Artificial Intelligence (AI) made leapfrogs of development and saw broader adoption across industry verticals when it introduced machine learning (ML). ML helps in learning the behavior of an entity using patterns detection and interpretation methods. However, despite its unlimited potential, the conundrum lies in how machine learning algorithms arrive at a decision in the first place. Questions like, "What are the processes they adopted, and at what speed? How did they make such autonomous decision?"

If you think neural nets are black boxes, you're certainly not alone. While they may not be as interpretable as something like a random forest (at least not yet), we can still understand how they process data to arrive at their predictions. In this post we'll do just that as we build our own network from scratch, starting with logistic regression. If you think neural nets are black boxes, you're certainly not alone. While they may not be as interpretable as something like a random forest (at least not yet), we can still understand how they process data to arrive at their predictions.

Microsoft has just provided two new nuggets on information from Flight Simulator, which is about to make its descent onto gamers' systems on August 18 -- now, also on Steam. VIEW GALLERY – 10 IMAGES In a new update, Microsoft explained that Flight Simulator "heralds a new era of data-driven flight simulation". In the update, Microsoft continued: "One of the exciting implications of this is that the data that makes up the world is always improving, and players can look forward to a simulator that evolves over time".The post continued: "Thanks to our partnership with Bing, players will enjoy new, even better terrain, and an ever evolving, machine learning-fueled simulator that grows over time".Microsoft finished up the update on Flight Simulator, adding: "We have so much ahead for Microsoft Flight Simulator, but even on day one simmers will get highly detailed aircraft, a new checklist system, live air traffic, dynamic weather, new aerodynamic modeling, as well as all the many other features we shared in our launch date announcement, all within a beautifully crafted and rendered world. Whether you are new to flight simulation or an aviation pro, the sky is calling in Microsoft Flight Simulator".There will be 3 different …

To explore all newsletters, click here. By signing, you agree to the terms of service and privacy policy. Self-driving cars, single-pilot commercial planes, robotic soldiers, and widespread gene editing may still be things of the future, but a new research center in San Antonio is working to bring these and other artificial intelligence innovations to life. The University of Texas at San Antonio officially launched its newest research center, the UTSA Matrix AI Consortium, on Thursday morning via a livestream kickoff event. The consortium will bring together experts studying artificial intelligence to expand the use and deployment of AI. "This initiative is a concerted effort to promote AI innovation, something I'm a big fan about these days," UTSA President Taylor Eighmy said.

For a few seconds, it seems real. Then, on the horizon, the landscape gives way to rugged coastline, and, as the plane flies closer, we glimpse the rippling waves glinting in the evening sun. In real life, I have not seen the ocean for five months and, although I'm just sitting in my kitchen watching a virtual presentation of a video game, I feel a surge of emotion. When the latest instalment in Microsoft's decades-old Flight Simulator series was first shown at the E3 video game event last year, it drew gasps from the audience. Using two petabytes of geographic data culled from Bing Maps, together with cutting-edge, machine learning algorithms running on the company's Azure cloud computing network, the game presents a near-photorealistic depiction of the entire planet.

This article is part of our reviews of AI research papers, a series of posts that explore the latest findings in artificial intelligence. Last November, Apple ran into trouble after customers pointed out on Twitter that its credit card service was discriminating against women. David Heinemeir Hansson, the creator of Ruby on Rails, called Apple Card a sexist program. "Apple's black box algorithm thinks I deserve 20x the credit limit [my wife] does," he tweeted. The @AppleCard is such a fucking sexist program.

Deep learning systems are revolutionizing technology around us, from voice recognition that pairs you with your phone to autonomous vehicles that are increasingly able to see and recognize obstacles ahead. But much of this success involves trial and error when it comes to the deep learning networks themselves. A group of MIT researchers recently reviewed their contributions to a better theoretical understanding of deep learning networks, providing direction for the field moving forward. "Deep learning was in some ways an accidental discovery," explains Tommy Poggio, investigator at the McGovern Institute for Brain Research, director of the Center for Brains, Minds, and Machines (CBMM), and the Eugene McDermott Professor in Brain and Cognitive Sciences. "We still do not understand why it works. A theoretical framework is taking form, and I believe that we are now close to a satisfactory theory. It is time to stand back and review recent insights."

Deep learning systems are revolutionizing technology around us, from voice recognition that pairs you with your phone to autonomous vehicles that are increasingly able to see and recognize obstacles ahead. But much of this success involves trial and error when it comes to the deep learning networks themselves. A group of MIT researchers recently reviewed their contributions to a better theoretical understanding of deep learning networks, providing direction for the field moving forward. "Deep learning was in some ways an accidental discovery," explains Tommy Poggio, investigator at the McGovern Institute for Brain Research, director of the Center for Brains, Minds, and Machines (CBMM), and the Eugene McDermott Professor in Brain and Cognitive Sciences. "We still do not understand why it works. A theoretical framework is taking form, and I believe that we are now close to a satisfactory theory. It is time to stand back and review recent insights."

With eight successful Mars landings, NASA is upping the ante with its newest rover. The spacecraft Perseverance -- set for liftoff this week -- is NASA's biggest and brainiest Martian rover yet. It sports the latest landing tech, plus the most cameras and microphones ever assembled to capture the sights and sounds of Mars. Its super-sanitized sample return tubes -- for rocks that could hold evidence of past Martian life -- are the cleanest items ever bound for space. A helicopter is even tagging along for an otherworldly test flight.

Previously used to tackle hospital acquired infections, the machines move through the airport terminals disinfecting high risk touch points like bathrooms and lifts.