Category Archives: Artificial intelligence

Google’s AlphaGo publicity stunt raises profile of AI and machine learning

Google AlphaGoWorld Go champion Lee Se-dol has beaten AlphaGo, an AI program developed by Google’s DeepMind unit this weekend, though he still trails the program 3-1 in the series.

Google’s publicity stunt highlights the progress which has been made in the world of artificial intelligence and machine learning, as commentators predicted a run-away victory for Se-dol.

DeepMind founder Demis Hassabis commented on Twitter “Lee Sedol is playing brilliantly! #AlphaGo thought it was doing well, but got confused on move 87. We are in trouble now…” allowing Se-dol to win the fourth game in the five game series. While the stunt demonstrates the potential of machine learning, Se-dol’s consolation victory proves that the technology is still capable of making mistakes.

The complexity of the game presented a number of problems for the DeepMind team, as traditional machine learning techniques would not enable the program to be successful. Traditional AI methods, which construct a search tree over all possible positions, would have required too much compute power due to the vast number of permutations within the game. The game is played primarily through intuition and feel, presenting a complex challenge for AI researchers.

The DeepMind team created a program that combined an advanced tree search with deep neural network, which enabled the program to play thousands of games with itself. The games allowed the machine to readjust its behaviour, a technique called reinforcement learning, to improve its performance day by day. This technique allows the machine to play human opponents in its own right, as opposed to mimic other players which it has studied. Commentators who has watched all four games have repeatedly questioned whether some of the moves put forward by AlphaGo were mistakes or simply unconventional strategies devised by the reinforcement learning technique.

Although the AlphaGo program demonstrates progress as well as an alternative means to build machine learning techniques, the defeat highlights that AI is still fallible; there is still some way to go before AI will become the norm in the business world.

In other AI news Microsoft has also launched its own publicity stunt, though Minecraft. The AIX platform allows computer scientists to use the world of Minecraft as a test bed to improve their own artificial intelligence projects. The platform is currently available to a small number of academic researchers, though it will be available via an open-source licence during 2016.

Minecraft appeals to the mass market due to the endless possibilities offered to the users, however the open-ended nature of the game also lends itself to artificial intelligence researchers. From searching an unknown environment, to building structures, the platform offers researchers an open playing field to build custom scenarios and challenges for an acritical intelligence offering.

Aside from the limitless environment, Minecraft also offers a cheaper alternative for researchers. In a real world environment, researcher may deploy a robot in the field though any challenges may cause damage to the robot itself. For example, should the robot not be able to navigate around a ditch, this could result in costly repairs or even replacing the robot entirely. Falling into a ditch in Minecraft simply results in restarting the game and the experiment.

“Minecraft is the perfect platform for this kind of research because it’s this very open world,” said Katja Hofmann, lead researcher at the Machine Learning and Perception group at Microsoft Research Cambridge. “You can do survival mode, you can do ‘build battles’ with your friends, you can do courses, you can implement our own games. This is really exciting for artificial intelligence because it allows us to create games that stretch beyond current abilities.”

One of the main challenges the Microsoft team are aiming to address is the process of learning and addressing problems. Scientists have become very efficient at teaching machines to do specific tasks, though decision making in new situations is the next step in the journey. This “General Intelligence” is more similar to the complex manner in which humans learn and make decisions every day. “A computer algorithm may be able to take one task and do it as well or even better than an average adult, but it can’t compete with how an infant is taking in all sorts of inputs – light, smell, touch, sound, discomfort – and learning that if you cry chances are good that Mom will feed you,” Microsoft highlighted in its blog.

Digital health startup Babylon gets £24m to develop medical AI

Babylon Simulator Screen ShotUK-based digital health service Babylon Health has raised $25m in a Series A funding round led by Swedish investment group AB Kinnevik. The venture capital advance is a record amount for a European cloud based health start up.

Babylon will use the cash to expand beyond its current online patient base of 250,000 UK users to deliver preventative medicine and sick care across EMEA. Since its launch in February 2015, the service has expanded to Ireland and there are plans for an East African service for 2016. Businesses such as Citigroup, Sky and MasterCard offer it to their staff as an employee benefit and it’s used by health insurance providers Mercer, Bupa and Aviva. It claims it’s at an early stage of partnering with the NHS to make its services available to the broader UK population.

The platform uses machine learning to analyse genetics, environment, behaviour, biology and key body functions. It uses this information as a form of preventative medicine, encouraging users to stay healthy through timely personalised health advice. It now plans an additional service which aims to help monitor and manage course completion when medicine is prescribed and to assesses the effectiveness of the treatment. Babylon has demonstrated a working prototype of this additional app, which is due for launch in 2016.

