As athletes and coaches begin to adopt IoT technology, 21st century fans are beginning to expect more from sporting events. The world of robotics and AI have so much to offer in terms of event management, so why not bring bots to stadiums the world over? Concierge robots could bring so much to the sports fan experience. Fans come from far and wide to attend major events, such as the World Cup, the Super Bowl, the Tour de France, and so on. They stay in hotels, hostels, and shared-homes.

The sun was sparkling on the Mediterranean Sea on the afternoon when a graduate student from my lab tossed our prize robot into the water for the first time. I watched nervously as our electronic creation sank beneath the waves. But the bot didn't falter: When we gave it the command to swim, it filled its expandable mantle with water, then jetted out the fluid to shoot forward. When we ordered it to crawl, it stiffened its eight floppy arms in sequence to push itself along the sandy bottom and over scattered rocks. And when we instructed it to explore a tight space beneath the dock, the robot inserted its soft body into the narrow gap without difficulty.

These claims are not ludicrous on their own. We've seen rapid advancements in technology over the past decades; we know computers are growing more powerful and more accessible by the month. Already in 2011, a supercomputer named Watson won a game of Jeopardy against two former champions, using a mixture of AI and all-important natural-language processing. The future is here and it may soon outstrip us. Kurzweil's timeline of the technological singularity is based on the law of accelerating returns, wherein the more powerful computers become, the faster they advance.

Our control model was a well established machine learning model using features that are known to work well. For text, the features are essentially normalized word counts (TF-IDF: term frequency / inverse document frequency vectors). For images, we use HOG features (histogram of oriented gradients). These features were fed into a logistic regression model for training and prediction. Our test model used custom collection; we fed data, trained a model, and made a prediction using transfer learning for text and image analysis under the covers.

Imagine a'Persuade' button for every critical moment in your life. One click to send the perfect Tinder pickup line. One click to convince your boss it's time for a raise. One click to persuade your significant other that you're actually right this time. In the last 10 years, we've seen an explosion of communication apps.

We are now free to share some of our perspectives on the company and its mission to accelerate the future with custom chips for deep learning. I'll share a recap of the Nervana story, from an investor's perspective, and try to explain why machine learning is of fundamental importance to every business over time. In short, I think the application of iterative algorithms (e.g., machine learning, directed evolution, generative design) to build complex systems is the most powerful advance in engineering since the Scientific Method. Machine learning allows us to build software solutions that exceed human understanding, and shows us how AI can innervate every industry. By crude analogy, Nervana is recapitulating the evolutionary history of the human brain within computing -- moving from the logical constructs of the reptilian brain to the cortical constructs of the human brain, with massive arrays of distributed memory and iterative learning algorithms. Not surprisingly, the founders integrated experiences in neuroscience, distributed computing, and networking -- a delightful mélange for tackling cognitive computing.

LONDON, ENGLAND - AUGUST 03: The Apple logo is displayed on the back of an iPhone on August 3, 2016 in London, England. Apple is continuing to make inroads into artificial intelligence. The Cupertino, Calif.-based tech behemoth bought Turi, a machine learning platform, for 200 million, according to sources at GeekWire. Apple would not confirm the move to USA TODAY, but said the company buys smaller technology companies "from time to time, and we generally do not discuss our purpose or plans." The Cupertino-based tech behomouth appears to be coming to terms with slumping demand for the iPhone by expanding into other markets, including artificial intelligence.

Algorithms, we all know them. If you're not technically inclined, you may tangentially know that they have something to do with coding. If you ARE technically inclined, you know that they are what makes our IT-based world go round. Well, according to one company, they can do a whole lot more. Zebra Medical Vision, an organization dedicated to creating machine learning diagnosis mechanisms, claims to be able to save over 500,000 Americans every year.

Around October 2015, Google announced it would be using artificial intelligence to help deliver its search results. This machine-learning AI system is called RankBrain. Since RankBrain uses machine-learning AI, it learns by itself, consuming web pages and search queries by the second with the intent of delivering the best and most relevant results to users. You need to understand that this is an addition to Google's algorithm and not an algorithm update such as Hummingbird, Penguin, etc. In fact, it is reported that RankBrain is now Google's third most important signal contributing to search queries and results.

Intel's acquisition yesterday of Nervana, a San Diego, CA-headquartered, two-year old machine learning specialist, signals the chip giant's wager that artificial intelligence (AI) will spark the next big...