Can a computer write a great novel or a script for a movie? Artificial intelligence (AI) is manna from heaven for sci-fi writers. We've seen a sentient computer called HAL wreak quiet havoc in 2001: A Space Odyssey. We've watched a robot girl's will to survive in 2015's Ex Machina. Most recently we've seen an AI-meets-the-wild-west scenario in TV series Westworld.

Marketers who want to up their social media game are watching the evolution of image analysis intently. The potential value is clear, but the "how" has been less so. Think about all of the data and images that are stored within image-friendly platforms like Instagram and Snapchat. There are more than 3 billion such images shared on social media every day. To better understand their audiences, marketers need to know how artificial intelligence and machine learning can help them analyze social media images that feature their brands (or their competitors' brands) to see how consumers are using products and better market to those audiences.

But many technologies that later came to be considered essential parts of modern life began their life as unnecessary technical baubles. For example, in 1970, the first consumer VCR prototype was unveiled at CES, a technology previously only needed by television studios. Even when a technology goes nowhere--3D TV glasses anyone?--looking at widgets, gizmos, and novelties can still provide a unique window into larger technological and cultural trends. So I defend the gadget as a worthy object of inquiry, and consequently have spent the last week at CES scouring the halls looking for interesting examples, particularly from smaller companies and startups. CES is so big that no such survey could hope to be comprehensive.

In a typical neural network, the series of matrix transformations applied to the vectors in the dataset perform rotation and scaling on the vectors. In order to stop the scaling transformation, the matrix would need to have unit determinant. Is it possible to apply certain constraint on the matrix such that the determinant always stays 1 even after optimization weight update is done? If scaling is not being done, then that means only rotation is getting applied. Does this imply that the norm of the input vectors will be preserved throughout the network computations?

Could artificial intelligence lead to a new species? GUEST: Dr. Don Simborg, author of What Comes After Homo Sapiens,

The growing use of blockchain technology in financial services will include a healthy dose of artificial intelligence, as new, automated analytic techniques look for patterns in the "relationship data" about people, contracts and transactions. That merger of two hot tech trends is one of the predictions made by Dr. Scott Zoldi, chief analytics officer at Silicon Valley analytic software firm FICO, and a recognized expert in the field of artificial intelligence. "Beyond its association with cryptocurrencies, blockchain technology will soon record'time chains of events,' as applied to contracts, interactions and occurrences," Dr. Zoldi wrote on the FICO Blog. "Think about renting a car. In the future, you will be able walk up to a car to lease it, but you'll do so with a micro-loan for which you are approved to lease the car for, say, an afternoon. This micro-loan will have insurance contracts attached to the blockchain, and a codified history of the car's history of drivers, events, and maintenance. As you drive through the city and interact with toll roads and parking spaces, all of this information will be automatically recorded and monitored on the blockchain. When you leave the car and lock it, the lease is complete and auditable on the chain. These kinds of data event chains will create new opportunities for graph analytics and novel new AI algorithms to consume relationship data at scale."

I'll be posting all code and relevant files soon, this demo is part of a tutorial series I'm doing at my university. I'll probably do a twitch stream and eventually YouTube playlist if people like it. Edit: to answer the question I believe in this particular demo I used KCF to track. For gestures I used a convolutional neural net which is both overkill and not the fastest solution, but part of the tutorial is machine learning.

Last year's CES was a surprisingly fruitful event for cord-cutting. At the tech industry's biggest trade show, companies like Tablo and Mohu announced radical new uses for over-the-air antennas, while bigger companies including Amazon and Roku made their own splashy announcements. The story was different at CES 2018. Several of those companies didn't show up at the trade show at all, while others only brought vague promises of future products with nothing to demo. Although this year's CES wasn't totally bereft of news and product launches, it wasn't the showcase for novel cord-cutting solutions that last year's show appeared to be.

I'm including noise-contrastive estimation, and GANs, but I'm worried I won't have enough to write (need about 3000 words). I've gone through most of the citations for these papers, so I'm thinking of just including GAN variants (like f-GAN, WGAN etc) to fill out any additional space. Anyone know of any other papers using a similar sort of technique? I'm aware of the part in ESLII also, just need to skim it again before I start writing.

The first full-length mainstream music album co-written with the help of artificial intelligence (AI) was released on 12 January and experts believe that the science behind it could lead to a whole new style of music composition. Popular music has always been fertile ground for technological innovation. From the electric guitar to the studio desk, laptops and the wah-wah pedal, music has the ability to absorb new inventions with ease. Now, the release of Hello World, the first entire studio album co-created by artists and AI could mark a watershed in music composition. Stemming from the FlowMachines project, funded by the EU's European Research Council, the album is the fruits of the labour of 15 artists, music producer Benoit Carré, aka Skygge, and creative software designed by computer scientist and AI expert François Pachet.