The pace of acceleration in the past several years in AI seems to be starting to climb the exponential part of the "S" curve. From playing Go, to translating one human language into another, to predicting and attempting to compose hit tunes, to diagnosing disease from radiographic images, AI is starting to approach or exceed human abilities. These gains are being reported in specific or narrow AI, as opposed to general AI or Artificial General Intelligence (AGI), which some might deem real AI. Without debating the definition or attainability of real AI, I want to muse on whether emerging AI could augment (or even democratize?) This is important because just narrow AI will disrupt a significant portion of the work force within this generation, and empowering entrepreneurs may be a worthy goal for mitigating this inevitability, as well as a productive strategy for regional and national economic growth.

The solid line in the charts represents the net effect of AI, with the bars showing the displacement and income effects.Graphic via PricewaterhouseCoopers It's impossible to say precisely how artificial intelligence will disrupt the job market, so researchers at PwC have taken a bird's-eye view and pointed to the results of sweeping economic changes. Their prediction, in a new report out Tuesday, is that it will all balance out in the end. More automation in trucks, factories and elsewhere could cost around 7 million existing jobs in the U.K. by 2037. But the rise in robots and machine-learning software will make the country more productive over the next two decades, growing at a 2% annual clip, to put nearly the same number of jobs back in the system: 7.2 million, PwC estimates. To be clear, those new jobs won't involve building robots or coding AI-powered software, which will make up only around 5% of employment, says John Hawksworth, PwC's chief economist.

Small robots aren't anything new, from DARPA's insect-sized disaster relief bots to diminutive inchworms powered by humidity. Now, though, researchers at MIT have likely created the smallest robots, yet: Microscopic, cell-sized electronic circuits made of two-dimensional materials that catch a ride on colloids, insoluble particles that stay suspended in liquid or even air. Since these minuscule devices can sense their environment, store data and carry out computational tasks, they could eventually be found in oil and gas pipelines, checking for leaks. They could be deployed into the air at a chemical refinery to sense harmful byproducts, or even into the human digestive tract for early detection of illness. "We wanted to figure out methods to graft complete, intact electronic circuits onto colloidal particles," MIT's Michael Strano said in a blog post.

Machine learning and artificial intelligence have been the talk of the town for the past few years--and the hype isn't slowing down anytime soon. I believe 2019 is going to be the year for businesses who have waited to finally jump on board to witness a goldmine of advancements for their industry. What could we potentially see next year? Let's dig deeper into AI and machine learning predictions for the coming months. When dealing with a technology as advanced as machine learning, there simply isn't an industry that would not benefit. I mean how could a business not take advantage of a technology that would make them more successful?

As human beings, we use our voices for conversation. When we interact with voice interfaces, therefore, our natural instinct is to apply the same rules that we would to a human conversation. We expect to be understood, but more than this, we expect the entity we're conversing with to remember the history of our conversation and understand the context of any following remarks. For some time, major search companies like Google and Bing have worked to teach their search engines to understand queries in natural language. Natural language search queries are queries that sound natural spoken aloud, such as, "How high is the Empire State building?" They often begin with question words ("When…?" "How…?" "Why…?"), contain stop words ("a", "the", "of", "for") and full sentences.

NEW DELHI – India's first training center for teachers of Japanese was officially opened Monday in the capital, New Delhi. The inauguration ceremony for the center, which is a joint project involving the Indian Ministry of External Affairs and the Japanese Embassy with the support of the Japan Foundation, was attended by Japanese Ambassador to India Kenji Hiramatsu. The ambassador noted in a speech that demand for learning Japanese is growing significantly as the Japan-India relationship flourishes, leading to an increasing number of employment opportunities in Japanese companies in the country. "The number of Japanese companies is increasing every year and is now about four times the number seen 10 years ago. These companies require Indians who can speak the Japanese language, in order to act as bridges between their Indian subsidiaries and headquarters in Japan," he said.

Orlando International is now scanning all international arrivals/departures. This could escalate the surveillance state in a big way. Artificial Intelligence (AI) can create $3.5T to $5.8T in value for stakeholders. Americans think they are immune to the prying eyes of government. That is simply not true .

There has been a disconnect in the economy that's been stymieing policymakers and enterprise executives alike: there are many workers who fear being left behind in the digital and AI waves sweeping the business world. At the same time, there's a critical shortage of the talent needed to build this new digital, AI-driven world. A study out of Deloitte finds that only 16% of executives believe their teams have the capabilities to deliver their digital strategy. Still, money pours into digital technologies and projects -- 41% of organizations have invested in AI, up from 22% in 2017. In a recent interview with Knowledge@Wharton, Jake Schwartz, co-founder and CEO of General Assembly, a global IT training firm, discussed this paradox, in which talent is desperately needed to move forward, yet companies seems unwilling to invest in training to acquire the talent.

But if companies and governments shy away from investing in and developing AI technologies, then they could face a worse fate: obsolesce, or even annihilation. At Fortune's Brainstorm Tech conference in Aspen, Colo. on Tuesday, a panel of executives and leaders from GM, Intel, Slack, and the U.S. Navy discussed a coming wave of AI automation--and why neglecting this tech revolution could spell doom for laggards. Naveen Rao, who leads AI products at Intel, compared the situation to a dog-eat-dog, Darwinian model of the natural world. "AI recapitulates what happens in evolutionary systems," he said. Animals use their senses, brains, and bodies to acquire food and other necessities, Rao said.

Recently we saw a new "Master algorithm" that could be used to create the first generation of super intelligent machines, and now a team of researchers from Maryland, USA, announced this week that they've invented a general Artificial Intelligence (AI) way for machines to identify and process 3D images that doesn't require humans to go through the tedium of inputting specific information that accounts for each and every instance, scenario, difference, change and category that could crop up, and they claim it's a world first, even though it follows on from a not too dissimilar breakthrough from Google DeepMind whose own platform, Alpha Zero, recently taught itself a mix of board games including chess to a grand master level, in just four hours. All that said though it's important to say here that while doing away with huge volumes of training data used to train today's AI's is a staggering breakthrough of potential epic proportions this announcement doesn't yet herald the emergence of fabled Artificial General Intelligence (AGI) which is still a little way off and which Google Deepmind published an architecture for last year. However, this new development, albeit a distant cousin of AGI for now, will no doubt have an influence on the speed at which the first AGI's now emerge. This is actually a huge deal for the technology sector, and it's a massive step for the case of general AI versus specific AI, and once fine tuned, this development will have the power to shape and change how everyone, from police and intelligence officials, to retail marketers and medical professionals, go about their daily business. Currently, neural networks, defined as those computing systems that are aimed at mimicking how humans think and make decisions, are only as good as the information that's inputted.