Partners in the venture include investment company BXR Group, Google-owned artificial intelligence company DeepMind and Hoxton Ventures, the fund established to bridge European companies to Silicon Valley. According to the FT.Com Babylon is valued at £100m.

In January another UK based online health start up, PushDoctor, announced it had raised $8.2million round of Series A financing from Oxford Capital, Draper Esprit and Partech Ventures.

IBM unveils plans for Watson supercomputer to lead the cognitive era

Toward Digital EncryptionIBM CEO Ginni Rometty used the Consumer Electronics Show in Las Vegas to showcase a range of new partnership projects that will help supercomputer Watson usher in the ‘Cognitive Era’.

Among the new advances promised are health and fitness programmes, robotic apps for banking retail and hospitality, intelligent home appliances and computers that understand and adapt to human behaviour.

Under Armour and IBM have jointly developed a new cognitive coach that gives athletes evidence-based advice on health and fitness-related issues, Rometty revealed. The system combines IBM Watson’s technology with data from the 160 million members of Under Armour’s Connected Fitness community.

Meanwhile Watson is being used by Medtronic to bring its analytics powers to diabetes management. A joint effort by both companies means that hypoglycemic events can be predicted three hours in advance and neutralise deadly health events.

The cloud has infused Watson into Softbank Robotics’ ‘empathetic’ robot Pepper, boosting its thought processing powers so it can understand and answer questions. This, argued Rometty, could be applied to businesses such as banking, retail and hospitality.

Rometty said IBM and SoftBank Robotics will tap into data and knowledge across the IoT so Watson-powered Pepper robots can make sense of the hidden meaning in social media, video, images and text. This, Rometty said, brings in a new era in computing where systems understand the world in the way that humans do: through senses, learning and experience.

Appliance maker Whirlpool is being hooked into the Watson IoT cloud to create new cognitive products and services, such as an oven that can learn about its user’s eating habits, health issues and food preferences. IBM demonstrated Whirlpool’s Jen-Air oven equipped with the Chef Watson cooking app.

The developments mark a new cognitive era of computing, where IT works around humans, a reversal of the standard practise, according to IBM. “As the first system of the cognitive era, Watson infuses a kind of thinking ability into digital applications, products and systems,” said John Kelly, senior VP of IBM Research and Solutions Portfolio.

A Watson software development kit (SDK) is available to give developers the chance to tailor the interaction experience. IBM will give clients access to Watson APIs and various pre-packaged applications designed to address a variety of personal and professional needs.

Anomaly Detective Adds Predictive Analytics to Splunk

Prelert today announced Anomaly Detective, an advanced machine intelligence solution for Splunk Enterprise environments. The introduction of Anomaly Detective expands Prelert’s line of diagnostic predictive analytics products that integrate with a customer’s existing IT management tools and quickly provide value by finding problematic behavior changes hidden in huge volumes of operations data.

Anomaly Detective’s self-learning predictive analytics with machine intelligence assistance recognize both normal and abnormal machine behavior. Using highly advanced pattern recognition algorithms, Anomaly Detective identifies developing issues and provides detailed diagnostic data, enabling IT experts to avoid problems or diagnose them as much as 90 percent faster than previously possible. IT personnel who utilize Splunk Enterprise software in infrastructure, applications performance and security can now additionally benefit from machine learning to automatically spot anomalies and isolate their root causes in minutes, saving time and resolving problems before the business is impacted.

Anomaly Detective is  downloadable software that installs as a tightly integrated application for Splunk Enterprise. Because it leverages recent advances in machine intelligence, Anomaly Detective is 100 percent self-learning and requires minimal configuration. Anomaly Detective augments existing IT expertise, empowering IT staff to spend less time mining data, reduce troubleshooting costs and improve compliance with service-level agreements — all of which contribute to a rapid return on investment.

“Prelert Anomaly Detective is like a machine intelligence assistant, using advanced machine learning analytics to analyze the massive amounts of IT operations management data produced by today’s online applications and services,” said Mark Jaffe, CEO of Prelert. “We’ve packaged the power of big data analytics, normally focused on solving business problems, in easy-to-use machine intelligence solutions that are greatly needed in the real world of IT operations.”

Prelert Anomaly Detective is now available and easily downloadable from the Prelert website and from Prelert resellers. Pricing is based on the amount of data analyzed per day, starting at $1,200 for environments indexing more than 500MB of data per day. For information on pricing for Splunk Enterprise, go to