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I guess we could all work on our vocabulary once in a while and this way we can contribute to a better world...

The Loebner Prize for artificial intelligence is the first formal instantiation of a Turing Test.

Illuminating article about corporations trying to exploit "open source" and not getting what they want.

I like the red had definition: "To be the catalyst in communities of customers, contributors, and partners creating better technology the open source way."

yeah, it is the same with crowdsourcing in general, when some company "managers" see how much cheaper they could do it but don't understand where it comes from...

pretty impressive stuff!

LSTMs: that was also the first thing in the paper that caught my attention! :) I hadn't seen them in the wild in years... My oversight most likely. The paper seems to be getting ~100 citations a year. Someone's using them.

There are a few papers on them. Though you have to be lucky to get them to work. The backprop is horrendous.

Other possible study: get a textbook example of an image of a pen, evolve it just enough so NN can't recognize it anymore, while minimizing the distance between the original and evolved images. EDIT: Its been done already: http://cs.nyu.edu/~zaremba/docs/understanding.pdf

Of course, you can't really use them to extrapolate. The unknown unknown is always the trickiest :P They should just make another class "random bullshit", really and dump all of this stuff in there. I think there's a potential paper right there

Interdisciplinary teams of handpicked individuals chosen for their field-leading expertise and innovative mind combine humanitarian questions with state of the art science, cutting-edge technology and endless fantasy. Organised by THE Port Association, hosted by CERN (IdeaSquare tbc) and with partners from other non-governmental organisations, a three-day problem solving workshop hackathon will be devoted to humanitarian, social and public interest topics. Interdisciplinary teams of selected participants will work together in the fields of: communication - transport - health - science - learning - work - culture - data

Big data analytic systems are reputed to be capable of finding a needle in a universe of haystacks without having to know what a needle looks like. The very best ways to sort large databases of unstructured text is to use a technique called Latent Dirichlet allocation (LDA). Unfortunately, LDA is also inaccurate enough at some tasks that the results of any topic model created with it are essentially meaningless, according to Luis Amaral, a physicist whose specialty is the mathematical analysis of complex systems and networks in the real world and one of the senior researchers on the multidisciplinary team from Northwestern University that wrote the paper. Even for an easy case, big data analysis is proving to be far more complicated than many of the companies selling analysis software want people to believe.

Most of those companies are using outdated algorithms like this LDA and just apply them like retards on those huge datasets. Of course they're going to come out with bad solutions. No amount of data can make up for bad algorithms.

DeepMind actually got a comp-sci paper into nature...

Responding to calls from the National Science Foundation (NSF) and White House Office of Science and Technology Policy (OSTP), a working group of the American Statistical Association has developed a whitepaper detailing how statisticians and computer scientists can contribute to administration research initiatives and priorities. The whitepaper includes a lot of topics central to machine learning and data mining, so please take a look.

I guess Norvig is trumping Chomsky big time if this is the attitude of the NSF :)))

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.

And the interface even looks a bit less retarded than theano

Exercise can enhance the development of new brain cells in the adult brain, a process called adult neurogenesis. These newborn brain cells play an important role in learning and memory. A new study has determined that mice that spent time running on wheels not only developed twice the normal number of new neurons, but also showed an increased ability to distinguish new objects from familiar objects.

wow ... time to start running again ...

In the past 12 months Americans have searched for Python on Google more often than for Kim Kardashian, a reality-TV star. The number of queries has trebled since 2010, while those for other major programming languages have been flat or declining.

Likely this is correlated with the increased interest in machine learning in the past decade - all the popular DL libraries are Python-based after all...

This is the future of publishing .... thinking to submit something there!! Anyone interested?

Just out - I wish I could understand this :(

ignorance is a bliss :)

Google is taking position here, but can they live up to their own standards?

" Avoid creating or reinforcing unfair bias." Thats the very definition of the AI used today. If you learn from a dataset, you are biased to that data set. No escape from it.

Taking out the trial and error network design and adding ensembles.