THEY don't drink, they don't get tired and they don't go on strike. To hospital managers, the idea of robots operating on patients without human intervention is an attractive one. To patients, though, the crucial question is, "are they better than human surgeons?" Surgery is messy and complicated. A routine operation can become life-threatening in minutes. Such considerations have meant that the role of robots in operating theatres has been limited until now to being little more than motorised, precision tools for surgeons to deploy--a far cry from the smart surgical pods and "med-bays" of science fiction.

Accenture and IPSoft have launched a new practice called Accenture Amelia Practice (AAP), a new business unit aimed at helping clients adopt artificial intelligence in business. Accenture claims that AAP will help organisations in improving their business outcomes and create new growth opportunities. The company said that it will develop an array of go-to-market strategies, solutions and consulting service offerings for the deployment of virtual agent technology for clients across several industries. In the initial stages, the business unit will cater to clients in banking, insurance and travel industries with its virtual agent technology. Accenture chief technology officer, Paul Daugherty said: "Artificial intelligence is maturing rapidly and offers great potential to reshape the way that organisations conduct business and interact with their customers and employees. "At the same time, executives are overwhelmed by the plethora of technologies and many products that are advertising AI or Cognitive capabilities.

With a bulky camera eye and spindly hydraulic arm, this medical robot looks like it could fit in on an automotive production line. It carefully scans soft, sticky intestinal tissue and delicately weaves stitches with unmatched surgical precision. Indeed, with no guiding hand from its fellow doctors, it is the best in the world at performing the medical operation it was designed for. It is performing surgery all by itself. The surgical bot is named STAR, or Smart Tissue Autonomous Robot, and it just performed the world's first autonomous, soft-tissue surgery.

Artificial intelligence sounds cool in theory, and as Google CEO Sundar Pichai said at the Google I/O event on Wednesday, the company wants to „help you get things done" with AI.

Google diving deeper into virtual reality and artificial intelligence during an annual conference that serves as a launching pad for its latest products and innovations. Virtual reality and artificial intelligence, or "machine learning," will be among the focal points at the Google I/O developers conference, kicking off Wednesday. That has spurred speculation that Google is getting ready to release a virtual-reality device to compete with Facebook's new Oculus Rift headset, as well as the Samsung's Gear VR and the Vive from HTC and Valve. "2016 is already the year of VR," writes CNET's Sarah Mitroff. "[Google] has shown off Cardboard, its low-cost portable VR viewer initiative, for the last two years, and this year we're certain to see new developments."

Over the past few months Google, Microsoft and Facebook have taken major decisions to make their artificial intelligence API's openly available to all. IBM have opened their Watson API on a'freemium' basis and Elon Musk launched the OpenAI project with a star-studded list of backers; Palantir CEO Peter Thiel, LinkedIn founder Reid Hoffman and Y Combinator president Sam Altman. These hugely powerful tools, which are used, developed and backed by the world's most advanced technology companies, are now available to anyone with the skills to use them. Whilst these announcements haven't quite drawn the media attention of an iPhone launch, their significance and reach may be far greater. The point is this: using these toolkits, individually or combined, anyone can integrate transformational AI or machine learning platforms - which are as sophisticated as anything currently on the market - to their business at on a pay as you go or free basis.

Like iPhone's Siri on steroids, ROSS promises to cut down the time it takes to retrieve complex legal data from hours to minutes. He also learns and gets better with each use. ROSS is not a physical bot in the office but a complex AI system; it doesn't have the physical presence of an R2-D2 or Wall-E, but could easily outmaneuver them mentally. "Before, the human had to go through (and) read all the cases. The case could be 30 pages to find those three, four sentences they needed," said Arruda.

As a business buzzword, "machine learning" doesn't measure up to some of its more popular cousins – big data and transformation being two of the standouts – but this may not be the case for much longer. What was once something only used by people working in fields like software engineering, statistical modeling, and artificial intelligence, is now being used in many more recognizable and consumable forms. Online services such as Google, Netflix, Amazon, and Spotify all use machine learning to improve the customer experience. For example, if you've been streaming Barry White all week, Spotify's "Discover Weekly" playlist will begin suggesting other similar artists. Listeners may start seeing Luther Vandross pop up in their playlist, for example.

Perhaps Google thinks that the chips available in the market are unable to handle the needs of its machine learning algorithms because Google today announced at its I/O developer conference that the search giant has been building its own specialized chips to power the machine learning algorithms. Google has been using the Tensor Processing Units (TPU) custom-built chips to power its data centers according to Google's senior VP for its technical infrastructure Urs Holzle. Now it wants TPU to power its machine learning algorithms. Google says it's getting "an order of magnitude better-optimized performance per watt for machine learning" and argues that this is "roughly equivalent to fast-forwarding technology about seven years into the future." Google said that it has managed to speed up the machine learning algorithms with the TPUs because it doesn't need the high-precision of standard CPUs and GPUs.

Perhaps Google thinks that the chips available in the market are unable to handle the needs of its machine learning algorithms because Google today announced at its I/O developer conference that the search giant has been building its own specialized chips to power the machine learning algorithms. Google has been using the Tensor Processing Units (TPU) custom-built chips to power its data centers according to Google's senior VP for its technical infrastructure Urs Holzle. Now it wants TPU to power its machine learning algorithms. Google says it's getting "an order of magnitude better-optimized performance per watt for machine learning" and argues that this is "roughly equivalent to fast-forwarding technology about seven years into the future." Google said that it has managed to speed up the machine learning algorithms with the TPUs because it doesn't need the high-precision of standard CPUs and GPUs.