The AI Times is a weekly newsletter covering the biggest AI, machine learning, big data, and automation news from around the globe. If you want to read A I before anyone else, make sure to subscribe using the form at the bottom of this page. IBM said the transition to a single hub was "accelerated over the past year when virtual work environments became commonplace." Accenture's Health Tech Innovation Challenge brings together start-ups and larger health organizations to tackle the world's biggest health issues. Now in its fifth year, the challenge gives start-ups the chance to pitch their innovative ideas to leading CEOs from across the healthcare industry in Canada and the US. Entrepreneurs will gain exposure to judges who represent the broad spectrum of Accenture's clients in healthcare, insurance, life sciences, and government.

What might self-driving cars do for people with a disability in places like the Central Coast? Notwithstanding recent improvements, the Coast still has a relatively poor public transport network, something that hinders people who cannot drive themselves to work or social engagements. And so it was with much anticipation I travelled to the Newcastle foreshore to experience for myself the driverless shuttle imported from France. If the shuttle was to be trialled and accepted here on the Central Coast, I could see it being a huge advantage to people living with disabilities, mobility issues, the elderly and people who are unable to drive. In 2016 approximately 6.4 per cent of people on the Central Coast needed help in their day-to-day lives due to disability.

AI pilots are progressing into production based on their combined contributions to improving customer experience, stabilizing and increasing revenues, and reducing costs. The most successful AI use cases contribute to all three areas and deliver measurable results. Of the many use cases where AI is delivering proven value in enterprises today, the ten areas discussed below are notable for the measurable results they are providing. What each of these ten use cases has in common is the accuracy and efficiency they can analyze and recommend actions based on real-time monitoring of customer interactions, production, and service processes. Enterprises who get AI right the first time build the underlying data structures and frameworks to support the advanced analytics, machine learning, and AI techniques that show the best potential to deliver value.

The deployment of increasingly smarter chatbots, AI-powered virtual assistants and conversational AI technology has enabled organizations to increase customer engagement, save resources by efficiently scaling their customer-facing operations, and ultimately make their customers and end users more satisfied. But now, with ever-smarter and more context-aware chatbots, advancements in fields such as predictive analytics and speech recognition, and the integration of these technologies into end-users' devices, we witness how data scientists, engineers, and AI entrepreneurs are taking things to the next level. The trends considered in this article are based on the insights provided by the conversational AI leaders and innovators who have thus far participated in our conversational AI interviews. For each trend, we discuss the impact and opportunities for businesses to leverage the next generation of conversational AI. We invite NLP and Conversational AI innovators to participate in the survey to be featured in our upcoming article "Inspiring People in Conversational AI to Follow in 2020".

As technology rapidly progresses, doomsday stories emerge just as quickly. Dissident voices, however, are trying to spread alternative messages. In the past century, increasingly efficient technology and the advancement of knowledge have addressed global challenges including global poverty, deaths from violent crime, childhood mortality, preventable diseases and human life expectancy - at a scale never seen before. For obvious reasons, such breakthroughs can be considered among humanity's greatest achievements; yet we also see how technology facilitates online disinformation, global cyberattacks and unprecedented terrorist media campaigns inspiring thousands of would-be terrorists. "Technology is a force that takes what was once scarce and makes it abundant," write Peter Diamantis and Steven Kotler in Abundance: The Future is Better than You Think.

Around a year ago, amidst numerous desktop browsers, a LinkedIn notification blinked expectantly. The freshly minted digital magazine of Forbes unleashing its 30 Under 30's. Intrigued, I hastily found the social entrepreneurship section. This was definitely very special. But it would take more than half a year since connecting with Emily on LinkedIn, to find the guts to actually reach out and hear more…because in reality, other than the recent Sciences Po course I took on algorithmic governance, I had underestimated how much potential AI had within law enforcement and justice.

Digital technology constantly changes, grows and delivers, but some of the promises of digital technology are ethereal when it comes to healthcare. Since 2010 IBM has had the promise of Artificial Intelligence (AI) in healthcare through the Watson initiative. IBM would describe Watson as a solution to the big healthcare problems, but which healthcare problems? Sometimes Watson has felt just out of the grasp of the front line digital leadership in all but the richest of healthcare systems, and for so long Watson has been'code' for AI in healthcare. In 2018 the UK minister for health talked up the virtues of AI as a solution to the General Practitioner resource issues hitting primary care delivery in the National Health Service (NHS) for the last decade, maybe even more.

Artificial intelligence is so hyped that it might be tempting for top health executives to presume it's just the domain of technologists, or so far off that they might be wiser waiting for others to move first. Instead, it's smart to consider where rival healthcare organizations are investing today. We surveyed 142 qualified professionals working in IT, business, informatics and clinical roles within hospitals, health insurers and pharmaceutical companies. The findings show that artificial intelligence and machine learning are already delivering value in specific areas. Respondents have big hopes for AI and ML in clinical settings for chronic conditions in particular.

I was recently a guest on the Game-Changing Predictive Machine Learning radio show hosted by Bonnie Graham. The other guests were Gil Gomez of Deloitte and Hudson Harris of HarrisLogic. Here are some of my remarks from the show. "Machine learning is really about complex-but-repetitive decisions and being able to automate those in new ways. And when you think about it that way, it's hard to think of an area where it won't have an impact. "Almost every job, every role, has some aspect of that job that involves complex, repetitive decisions, and you can now automate that and elevate the person doing the role to a higher level, allowing them to do more with less." "Governance is an area that is not sufficiently discussed when it comes to machine learning.

Your Shopping Cart is empty. How companies are using artificial intelligence in their business operations. A 5-Part Process for Using Technology to Improve Your Talent Management Talent management Digital Article "Talent tech" can change how firms hire, evaluate, and develop employees. We Need Transparency in Algorithms, But Too Much Can Backfire Technology Digital Article Consumers should have some idea how machines make decisions. Most of AI's Business Uses Will Be in Two Areas Technology Research Supply chain and sales and marketing are the first big opportunities.