Do you fancy a technical talk to kick off this week? The AI Machine Learning community gets back at TechHub Bucharest for an interesting presentation. Join them on Monday, June 6, to find out more about the AlphaGo model and the machine learning algorithms it employs. During this meetup you'll get an in-depth presentation of the AlphaGo model and the machine learning algorithms it employs. AlphaGo is the artificial Go player developed by DeepMind, the first one to win against a professional human Go player.

We are living in a digital era where Customer is the king. Many businesses have capitulated to this new realm and have started interacting with customers dynamically. Today the customers are free to navigate a merchant (eCommerce) website any way they fancy. Also the merchant can display content and place offers dynamically based on how a given customer interacts with his website. To add to the complexity purchase decisions are not necessarily made on the first visit itself.

In the past year alone, Google-owned Deep Mind has made great strides in artificial intelligence. The company has long kept an eye towards safety with the establishment of an ethics board as part of the 2014 acquisition, and now a new paper (via BI) from DeepMind and the University of Oxford describes the creation of a "big red button" method that can be used to stop AI from causing harm… In the paper, DeepMind assumes that AI agents are "unlikely to behave optimally all the time" when interacting with the real world. As such, it's important that human operators are able to halt the AI from continuing "a harmful sequence of actions" and lead it to a safer situation. The paper defines harm as either to the surrounding environment or the agent itself. The method created by the researches goes a step further by making sure the AI does not prevent itself from being interrupted by humans.

It's not all that easy to call KnuEdge a startup. Created a decade by Daniel Goldin, the former head of the National Aeronautics and Space Administration, KnuEdge is only now coming out of stealth mode. It has already raised 100 million in funding to build a "neural chip" that Goldin says will make data centers more efficient in a hyperscale age. Goldin founded the San Diego, Calif.-based company with the former chief technology officer of NASA, said he believes the company's brain-like chip will be far more cost and power efficient than current chips based on the computer design popularized by computer architect John von Neumann. In von Neumann machines, memory and processor are separated and linked via a data pathway known as a bus.

Google has suggested a "big red button" could be used to prevent artificial intelligence from a "harmful sequence of actions". A research paper from DeepMind and the University of Oxford says there should be a way to "repeatedly safely interrupt" an algorithm. "Safe interruptibility can be useful to take control of a robot that is misbehaving and may lead to irreversible consequences, or to take it out of a delicate situation, or even to temporarily use it to achieve a task it did not learn to perform or would not normally receive rewards for this," the paper, which proposes a framework to let humans stop an algorithms from continuing on a dangerous path, says. The paper's authors – Laurent Orseau, from DeepMind, and Stuart Armstrong from the The Future of Humanity Institute – explain that an "interruption policy" could be built into algorithms to safely stop a machine. Reinforcement learning algorithms, the paper continues, often work in complex environments, such as "the real world", and are unlikely to act as they are intended on every occasion.

Self-driving vehicles claim to reduce the risk of accidents and congestion by removing human unpredictability. But one car manufacturer has been teaching its robotic vehicles to drive more like humans in an effort to make them safer on the roads. Audi's A7 sportback autonomous test vehicle - nicknamed Jack - drifts towards the road markings before signalling its intent to perform a lane-change manouevre. Audi's new driverless car technology (pictured) is being taught to behave more like a human by moving closer to lane markings before signalling that it is about to change lanes and giving larger vehicles a wider bearth The German car giant has found that this subtle movement is used by human drivers as an unconscious signal of intent before they even turn on the indicators. Audi's car also tends to give larger vehicles like trucks a wider berth when overtaking, much like human motorists.

Machine learning is a technical discipline that provides computers with the ability to learn from data (observations) without being explicitly programmed. Machine learning excels in solving complex, data-rich business problems where traditional approaches, such as human judgment and software engineering, increasingly fail. "Ten years ago, we struggled to find 10 machine learning based business applications. Now we struggle to find 10 that don't use it." While the basic concepts of machine learning have been around for decades, interest is at an all-time high.

We all know how crucial triage is in a medical environment. Intuitively we know it makes sense to ensure that the most critical cases are seen quickly and efficiently. Most business functions have applied triage based processes for years, decades. Sales to direct the right opportunities to the most relevant sales people. HR to allocate the appropriate resource to a particular case.

Chris and Nationwide view AI in the context of their entire technological development: "we see AI as a continuation and acceleration of the automation that has been central to the changing nature of financial services over the last twenty or thirty years", he explains. "As an innovation team, we believe that history is often a good guide to the future and as in previous technological leaps forward, the view of AI being'destructive' to jobs is too simplistic. It will instead change the nature of the jobs people perform". "In many areas this will prove beneficial by complementing what people do. Putting information at their fingertips and removing laborious manual processes will allow them to focus on the most fulfilling and challenging parts of their roles. For others, the impact will be to create new types of job where the focus will be on ensuring that information, processes and our environment are constantly optimised to enable machines to perform their roles."

The Future of Humanity Institute, University of OxfordStuart Armstrong is a philosopher at the University of Oxford and one of the paper's authors. Machines are becoming more intelligent every year thanks to advances being made by companies like Google, Facebook, Microsoft, and many others. AI agents, as they're sometimes known, can already beat us at complex board games like Go and they're becoming more competent in a range of other areas. Now a London AI research lab owned by Google has carried out a study to make sure we can pull the plug on self-learning machines when we want to. DeepMind, acquired by Google for a reported 400 million in 2014, teamed up with scientists at the University of Oxford to find a way to make sure AI agents don't learn to prevent, or seek to prevent humans from taking control.