You can now buy a humanoid robot housekeeper for less than the price of a second-hand car. But before splashing out, there's something you need to know Science fiction is strewn with humanoid robots, from bad-tempered Bender in to cunning Ava in . And it has long seemed like that's the natural home for such robots - on the screen and in books. The idea of a walking, talking, functioning robot with two arms and two legs has appeared to be a distant dream. Last year, machines ran, boxed and even played football at China's World Humanoid Robot Games, albeit sometimes falling over in the process . Meanwhile, companies have been readying their own range of humanoids that promise to do something a bit more useful: help around the house .

A new robot hand provides extremely fast and flexible finger movements, while also being tough enough to survive intense damage. That durability helps the hand, which is already being used in Google DeepMind's robotics experiments, during the trial-and-error learning required to train artificial intelligence. This latest robotic hand developed by the UK-based Shadow Robot Company can go from fully open to closed within 500 milliseconds and perform a fingertip pinch with up to 10 newtons of force. It can also withstand repeated punishment such as pistons punching the fingers from multiple angles or a person smashing the device with a hammer. The new hand's robust design is well suited for AI-powered robotics experiments based on reinforcement learning, which allows robots to gradually learn how to interact with environments by fumbling through tasks using trial and error, says Ram Ramamoorthy at the University of Edinburgh in the UK.

Automation represents perhaps the clearest embodiment of Benjamin Franklin's legendary "time is money" aphorism -- and artificial intelligence (AI)-driven networks are one area where it's relatively easy to see the near-term benefits that give new meaning to Franklin's simple phrase. Network automation simplifies operations for network teams and reduces configuration errors. So, it stands to reason that greater automation through AI will deliver a more predictable and reliable network that seemingly can speed up time while saving lots of money. We turned to the CIO Experts Network of IT professionals and industry analysts to collect their views on AI-driven networks and how the technology is likely to change the lives of network teams. "I think of an AI-driven network as one that can be prepared in advance of a catastrophe or breach by capturing and saving critical data prior to a network outage or cyber event," says Scott Schober (@ScottBVS), President/CEO at Berkeley Varitronics Systems, Inc. "When this is an integrated part of the network, troubleshooting time is reduced delivering improved efficiencies for network teams. Still, like all things AI, it's necessary to sort what's real from what's hype, experts say. Hyped up AI technologies are often rolled out as the solution to all problems, observes Nicki Doble, Chief Transformation Officer AIA Philippines. "I don't buy into the hype," she says. "However, I absolutely agree that an AI-driven network helps in detecting new and never seen before threats.

To make decisions more quickly and accurately, enterprises in the Middle East and Africa (MEA) are increasingly turning to Machine Learning, arguably today's most practical application of Artificial Intelligence (AI). How should CIOs and IT leaders ensure success and ROI from Machine Learning deployments in their organisations? Machine Learning is a type of AI that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Machine Learning algorithms use historical data as input to predict new output values. In addition, Machine Learning systems apply algorithms to data to glean insights into that data without explicit programming: It's about using data to answer questions.

In any debate, there are always at least two sides. That reasoning also applies to whether or not it is a good idea to use artificial intelligence technology to try stemming the advantages of cybercriminals who are already using AI to improve their success ratio. In an email exchange, I asked Ramprakash Ramamoorthy, director of research at ManageEngine, a division of Zoho Corporation, for his thoughts on the matter. Ramamoorthy is firmly on the affirmative side for using AI to fight cybercrime. He said, "The only way to combat cybercriminals using AI-enhanced attacks is to fight fire with fire and employ AI countermeasures."

The goal of any business is to improve productivity, enhance the customer experience, and maximise profits--Artificial Intelligence (AI) can play a crucial role on all these fronts, says Ramprakash Ramamoorthy, director of research at ManageEngine, the enterprise IT management division of Chennai-based business software maker Zoho. "The enormous growth witnessed in cloud computing has resulted in a huge amount of generated data. This is where AI steps in. Utilising AI to analyse vast amounts of collected data helps businesses gain a deep understanding of their systems," he says. Ramamoorthy stresses that when deployed correctly, AI systems can predict outages, help provide proactive infrastructure management and ensure better service availability.

Artificial intelligence is increasingly becoming a part of our daily lives, both in the workplace and at home. Some AI experts are stressing the need to focus on making AI ethical and keeping it human friendly. Bias in programming, security concerns, and a lack of public knowledge about how AI works are all issues that need to be addressed to develop and maintain a healthy relationship between humans and the technology we use. "This is the year AI ethics become absolutely mandatory functions in most businesses, not just talk," Alex Spinelli, chief technology officer at LivePerson and former global head of Alexa OS for Amazon, told Hypergrid Business. Companies are just starting to consider responsible use of AI as a part of their business model.

Artificial Intelligence (AI) is the buzzword these days, and for good reason. Businesses around the world are taking up AI technologies to try and reduce operational costs, increase efficiency, grow revenue and improve customer experience. Businesses are also looking at putting a full range of smart technologies such as machine learning, natural language processing and more, into their processes and products. However can businesses that are new to AI, reap major rewards? When it comes to artificial intelligence, most people are well aware of the tropes from popular entertainment: the malevolent computer, the android gone rogue.

Many multiagent applications require an agent to learn quickly how to interact with previously unknown other agents. To address this problem, researchers have studied learning algorithms which compute posterior beliefs over a hypothesised set of policies, based on the observed actions of the other agents. The posterior belief is complemented by the prior belief, which specifies the subjective likelihood of policies before any actions are observed. In this paper, we present the first comprehensive empirical study on the practical impact of prior beliefs over policies in repeated interactions. We show that prior beliefs can have a significant impact on the long-term performance of such methods, and that the magnitude of the impact depends on the depth of the planning horizon. Moreover, our results demonstrate that automatic methods can be used to compute prior beliefs with consistent performance effects. This indicates that prior beliefs could be eliminated as a manual parameter and instead be computed automatically.

Forget health and safety videos – this algorithm could do a better job of making sure people lift with their knees bent and back straight. Sensors that automatically detect whether you're about to give yourself a back injury at work could be easily slipped into the bottom of a shoe. People often don't realise that they're not adopting the right posture when lifting heavy items, says Eya Barkallah at the University of Quebec at Chicoutimi in Canada. So Barkallah and her colleagues created a pair of wearable sensors that can detect when someone isn't using the right posture while they're lifting or carrying something heavy. "We wanted to find a preventative treatment for work-related injuries," Barkallah says.