A research team at Korea's Daegu Gyeongbuk Institute of Science and Technology (DGIST) succeeded in analyzing big data up to 1,000 times faster than existing technology by using GPU-based'GMiner' technology. The finding of big data pattern analysis is expected to be utilized in various industries including the finance and IT sectors. An international team of researchers, led by Professor Min-Soo Kim from Department of Information and Communication Engineering developed'GMiner' technology that can analyze big data patterns at high speed. GMiner technology exhibits performance up to 1,000 times faster than the world's current best pattern mining technology. Pattern mining technology identifies all important patterns that appear repeatedly in the big data of various fields such as buying goods at mega-marts, banking transactions, network packets, and social networks.

Michio Kaku: People often ask me the question, "In the era of AI what jobs and what skills will I need?" Well, first of all let's take a look at the first era of space exploration the 1960s. There was a crash program back then to miniaturize the transistor. The Russian astronauts, they're also very tiny because they have to fit inside the nose cone of a missile, and we scientists were given the mission to miniaturize transistors as far as possible. Now, as a consequence of that, we have what is called the Internet age today.

Digital transformation is no longer an "if" but a "when" for enterprises across both public and private sector. The promise of greater efficiency, customer-centric products and services, rapid response to changing regulatory or economic requirements – and the chance to compete with disruptive start-ups percolating every sector of the economy can no longer be overlooked. The challenge is how to get started and get the runs on the board that build innovation momentum. Google Cloud's Nigel Watson believes machine learning and artificial intelligence (AI) offer the most straightforward way to demonstrate what digital transformation can deliver. Watson is Head of Cloud Technology Partners, Japan and Asia Pacific for Google Cloud.

Tune in to this extraordinary edition of S.M.A.C. Talk Technology Podcast in which we examine how to become a disruptor (not disrupted!) in every industry Innovation itself isn't the entire challenge – pockets of innovation can be found in most any company, from the wildly successful to those that have failed spectacularly. The real challenge is being able to innovate at scale across an entire organization, all while creating a mechanism for those innovations to be shared, sustained, and to drive value back into the core of the business. In this series of podcasts, we'll explore how you can make that happen in your business. Listen in on these talks from your fellow innovators to discover how to embrace digital transformation and become a disruptor in your industry. More than 3,100 global executives took part in the most comprehensive global study of its kind, conducted by Oxford Economics.

If you were inventing the farm today, why would you put it outside, on a giant plot of land? OK, there's the sunlight thing, but then you get droughts and frosts and plant-munching insects that have to be battled with harmful pesticides. And because outdoor farms need so much acreage, they're usually far from most of their customers -- which means that by the time a tomato gets to you in a city, it tastes like a baseball. But now, upstarts such as Bowery farming, AeroFarms, and Lettuce Networks are doing something different. They're using data and artificial intelligence to operate more efficiently than traditional farms. The new generation of farming promises to feed more people while doing less environmental damage.

IBM has been on the AI journey for a long time, but the path has not always been smooth. My experience in the consulting business has taught me that successful practitioners need to be flexible and quick to make course corrections. We at IBM have learned along our AI journey, and here are three lessons that come to mind from my own interaction with clients and business colleagues. Remember the adage: garbage in, garbage out. We've acknowledged that the results of data analysis are sometimes misleading or even inaccurate.

The government signed a peace accord in late 2016 with the Revolutionary Armed Forces of Colombia (FARC), which was heavily involved in coca production and cocaine trafficking. Since the group demobilized, many new gangs have moved in and taken over its lucrative business and trafficking routes.

The tabular arrangement of the chemical elements, ordered by atomic numbers, electron configuration and chemical properties -- commonly called the periodic table -- not only came to be the favourite poster in school classrooms around the world, but also represents a century of fine tuning by the brightest scientists around the globe. The first version of the modern periodic table, which has been instrumental in predicting new elements in the universe and their behaviour, was first proposed by Russian chemist Dmitri Mendeleev in 1869. But the journey to the periodic table in its current form began in 1789 when Antoine Lavoisier published a list of 33 chemical elements, grouping them into gases, metals, nonmetals and earths, eventually leading to a century of chemists dedicated to classification of elements. This monumental exercise in science was replicated by an artificial intelligence (AI) programme developed by Stanford physicists within hours. The AI programme, called Atom2Vec, first learned to distinguish between different atoms after analysing a list of chemical compound names from an online database, Phys reported.

Soft robotics allow for safe interactions with humans, which is imperative for healthcare applications and wearable electronic devices. Smart materials--including shape-memory polymers, pneumatic polymers, hydrogels, and electroactive polymers--have all demonstrated utility in various applications, but each mode of actuation possesses drawbacks. Electromagnetic actuators (EMAs) are controlled by a magnetic field, leading to high-performance systems with small sizes, fast response times, and high power efficiency. However, these devices typically use rigid components, which are not amenable to soft robotics. Professor Yon Visell of the California NanoSystems Institute, UC Santa Barbara, and co-workers have developed a method to fabricate soft electromagnetic actuators (SEMAs) that is both inexpensive and scalable. The SEMAs are thermally efficient, polymodal, and can operate at high frequencies and low voltages.

When it comes to groundbreaking research, there are two fields that seem to occupy the newscycle: carbon nanotubes and artificial intelligence. The potential combination of those two fields of study seems like it could radically change the word as we know it, or, as South Korean scientists have discovered, at least change how we type. The carbon atom, one of the building blocks of life, gains radical new abilities when assembled into long, thin chains, known as carbon nanotubes. Think ultra-flexible films that are better at stopping bullets than kevlar vests, or bio-engineered plants that can detect land mines and explosives. And AI, trained using deep learning techniques, is soon going to make it almost impossible to discern fake videos from real ones. But researchers from South Korea's Sejong University, Chung-Ang University, and Kyungpook National University are instead merging those burgeoning technologies to create an ultra-thin portable keyboard that can be crumpled up like paper without breaking it.