WaveNets are able to generate speech which mimics any human voice and which sounds more natural than the best existing Text-to-Speech systems, reducing the gap with human performance by over 50%. It directly modells the raw waveform of the audio signal, one sample at a time. As well as yielding more natural-sounding speech WaveNets open up a lot of possibilities for TTS, music generation and audio modelling in general.
Perfectly open communities always go sour. You need filters. Every functional community has them. And that’s where machine learning comes in. Chris Nicholson explains in this Tech Crunch article.”Deep learning is setting new records in accuracy for a lot of difficult problems and it needs to focus on fixing the online platforms bringing us news.
In this paper they investigate conditional adversarial networks as a general-purpose solution to image-to-image translation problems. These networks not only learn the mapping from input image to output image, but also learn a loss function to train this mapping.
As a community, we no longer hand-engineer our mapping functions, and this work suggests we can achieve reasonable results without hand-engineering our loss functions either.
The new computer has been dubbed ABCI, an acronym for AI Bridging Cloud Infrastructure. Bidding for the project has begun and will close on Dec. 8.
The supercomputer will be made available for a fee to Japan’s corporations, who now outsource data crunching to foreign firms such as Google and Microsoft, Sekiguchi to amongst other things conduct Deep Learning
Daniel Miessler an information security professional believes “Descent with modification combined with natural selection is arguably the most powerful natural force we’ve ever encountered. If we can figure out how to model these appropriately, and we can leverage our scaling technologies the way we have with Machine Learning” He sets out the case in this blog that Evolutionary Algorithms will surprise everyone with the impact they’ll bring.