitted.

It happens all the time, and it comes from a mix of things. One way it happens is that you get a PhD in astrophysics with years of data analysis experience in for a data science job. Have a software engineer interview her and he might find that she doesn't know a number of basic computer sciences concepts [traversing a linked list, tail recursion, implement breadth-first-search]. His knowledge background says these b…

This is a good example. At the same time this CS interviewer may not know what's the second central moment of a probability density function.

Uhhh... the variance?
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