This week we discuss Intel’s latest deep learning acquisition, AI in the Olympics, image completion with deep learning in TensorFlow, and how you can win a free ticket to the O’Reilly AI Conference in New York City, plus a bunch more.
Here are the notes for this week’s podcast:
O’Reilly AI Conference Giveaway
I’m excited to be partnered with the O’Reilly Artificial Intelligence Conference, to give away a free ticket to the event, which will be held September 26 – 27, 2016 in New York City.
There are three ways to enter the giveaway:
1. (Preferred) Follow @twimlai on Twitter and retweet this tweet:
Win a FREE ticket to the @OReillyAI Conference. To enter, follow @twimlai + RT. https://t.co/ReYqwqp538 for details. pic.twitter.com/9pLrzHIX9d
— TWIML (@twimlai) August 15, 2016
2. Sign up for the TWIML&AI Newsletter and add a note “please enter me” in the comments field.
3. Use this site’s contact form to send me a message and use “AI contest” as the subject.
A winner will be chosen at random and announced on the 9/2 podcast. Ticket is non-transferrable. Good luck, and hope to see you in New York!
If you’d like to buy a ticket, register using the code PCTWIML for 20% off!
And don’t forget to get your free early access ebook: Mastering Feature Engineering
Intel Buys Deep Learning Startup Nervana
- Intel Buys a Startup to Catch Up in Deep Learning
- Deep Learning Chip Upstart Takes GPUs to Task
- Nvidia’s bet on deep learning and autonomous cars drives stock to record highs – MarketWatch
AI Bot Joins Team Washington Post at the Rio Olympics
Technology
- Fujitsu Software to Accelerate Deep Learning Workloads
- DetectNet: Deep Neural Network for Object Detection in DIGITS | Parallel Forall
- Google Research Blog: Meet Parsey’s Cousins: Syntax for 40 languages, plus new SyntaxNet capabilities
Image Completion with Deep Learning
- Image Completion with Deep Learning in TensorFlow
- bamos/dcgan-completion.tensorflow: Image Completion with Deep Learning in TensorFlow
- [1607.07539] Semantic Image Inpainting with Perceptual and Contextual Losses
- [1511.06434] Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
