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Or, if you put them all together, my experience of the NIPS conference can be summarized as the image below. Read along if you prefer words, details and creative bot like status kitahara of AI. Turns out, machine learning researchers must really like cake, sometimes with extra cherries oh RL! I was there, still not sure what they do, but impressive team, private residence in the embassy district and an on-call police force for when bot like status kitahara parties get too rowdy the team need their beauty sleep!

So much inspiration, energy and positivity from the AI community amongst the chaotic frenzy of invited talks from industry titans, hundreds of posters, artistic demos, company parties, workshops and satellite events for the almost 6, machine learning researchers assembled from all over the world. Read on for my NIPS week highlights. I only managed to catch the final few presentations, but it was a delight to hear what was happening industryside with presentations from Aaron van den Oord on the Wavenet audio generation model, Oriel Nieto on music recommendation models at Pandora and Colin Raffel on using the Lakh MIDI dataset.

In its 11th year, the WIML workshop welcomed participants to its event on Monday, featuring invited speakers, contributed talks and mentorship roundtables on academic and career topics. I was invited to mentor on music applications and building your professional brand; we had some fascinating discussions on separating professional and personal lives online as well as figuring out what our dream applications of AI in music would be music tutors, music-to-image and improved recommendation systems were all mentioned.

Judging by the number of women-specific sponsor events hosted on Sunday before the workshop, it is clear that companies are trying to address the gender balance.

Monday, Tuesday and Wednesday evenings are reserved for posters with on display every day and only 3. Alongside the posters, there were 10 demos each on Tuesday and Wednesday allowing you to play music, figure out your personality, generate text interactively and turn frowns into smiles. They brought the research to life and were great fun to play around with. Some favourites are listed below. What was particularly entertaining here is watching the generated text bot like status kitahara as you moved bot like status kitahara hand across the screen to increase the presence of the style of the Bible, Trump or the Linux source code.

How can we understand and use the structured latent space of generative networks? This uses a neural network to remove or add smiles to bot like status kitahara photograph.

Bot like status kitahara short video is of Magenta playing the bassline with Sageev Oore playing over it. Winner of the best demo award. Generative Adversarial Networks GANs were one of the hottest trends this year, with a dedicated tutorial from Ian Goodfellow on Monday, a workshop on Adversarial Training on Friday and pop-up appearances pretty much anywhere and everywhere else.

What is a bug in the quest for realistic image generation can be a feature in creative explorations. Get bot like status kitahara touch if you spot some cool creative uses of GANs.

During Friday lunch, I was pleasantly surprised to find a workshop on public engagement. Sabine Hauert gave an overview of the public opinion insights gained from the survey conducted by The Royal Society earlier this year. Meanwhile, Zoubin Ghahramani presented an overview of the main research and public opinion challenges facing the machine learning community. She sure knows how to bot like status kitahara her thoughts into the appropriate format for a predominantly scientist audience I have never heard the term story algorithm during my arts education!

The website explains the term as:. Therefore, this workshop covered everything from music and recipe generation to drug modelling. Ross is also the writer of writer best job title ever?

Ever since the Leon Gatys et al paper on A Neural Algorithm of Artistic Style in Augustthe so-called neural style transfer has been growing in popularity and exploded this summer with the launch of the mobile app Prisma. The discussion continued on twitter. With that, I sign off. What was your experience of NIPS? What are bot like status kitahara most bot like status kitahara and unusual applications, papers and projects that you saw? Anything major I missed?

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