LivePerson, Inc., a global leader in Conversational AI, announced two major strategic acquisitions: VoiceBase, a leader in real-time speech recognition and conversational analytics; and Tenfold, the world's most advanced customer engagement platform for integrating communication systems with leading CRM and support services. Through these acquisitions, three powerful technologies combine to create a unified, AI-enabled system for customer experience: VoiceBase's superior speech recognition and analytics capabilities, Tenfold's advanced voice, messaging, and CRM integrations, and LivePerson's industry-leading Conversational AI and asynchronous messaging. Brands can now enable natural, conversational consumer experiences that carry context and continuity across all channels, powered through a single automated voice and messaging desktop experience. Acquiring VoiceBase and Tenfold accelerates LivePerson's vision to help brands gain complete ownership and visibility over engagements in the channels customers care about, inclusive of voice and messaging. These companies bring voice intelligence and AI technologies to support LivePerson's upcoming voice capabilities within its world-class conversational AI messaging platform. "Brands want to accelerate their use of Voice and Conversational AI with deep connective tissue into their systems," said Rob LoCascio, founder and CEO of LivePerson.

This article originally published in tenfold.com We are living in exciting and innovative times with futuristic technology literally at our fingertips. But for the longest time, small to medium-sized businesses were not serviced by the latest tech trends such as AI, machine learning enterprises have been able to benefit from. In this article, we'll explore these technology trends and how they will impact business in 2018 and beyond. So, what kind of things can this'smart' tech do?

In the US alone, tens of millions of mammograms are performed each year. Analyzing these images takes up a lot of doctors' time. The use of computer assistance to help read mammograms is becoming widespread, but doubts persist about whether the practice is helpful enough to justify its steep price tag. Lower-cost deep learning systems, which train themselves to recognize cancer, could help. Thanks to deep-learning methods like those more commonly used to spot everyday objects in photographs, a new system identified cancer's precise location more than 90 percent of the time in tests.

Enter your email address to subscribe to this blog and receive notifications of new posts by email. Permission to publish provided by Ira Padilla. For those who may find awkward the reference to "half a decade" and not the "next decade" here is why: AI is evolving at such a staggering rate that it is simply not possible to foresee what it will represent in 10 years' time. As Maurice Conti (Chief Innovation Officer at Telefónica Alpha and former director at Autodesk) reminded on his intervention at TEDX in February 2017, in human history the "Hunter-Gatherer" age lasted for several million years, then the Agricultural age lasted several thousand years, the Industrial age has been around for a couple of centuries now, the Information age has merely a few decades and the AI age (although the concept was drawn in the 1950s) has in fact effectively started less than half a decade ago. It is very easy to mistake AI for RPA (Robotic Process Automation), so let's start by defining what sets them apart.

Artificial Intelligence (AI) is revolutionising multiple areas of information technology and has exciting potential for applications in biomedicine. It is predicted that the use of AI in healthcare will grow tenfold in the next five years. In a clinical setting AI will be a powerful tool, using patients' data - including their genetic sequence - to empower clinicians to make informed healthcare decisions based on the latest and most effective treatment options for each patient. Computer-aided diagnosis and treatment is currently being trialled at 16 cancer institutes in partnership with IBM's Watson Health AI venture. However, not all of the medical applications of AI will be for doctors; the technology has diverse applications for healthcare.