It's well known that we in the tech sector love our acronyms. We also like re-badging stuff.What was once ASP (application service provision) morphed into SaaS (software as a service) and then became part of the cloud computing eco-system. And so it is at the moment with AI (artificial intelligence). There have been a number of pronouncements recently, particularly from private practice firms, about their adoption of AI. But is the truth more weighted towards the "artificial" than the "intelligence"?

Trust greases the wheels of the sharing economy, paving the way for transactions to take place between total strangers. But figuring out who is trustworthy and who is not remains a sticky bottleneck for digital businesses wanting to scale faster. Meanwhile the consequences for customers when startups screw up these risk calculations can be very unpleasant indeed. The traditional route to assessing risk is to run a full background check on an individual -- a process that can be time consuming and expensive, given it can involve sending an actual person to an actual courthouses to parse actual paper records. Which is why, in recent years as sharing economy businesses have been gunning to scale up, other entrepreneurs have spotted an opportunity to step in to offer online services for verifying identity and screening for unsavory behavior, to try to steal a march on more established but slower paced background checkers.

As the driverless car gets closer to reality, so too does the dilemma of how to insure the car and its owner. The auto insurance industry faces upheaval in the next 25 years as the migration to autonomous safety features -- and ultimately a self-driving car -- shifts more of a car's accident risk from the driver to the vehicle, analysts said. The number of accidents is expected to drop sharply because currently more than 90% of accidents are caused by driver error. The U.S. market for personal auto insurance policies, which currently generates 200 billion in premiums a year, could shrink substantially, some experts predict. "There are going to be dramatic changes," said Joe Schneider, a managing director at KPMG who's part of the accounting firm's task force studying the issue.

The reputation of SystemML is on the rise. This flexible machine learning system scales automatically to Spark and Hadoop clusters and offers faster analysis on fewer nodes -- with substantial improvements in accuracy. In this presentation from Spark Summit in June 2016, researcher Fred Reiss spells out use cases for custom ML algorithms -- across the spectrum from auto manufacturing to the Watson Health initiative.

Kriti Sharma is a Bot entrepreneur, evangelist and expert. Four years ago she helped to launch PingIt, the Barclays mobile payments app. Sharma has masters degree in advanced computer science from St Andrews University and created a big data engine whilst studying there. Four months ago Sharma joined Sage as Global Director, Mobile Product Management. Her first task has been to create an as yet unnamed Bot to help entrepreneurs run their business.

When you think of leaders in artificial intelligence, Netflix (NASDAQ:NFLX) doesn't usually jump to the top of the list. But the streaming video service's VP of Product Innovation Carlos Uribe-Gomez and Chief Product Officer Neil Hunt published a paper that says some of its AI algorithms save Netflix 1 billion each year. In their paper, the two Netflix execs detail how the company's recommendation engine impacts its churn rate. Netflix no longer reports its churn rate, but the paper notes that Netflix's "retention rates are already high enough that it takes a very meaningful improvement to make a retention difference of even 0.1%." Let's dive into how the recommendation engine saves Netflix money -- and what the return on investment looks like.

"AI is the new mobile" is a phrase we might as well start getting used to hearing. It's infuriating that, just as the marketing world finally starts to think "mobile first", not one but two technology giants signal loudly that they're over mobile and on to the next thing. Witness Google chief executive Sundar Pichai, who recently spoke about moving from a mobilefirst to an AI-first world. Make no mistake, he sees artificial intelligence as the future of search, best exemplified by what Google calls the Google assistant: less a product and more an artificially intelligent, conversational interface to all things Google. Earlier in the year, at Facebook's developer conference F8, Mark Zuckerberg made AI one of the three pillars of Facebook's ten-year roadmap (alongside – yes, you guessed it – connectivity and virtual reality).

Enfield Council has taken a step into the use of artificial intelligence in a deal with cognitive technology company IPSoft to use its Amelia virtual agent in supporting its services. The London borough plans to begin using the software during the autumn, providing the first role for the technology platform in a public sector organisation. A spokesperson for the council told UKAuthority: "The initial deployment will be to help people navigate the website more effectively, and free up time for customer service staff to handle the more complicated enquiries." Amelia is a cognitive agent for service desk roles that uses natural language to communicate with people. IPsoft claims it can analyse language, understand context, apply logic, learn through observation, determine what actions to take to resolve problems and sense emotions.

Tambe's systems provided measurable outcomes that prove A.I. can be more efficient in managing patrol schedules than a lone human decision-maker. After LAX security officials implemented Tambe's first software system, called ARMOR, they saw an immediate, five-fold increase in the seizure of weapons, drugs and more. In 2013, a study by Los Angeles Metro found a 66 percent increase in the number of fare jumpers on L.A.'s subways. ARMOR was even adapted for the U.S. Coast Guard to catch illegal fishers in the Gulf of Mexico. ARMOR-FISH, tested in 2014, located illegal activities, though funding for the project has since stalled.

In this episode of our podcast, I sit down with Dr. Edward Challis Founder and CEO of Seedcamp-backed Re:Infer and Christoph Auer-Welsbach, IBM Watson Partner Innovation, joined Carlos to discuss Artificial Intelligence, Machine Learning, and whether or not we will have to worry about humanity's fate in the future… eg. With their experienced backgrounds, we covered the state of artificial intelligence today, some of the plausible uses and evolution of AI in the near term, and dispelling some of the myths around what is AI and what it can and can't do. If the above player doesn't work for you, you can also listen directly from our Soundcloud page.