For the image manipulation I used the Python Imaging Library (PIL).

Regardless of the analysis of smartphone market share, Office and cloud revenues, quarterly profits, gaming consoles sales, Surface hardware, or search engine relevance, Microsoft remains a large company employing diversified and talented individuals. Often, the individuals under Microsoft's employ do double duty as the brilliant minds creating projects and industries for the company while also pioneering advancements, groundbreaking achievements, and technologies in fields outside of their immediate obligations. Recently, Yuval Peres and Robert Schapire joined the long list of Microsoft employees and researchers who have been recognized by their peers for their achievements in their respective fields. Peres and Schapire's are receiving perhaps the highest honor in science and research by being elected to the Nation Academy of Sciences. Peres and Schapire's recognition will see them become part of new 84 members and 21 foreign associate groups that will be joining the National Academy this year.

As you read this, some 100 billion neurons are transmitting information through electrical and chemical signals via synapses in your brain. Given the central role these cells play in neurological functioning, it's perhaps not surprising they typically hog the limelight -- after all, the signals they transmit lie at the heart of human behavior, from the simplest of movements to the most complex of thoughts. It's worth noting, however, that complimentary cells called astrocytes actually outnumber neurons in the brain. Unfortunately, these star-shaped cells have largely been ignored in neurological research because they don't fire electrical impulses in the same way that neurons do. Yukiko Goda of the Riken Brain Science Institute in Saitama is helping to correct this. Goda, who was born in Osaka, went to high school in Toronto after her father was transferred to Canada for work.

In the fourth issue of this monthly digest series you can find out how Qualcomm is bringing deep learning and AI to smart devices, why Daimler sent self-driving trucks all across Europe, how to imitate Rembrandt's best work with the help of deep learning, and much more. From the Smithsonian comes news--and a must-see fascinating video--about a painting created using data from more than 168,000 fragments of Rembrandt's work, trained to paint in Rembrandt's signature style. Over the course of 18 months, a group of engineers, Rembrandt experts and data scientists analyzed 346 of Rembrandt's works, then trained a deep learning engine to "paint" in the master's signature style. In order to stay true to Rembrandt's art, the team decided to flex the engine's muscles on a portrait. They analyzed the demographics of the people Rembrandt painted over his lifetime and determined that it should paint a Caucasian male between 30 and 40 years of age, complete with black clothes, a white collar and hat, and facial hair.

Today our focus has been on KPIs, ERP, WMS, TMS, YMS, EDI, The Cloud, S and OP, 3 D Printing, IoT, IoE, Drones: Same Hour/Day/Time Delivery to Customers, Cyber Security, Theft, Government Regulations, E-Commerce, Omni-Channel, Modeling/Simulation, Risk Management, Tracking, Traceability, Re-shoring, Robotics, et al, but…what about Artificial Intelligence or AI technologies? AI is a controversy of deep, lasting dimensions. Will machines learn to think like humans…and then outthink us? The application of AI technologies has created the ability to understand, store and use product information in an entirely new way. AI technologies allow you to understand the underlying grammatical structure, the product DNA, used to build each product, together with all natural variations that potentially exist.

Nvidia's (NVDA) AI technology with Facebook (FB), Alphabet (GOOGL) and Microsoft (MSFT) is powering "superhuman" levels of inference, or artificial intelligence, Nvidia CEO Jen-Hsun Huang said Thursday, after the Tesla Motors (TSLA) partner blasted Q1 views on record deep-learning sales. "The truth is that nobody really knows how big this deep-learning market is going to be," Huang said on the company's earnings conference call. He referred specifically to gains that customer Microsoft was making with AI and deep learning. "The work that recently was done at Microsoft Research, they've achieved superhuman levels of inferencing … of image recognition and voice recognition that's really kind of hard to imagine," he said, "and these networks are now huge." On the stock market today, Nvidia stock rocketed 15% and hit an all-time high of 41.

The astrophysicist and author Janna Levin has two main offices: One at Barnard College of Columbia University, where she is a professor, and a studio space at Pioneer Works, a "center for art and innovation" in Brooklyn where Levin works alongside artists and musicians in an ever-expanding role as director of sciences. Beneath the rafters on the third floor of the former ironworks factory that now houses Pioneer Works, her studio is decorated (with props from a film set) like a speakeasy. There's a bar lined with stools, a piano, a trumpet and, on the wall that serves as Levin's blackboard, a drink rail underlining a mathematical description of a black hole spinning in a magnetic field. Whether Levin is writing words or equations, she finds inspiration just outside her gallery window, where a giant cloth-and-paper tree trunk hangs from the ceiling almost to the factory floor three stories below. "Science is just an absolutely intrinsic part of culture," said Levin, who runs a residency program for scientists, holds informal "office hours" for the artists and other residents, and hosts Scientific Controversies--a discussion series with a disco vibe that attracts standing-room-only crowds. "We don't see it as different." She conducted research on the question of whether the universe is finite or infinite, then penned a book about her life and this work (written as letters to her mother) at the start of her physics career. She has also studied the limits of knowledge, ideas that found their way into her award-winning novel about the mathematicians Alan Turing and Kurt Gödel.

The use of machine learning has allowed us to solve many of our problems. It can allow us to effectively manage bandwidth, possibly predict solar flares, automate the rooting out of weeds, and so much more. The ability to learn and experience the world much as humans do allows our machines to be better at the tasks we give them. Sometimes, they're even better than humans are. US chemists have created a machine-learning algorithm that studies successful and failed experiments in order to beat humans at predicting ways to make crystals.

You must understand your data in order to get the best results. In this post you will discover 7 recipes that you can use in Python to learn more about your machine learning data. Understand Your Machine Learning Data With Descriptive Statistics in Python Photo by passer-by, some rights reserved. This section lists 7 recipes that you can use to better understand your machine learning data. Each recipe is demonstrated by loading the Pima Indians Diabetes classification dataset from the UCI Machine Learning repository.

Algorithms help us to choose which films to watch, which music to stream and which literature to read. But what if algorithms went beyond their jobs as mediators of human culture and started to create culture themselves? In 1950 English mathematician and computer scientist Alan Turing published a paper, "Computing Machinery and Intelligence," which starts off by proposing a thought experiment that he called the "Imitation Game." In one room is a human "interrogator" and in another room a man and a woman. The goal of the game is for the interrogator to figure out which of the unknown hidden interlocutors is the man and which is the woman.