It wasn't too long ago that the concept of carrying a sophisticated computer, camera and phone, all rolled into one gadget fitting in your pocket, was the stuff of science fiction. Now smartphones are everywhere and they're getting smarter all the time. Imagine when your phone will be able to diagnose most of your medical problems for you based on artificial intelligence (AI) in the cloud, saving you a trip to the doctor. The app could issue a diagnosis and a prescription, and your local pharmacy could 3D-print your medicine. This exciting new frontier is part of the Fourth Industrial Revolution (4IR), a period of rapid change driven by progress in science and technology.

Everybody is taking a stab at designing artificial intelligence processors, or electronic chips that could become the brains of computers that act as if they were humans. The latest to tackle the task of designing AI chips is Vinod Dham, a former Intel executive known as the "father of the Pentium." He has teamed up with some younger chip designers to build RAP chips, or real AI processors. At AlphaICs, the team is creating a coprocessor chip that can do agent-based artificial intelligence. These RAP chips could one day be deployed in computing devices and autonomous cars to make decisions at lightning speeds, or in data centers on a massive scale.

Nao Tokui – a visiting associate professor at Kyushu University in California and a CEO of Qosmo, an AI and music startup – has developed a neural-network-based system that collects about 20 seconds of any sound to produce a custom drum kit, and then automatically sequences rhythms using those utterances and noises. Any snippet of audio can be used as input, from your own voice to improvised percussion. In a video demo of the JavaScript-based code, Tokui gently slaps his cheek, and flicks a plastic bottle. The sounds are recorded by his computer's microphone, and fed into the software to generate a rhythm from the audio: Whatever's recorded by the code is automagically split and assigned to the instruments that make up the virtual drum kit, such as the kick drum, snare, hi hat, and tom-toms. After all this, the model strings together combinations of the kit's components into a sequence to produce a loop that you can bop your head to.

The future of Industry is all about keeping pace with technology and preparing the organization to extend investment support for the affluent class with service to traditional investment model. Considering the population to be supported, traditional investment support model would not be a feasible option. Moreover the affluent class also looks forward for technology support in decision making, nearly in every aspect of life. This makes Digital Stock Avatars or so called Artificial Intelligence platforms, extending investment support and execution, a reality. Exchanges globally are opening up to meet the expectations of the new age community with advancement towards Digital Avatars with Tech. In India, extending Algorithmic trading is still restricted to a few which is deterrent to the growth of the Investor community.

The nightmare scenario for computer security – artificial intelligence programs that can learn how to evade even the best defenses – may already have arrived. That warning from security researchers is driven home by a team from IBM Corp. who have used the artificial intelligence technique known as machine learning to build hacking programs that could slip past top-tier defensive measures. The group will unveil details of its experiment at the Black Hat security conference in Las Vegas on Wednesday. State-of-the-art defenses generally rely on examining what the attack software is doing, rather than the more commonplace technique of analyzing software code for danger signs. But the new genre of AI-driven programs can be trained to stay dormant until they reach a very specific target, making them exceptionally hard to stop.

For many years, the main goal of companies is to collect as much user data as possible. Dealing with all these and new incoming data quickly and effectively is impossible without intelligent systems. This is why companies desperately need to harness AI technologies to come to the top place among competitors – and the sooner the better. However, the challenge is that modern AI systems are "idiot savants" as Gurdeep Singh Pall of Microsoft put it in one of his talks. "They are great at what they do, but if you don't use them correctly, it's a disaster."

Meet "Dilly Plate," a little robot who just got a job as a waiter at Pizza Hut in Seoul, Korea. It (he?) started a two-week test run on Monday, according to the Korea Times, the first time a robot waiter has been allowed to cut loose on the floor of the country's dining industry, the company said. Developed by Woowa Brothers, a South Korean startup that also operates the food-delivery app Baedal Minjok ("Delivery Nation"), the little pizza server looks a bit like a moving table and is designed to makes short-distance deliveries within the restaurant. Dilly Plate's pizza-delivery services are the first step in commercializing the food bot developed by Woowa and researchers at Korea University, practicing its indoor food-delivery skills before moving into the great outdoors and making long-distance deliveries. Woowa Brothers, which back in 2014 got $36 million in funding in a round lead by Goldman Sachs, hopes to develop low-cost robots that could open the delivery market to include picking up items at the grocery story, taking out recyclables, making pharmacy runs, and more, according to an interview with Korea Joong Ang Daily.

Companies are using AI to prevent and detect everything from routine employee theft to insider trading. Many banks and large corporations employ artificial intelligence to detect and prevent fraud and money laundering. Social media companies use machine learning to block illicit content such as child pornography. Businesses are constantly experimenting with new ways to use artificial intelligence for better risk management and faster, more responsive fraud detection -- and even to predict and prevent crimes. While today's basic technology is not necessarily revolutionary, the algorithms it uses and the results they can produce are.

If policymaking is never easy, and military policymaking is very difficult, it stands to reason that space military policymaking is basically impossible. Yet today, in a speech at the Pentagon, Vice President Mike Pence announced the formation of a sixth branch of the US armed services: a SPACE FORCE! But can that really happen? Well, let's proceed with the go/no-go. "The time has come to establish the United States Space Force," Pence said in his speech, asking for $8 billion to build out the idea.

Finding the diameter of a dataset in multidimensional Euclidean space is a well-established problem, with well-known algorithms. However, most of the algorithms found in the literature do not scale well with large values of data dimension, so the time complexity grows exponentially in most cases, which makes these algorithms impractical. Therefore, we implemented 4 simple greedy algorithms to be used for approximating the diameter of a multidimensional dataset; these are based on minimum/maximum l2 norms, hill climbing search, Tabu search and Beam search approaches, respectively. The time complexity of the implemented algorithms is near-linear, as they scale near-linearly with data size and its dimensions. The results of the experiments (conducted on different machine learning data sets) prove the efficiency of the implemented algorithms and can therefore be recommended for finding the diameter to be used by different machine learning applications when needed.