2017 The State of Data Science & Machine Learning
“This year, for the first time, we conducted an industry-wide survey to establish a comprehensive view of the state of data science and machine learning. We received over 16,000 responses and learned a ton about who is working with data, what’s happening at the cutting edge of machine learning across industries, and how new data scientists can best break into the field. The below report shares some of our key findings and includes interactive visualizations so you can easily cut the data to find out exactly what you want to know.”
GOOGLE’S AI WIZARD UNVEILS A NEW TWIST ON NEURAL NETWORKS
Sara Sabour, Nicholas Frosst, Geoffrey Hinton have released two research papers (Dynamic Routing Between Capsulesand “Matrix capsules with EM routing”)
Understanding Hinton’s Capsule Networks. Part I: Intuition.
“In this post, I will explain why this new architecture is so important, as well as intuition behind it. In the following posts I will dive into technical details.”
AlphaGo Zero — How and Why it Works
DeepMind’s AlphaGo made waves when it became the first AI to beat a top human Go player in March of 2016. This version of AlphaGo — AlphaGo Lee — used a large set of Go games from the best players in the world during its training process. A new paper was released a few days ago detailing a new neural net — -AlphaGo Zero — -that does not need humans to show it how to play Go. Not only does it outperform all previous Go players, human or machine, it does so after only three days of training time. This article will explain how and why it works.
Everything you need to know about Neural Networks
Understanding what is Artificial Intelligence and how does Machine Learning and Deep Learning powers it is an overwhelming experience. We are a group of self-taught engineers who have gone through that experience and we are sharing (in blogs) our understanding and what helped us in simplified form, so that anyone who is new to this field can easily start making sense of the technicalities of this technology.
Can a Machine Be Conscious?
Three neuroscientists argue that the architecture of consciousness in the human brain can help create artificial consciousness.
Do We Need Brain Implants to Keep Up with Robots?
Pundits have been fretting a lot lately about robots leaving humans behind, taking our jobs and possibly a lot more, as in The Matrix and Terminator films. Christof Koch, my go-to source for brain science for 25 years, has proposed a solution. To keep up with machines, we should boost our cognitive powers with brain implants.
Google Colaboratory — Simplifying Data Science Workflow
Google has recently made public its internal tool for data science and machine learning workflow called Colaboratory. Although it is very similar to Jupyter Notebook upon top of which it is built, the real value comes from the free computing power that this service currently offers. Collaboration feature, similar to that of Google Docs, allows small teams to work closely together and quickly build small prototypes. In general, this tool closely aligns with the Google’s vision of becoming an “AI-First” company.
TensorFlow Eager Execution: A new imperative interface
Eager execution is an imperative, define-by-run interface where operations are executed immediately as they are called from Python. This is how frameworks such as PyTorch or Chainer work. Now you can use the same style in Tensorflow.
A List of Chip/IP for Deep Learning (keep updating)
Machine Learning, especially Deep Learning technology is driving the evolution of artificial intelligence (AI). At the beginning, deep learning has primarily been a software play. Start from the year 2016, the need for more efficient hardware acceleration of AI/ML/DL was recognized in academia and industry. This year, we saw more and more players, including world’s top semiconductor companies as well as a number of startups, even tech giants Google, have jumped into the race. I believe that it could be very interesting to look at them together. So, I build this list of AI/ML/DL ICs and IPs on Github and keep updating. If you have any suggestion or new information, please let me know.
Sony reboots Aibo with AI and extra kawaii
Sony claims Aibo’s new adaptive behavior includes being able to actively seek out its owners; detect words of praise; smiles; head and back scratches; petting, and more. The Aibo robot costs 198,000 JPY (~$1,735) but you also need a subscription plan to connect to the cloud service that powers Aibo’s AI.
Earth on AWS Datasets
A collection of geospatial datasets available on AWS. These include satellite images, weather radar data, street map data, points of interest, and much more. Cloud Credits for Earth Observation Research are also available.
