Donald Trump's speeches are nothing like that, according to Brad Hayes, a MIT scientist who programmed a Twitter bot to sound like him. Called DeepDrumpf, it uses an artificial intelligence algorithm based on Trump's language in hundreds of hours of debate transcripts. Hayes told Tech Insider he has learned a lot over the last few weeks about how Trump talks. Here is how he describes Trump's language, which differs dramatically from past presidential candidates. Trump often uses short, imperative sentences, Hayes says.

Latency to end-users and regulatory requirements push large companies to build data centers all around the world. The resulting data is "born" geographically distributed. On the other hand, many machine learning applications require a global view of such data in order to achieve the best results. These types of applications form a new class of learning problems, which we call Geo-Distributed Machine Learning (GDML). Such applications need to cope with: 1) scarce and expensive cross-data center bandwidth, and 2) growing privacy concerns that are pushing for stricter data sovereignty regulations. Current solutions to learning from geo-distributed data sources revolve around the idea of first centralizing the data in one data center, and then training locally. As machine learning algorithms are communication-intensive, the cost of centralizing the data is thought to be offset by the lower cost of intra-data center communication during training. In this work, we show that the current centralized practice can be far from optimal, and propose a system for doing geo-distributed training. Furthermore, we argue that the geo-distributed approach is structurally more amenable to dealing with regulatory constraints, as raw data never leaves the source data center. Our empirical evaluation on three real datasets confirms the general validity of our approach, and shows that GDML is not only possible but also advisable in many scenarios.

IBM is about to deliver the foundation of a brain-inspired supercomputer to Lawrence Livermore National Laboratory, one of the federal government's top research institutions. The delivery is one small "blade" within a server rack with 16 chips, dubbed TrueNorth, and is modeled after the way the human brain functions. Silicon Valley is awash in optimism about artificial intelligence, largely based on the progress that deep learning neural networks are making in solving big problems. Companies from Google to Nvidia are hoping they'll provide the AI smarts for self-driving cars and other tough problems. It is within this environment that IBM has been pursuing solutions in brain-inspired supercomputers. The main benefit is that such chips may be able to operate at lower frequencies and get much more work done on a much smaller amount of power.

Microsoft has created a new chat bot to "learn" from the internet… but she picked up a lot of bad habits. The tech company announced the launch of Tay this week, an artificial intelligence bot that is learning to talk like millennials by analysing conversations on Twitter, Facebook and the internet. The company's optimistic techies explained: "Tay is an artificial intelligent chat bot developed by Microsoft's Technology and Research and Bing teams to experiment with and conduct research on conversational understanding. "Tay is designed to engage and entertain people where they connect with each other online through casual and playful conversation. The more you chat with Tay the smarter she gets."

A government-led effort to develop commercial guidelines for face-recognition technology is moving forward, and it has privacy advocates red in the face. The National Telecommunications and Information Administration, an agency within the U.S. Commerce Department, held a meeting in Washington Tuesday to consider a set of "best practices" for collecting and storing facial data and to discuss how face-recognition technology might apply to the Obama administration's so-called Consumer Privacy Bill of Rights publicized in 2012. The meeting is part of an ongoing process being billed as a "multistakeholder" effort to develop an enforceable code of conduct for emerging biometric technologies, but privacy groups say their warnings about potential privacy abuses are not being heard. Instead, they say the process has been hijacked by technology industry interests intent on harnessing sensitive private data for monetary gain. "Lobbyists craft purposefully vague proposals without any real safeguards for biometric data," Jeff Chester, executive director of the Center for Digital Democracy, wrote in a blog post Tuesday.

Economic experts are trying to figure out a question that just two decades ago seemed ridiculous: If 90 percent of human jobs are replaced by robots in the next 50 years -- something now considered plausible -- is capitalism still the ideal economic system to champion? No one is certain about the answer, but the question is making everyone nervous -- and forcing people to dig deep inside themselves to discover the kind of future they want. After America beat Russia in the Cold War, most of the world generally considered capitalism to be the hands-down best system on which to base economies and democracies. For decades, few doubted capitalism's merit, which was made stronger by thriving globalization and a skyrocketing world net worth. In 1989 -- when the Berlin Wall fell -- the world had only 198 billionaires.

One of the huge drawbacks of modern technology is that it fills the air around us with radio signals. From your kitchen radio to your LTE-enabled smartphone, all of these devices use radio waves to communicate. Unfortunately, there is only a certain amount of radio frequencies that can be used. DARPA (Defense Advanced Research Projects Agency) is looking for a way around this problem, and wants teams to develop an artificially intelligent system that will control what devices use what radio waves and when. Basically, instead of forcing devices to make use of narrow frequency bands when the spectrum gets congested, DARPA wants devices to negotiate sharing frequencies when they need them.

Economic experts are trying to figure out a question that just two decades ago seemed ridiculous: If 90 percent of human jobs are replaced by robots in the next 50 years -- something now considered plausible -- is capitalism still the ideal economic system to champion? No one is certain about the answer, but the question is making everyone nervous -- and forcing people to dig deep inside themselves to discover the kind of future they want. After America beat Russia in the Cold War, most of the world generally considered capitalism to be the hands-down best system on which to base economies and democracies. For decades, few doubted capitalism's merit, which was made stronger by thriving globalization and a skyrocketing world net worth. In 1989 -- when the Berlin Wall fell -- the world had only 198 billionaires.

Microsoft launched an artificial intelligence chat "bot" last week, thinking this would be a way to show off its AI programming skills. Unfortunately, within 24 hours Tay had turned from a naive young AI into a rude, anti-Semitic pro-Nazi jerk. Also: Taliban kills 76 Christians in Pakistan on Easter; LGBTQ activists upset at North Carolina; Disney, Marvel and the NFL bully Georgia; CIA-armed Syrian rebels shooting at Pentagon-armed rebels; more evidence for Planet 9; and Mexicans celebrate Easter by burning Donald Trump in effigy.

The platform will be the integral part of Image Search Engine for Image Referral Network and Image Ad Network, to automate generation and placement of highly-relevant targeted ads based on images in a large scale for the first time in the industry. ZAC's AI Discovery platform can also be used for other types of images, data, or objects, e.g., clothing, purse, accessories, medical images, satellite images, and biometrics. ZAC has an impressive team of scientists and developers. The software development is headed by Saied Tadayon, a veteran software developer and scientist, who got PhD from Cornell at age 23. One of ZAC's inventors is Prof. Lotfi A. Zadeh ("The Father of Fuzzy Logic"), a pioneer computer scientist at U.C. Berkeley.