From consulting in machine learning, healthcare modeling, 6 years on Wall Street in the financial industry, and 4 years at Microsoft, I feel like I've seen it all. And this has opened my eyes to the huge gap in educational material on applied data science. It just ain't real'til it reaches your customer's plate I am a startup advisor and available for speaking engagements with companies and schools on topics around building and motivating data science teams, and all things applied machine learning.

In today's post, we would only run the single person pose estimation using OpenCV. We would just be showing the confidence maps now to show the keypoints. In order to keep this post simple, we shall be showing how to connect multiple person keypoints using Pose affinity maps in a separate post next week. We would be using the pretrained model trained by the OpenPose team using Caffe on MPI dataset. This dataset has 15 keypoints to identify various points in human body. We also define the pose pairs which define the limbs. This is used to create the limbs which connect the keypoints and Pose affinity maps are used to predict the limbs.

Philippe Esling received a B.Sc in mathematics and computer science in 2007, a M.Sc in acoustics and signal processing in 2009 and a PhD on data mining and machine learning in 2012. He was a post-doctoral fellow in the Department of Genetics and Evolution at the University of Geneva in 2012. He is now an associate professor with tenure at Ircam laboratory and Sorbonne Université since 2013. In this short time span, he authored and co-authored over 20 peer-reviewed journal papers in prestigious journals. He received a young researcher award for his work in audio querying in 2011, a PhD award for his work in multiobjective time series data mining.

YOUNGSTOWN, Ohio – Youngstown State University will host a forum Saturday discussing the impact of artificial intelligence on work and education. The forum will be held 10:30 a.m. to 4:30 p.m. at the Youngstown Historical Center of Labor and Industry. It is free and open to the public. Among the presenters are David Staley, director of the Humanities Institute and a professor of history, design and educational studies at Ohio State University, and Sundar Vedantham, director of software development in Intel Corp.'s datacenter group. Sponsored by the YSU department of computer science and the Northeast Ohio chapter of the Association for Computing Machining, the forum will delve into how AI will impact workplaces, workers' relationships with coworkers and work environments, the economic, societal and ethical concerns of AI, and how AI could create a "workless" future. Published by The Business Journal, Youngstown, Ohio.

When you think of AI or machine learning you may draw up images of AlphaZero or even some science fiction reference such as HAL-9000 from 2001: A Space Odyssey. However, the true forefather, who set the stage for all of this, was the great Arthur Samuel. Samuel was a computer scientist, visionary, and pioneer, who wrote the first checkers program for the IBM 701 in the early 1950s. His program, "Samuel's Checkers Program", was first shown to the general public on TV on February 24th, 1956, and the impact was so powerful that IBM stock went up 15 points overnight (a huge jump at that time). This program also helped set the stage for all the modern chess programs we have come to know so well, with features like look-ahead, an evaluation function, and a mini-max search that he would later develop into alpha-beta pruning.

IBM has recently launched its inaugural IBM Women Leaders in A.I. in recognition of women advancing their company's journey to artificial intelligence across diverse industries around the globe--from California's County of Sonoma to South Africa's NedBank. There is an opportunity for women to not only contribute to Artificial Intelligence (A.I.) – one of the modern era's most important technologies – but help lead in its application across various industries around the globe. This position of influence is not solely to appease a diversity mandate or to stand guard against algorithmic biases. Women can stand up as one of the integral factors in bringing transparent, inclusive and trusted A.I. to business. Among those recognized on IBM's list of Women Leaders in A.I., we recognized a common success factor - shared a propensity for bringing stakeholders together for effective work.

Researchers at the OpenAI artificial intelligence laboratory developed bots that trained themselves to cooperate by playing hide-and-seek. Scientists at the OpenAI artificial intelligence (AI) laboratory have developed AI bots that trained themselves to cooperate by playing hide-and-seek. The team had the bots play the game in a simulated environment containing fixed walls and movable boxes; each bot had its own perspective of its surroundings, and could not directly communicate with other bots. The bots that hid quickly deduced the fastest way to fool seekers was to find objects in the environment with which to conceal themselves; the seekers learned they could manipulate objects like ramps to overcome obstacles like walls. The bots learned that cooperation--like passing objects to each other or co-building a hideout--was the quickest way to win.

Microsoft announced a $1 billion investment in OpenAI, a lab co-founded by Elon Musk to develop "artificial general intelligence." The investment is the start of a long-term partnership between the two organizations. OpenAI will ensure its services work on Microsoft's Azure cloud platform, and the companies will collaborate on new supercomputers. OpenAI's stated mission is to develop "artificial general intelligence," or AGI. In layman's terms, AGI is AI that can think like a human (possibly even better) while carrying out complex tasks autonomously. Whether or not an AGI would immediately decide to incinerate humanity a la Skynet remains to be seen, but OpenAI at least claims its artificial intelligence would be safe and beneficial for the human race.

Artificial intelligence is learning how to predict El Niño climate cycles. The hope is that the technology could be used to improve climate predictions and give policy-makers more time to prepare. El Niño can cause severe weather and devastating damage. A phase of the El Niño-Southern Oscillation, it occurs when water warms over the tropical Pacific Ocean, shifting east and increasing rainfall and cyclones over the Americas while pulling rain away from Indonesia and Australia. Strong El Niño events are associated with intense storms and flooding in some areas, and drought and fires in others.

A tuna-inspired robot can wriggle just as fast as real fish and swim faster than most other robots of its type. This "Tunabot" could help us learn how fish use their fins and may someday be used for underwater surveillance. Hilary Bart-Smith at the University of Virginia and her colleagues built Tunabot from 3D-printed steel and resin, covered in stretchy plastic skin. It is designed to mimic an adolescent tuna, but without any fins other than the tail, and is about 25 centimetres long. The team chose to model the robot after a tuna because the fish can swim extremely fast with high energy efficiency.