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.

According to a report by Venture Beat, now may be the time to pull the trigger on that GPU purchase you have been holding off on. With cryptocurrency on the decline and the mining industry pulling back its expenditures on GPUs, you could spend less on a graphics card than ever before. The market is prime for users to finally get their hands on a GPU as the supply-demand issues it has been experiencing are coming to an end. With less pent-up demand for the technology, balance may potentially (finally) be restored, and it may be a little easier to swallow the price, as well as find more GPUs in stock. Below, seven members of Forbes Technology Council discuss whether the supply-demand issues with GPUs will finally find some sort of balance based on falling GPU prices.

Twenty years ago, setting up a timer to record on a tape your favourite TV show using a VCR device or recording a message on your voicemail was a total success in technology automation. Even the simple task of programming a digital alarm clock to wake us up at a certain time in the morning stopped being rocket science for some of us, fulfilling an inner desire to be part of a society that was unstoppably shifting into a digital transformation. This is just a small slice of how technology automation has changed over the past 20 years, and I assume we can all acknowledge that AI is gaining momentum, albeit regulatory authorities, legislators and lawyers not being fully sure how to adapt or embrace the change that's currently happening. Artificial Intelligence is here, it's the hot topic or the popular kid everyone wants to play in the park with. AI and automation are bringing us daily benefits; Internet and Big Data are becoming an essential part of both our work and private lives and we now have the capacity to collect huge sums of information too cumbersome for a person to process.