As manufacturing businesses are increasingly on the lookout for opportunities to boost automation, it is clear that big data and machine learning are set to revolutionize the future of production. Companies are already collecting huge amounts of data from various resources, including industrial machinery, and monitoring precise details of the production process in the hope of improving quality at every stage. When companies have gathered enough of the right data, predictive technologies can allow businesses to manage the servicing of machinery based on sensor data and advanced analytics, rather than on a fixed schedule. For a piece of machinery or an autonomous vehicle, for example, these technologies can help predict when and how they are likely to break down. Businesses can then service the equipment before it starts to be a problem and generate losses.

One question that always pops up in any machine learning problem: Which algorithm should I use? What do the algorithms do anyways? After briefly going over a typical machine learning process, we have a closer look at third step, i.e. building the model: What algorithms are out there? Which one should we use? One of Microsoft's Data Scientist, Brandon Rohrer, has written a nice three-part blog series on introducing data science with no jargon: Furthermore, there is one really neat cheat sheet created by Microsoft's Data Science team on when to use which algorithm: Finally, one last resource that I hihgly recommend: Top 10 data mining algorithms in plain English.

Ahead of'The future of litigation' on Thursday, RPC's Daniel Wyatt tells Tom Connelly how the Pyrrho case is redefining what it means to be a litigation lawyer Everyone's talking about artificial intelligence (AI), about what it can actually do, about how far it will go, and about whether trainee lawyers and paralegals' jobs are at risk. Daniel Wyatt, a litigation and arbitration specialist at RPC, has witnessed the rise and rise of AI within the legal sector first-hand. Wyatt -- who joined RPC as an associate in 2012 -- recognises that AI's impact on litigation and the legal sector is hugely important but stresses that it is more about a change in focus, not the death knell for junior posts. There will always be a need for junior lawyers. I suspect that the impact of AI will be more a case of re-distributing the work that paralegals and trainees undertake.

As the ancient Roman orator Cicero once put it, "The face is the index of the soul." In 2017, our faces are more index.html Nearly 250 million video surveillance cameras have been installed throughout the world, industry researcher IHS Insight estimated, and the global video surveillance market revenue is estimated to triple over a seven-year period, increasing to $42 billion in 2020 from $14 billion in 2013, according to industry predictions. Add to that surreptitious recording technology like drone cameras, Google Glass, Snapchat video glasses. Market researcher IBISWorld estimated the revenue for advertising agencies last year reached $44 billion, up 4% on the previous year. Face-reading technology can also now detect your emotions -- even those you don't realize you're projecting.

Artificial intelligence ("AI") is a technical field of computer science that includes machine learning, natural language processing, speech processing, expert systems, robotics and machine vision. The term "artificial intelligence" is sometimes challenged in favor of machine intelligence or machine learning. Machine learning automates decision making using programming rules and in some cases training data sets. Human subject matter experts can provide feedback on results as part of a training process. Machine learning can adapt its programming based on the training process and feedback.

Last December, Starbucks announced "My Starbucks Barista," a virtual barista for its mobile app that enables customers to place orders via voice command or messaging interface. This led me to consider the current perception of artificial intelligence and where it stands in relation to the current reality of the technology. Are chatbots the real deal or yet another victim of hyped technology? If you ask me, chatbots are still in the hype phase within the public eye and don't deserve a fraction of the attention they currently receive. While this may sound harsh, it's important to understand the difference between potential and intrinsic value, just like with any other new technology. You may be asking, if a brand as large as Starbucks is launching a chatbot, how can AI and chatbots still be considered hype?

For the most part conversations on the topic tend to revolve around loss of jobs and the redundancy of human labour. The Sunday Times has even gone as far as producing a list of the jobs most likely to become automatised in the coming years due to artificial intelligence. While some jobs are at a higher risk than others, it's estimated that those in advertising have only a 3.8% chance of being replaced by a machine. In reality, AI will actively work with us, not against us, making our business processes more streamlined and efficient. Infosys, a global leader in technology services, published a report that establishes a clear link between the revenue and implementation of AI technology in businesses. Although there have been cases of job loss due to automation, such as the recent layoffs at General Electric.

My wife used to love reading but since her stroke has aphasia, no speech, limited vision and limited dexterity in her left hand only. She can select TV channels on a remote but she cannot read a short news story let alone a novel, so she listens to the radio and watches a lot of TV. I thought of getting her a Kindle e-reader but they don't seem to do text to speech any more. A shop assistant suggested a tablet with a text-to-speech app. It needs a really simple interface or my wife will not be able to use it without assistance.

Whether or not an artificial intelligence (AI) ought to be granted patent rights is a timely dilemma given the increasing proliferation of AI in the workplace. AI technology has been applied effectively in medical advancements, psycholinguistics, and tourism and food preparation. Even a film written by an AI recently debuted online, and AI has sneaked into the legal profession. One might argue that Intellectual Property (IP) laws and IP Rights were designed to excusively benefit human creators and inventors, and thus would exclude non-humans from holding IP rights. However, many IP laws were drafted well before the emergence of AI, and in any case do not explicitly require that a creator or inventor be'human.'

Artificial Intelligence (AI) may have a big role in Africa's eHealth strategies. An article in Wired says it's hugely successful at poker too. From the 1940s, chess was the test of AI. It's a game of structured rules that computers could learn. To succeed, it has to outmanoeuvre other players' bluffs and intuition and deal with only partial information about the state of each game too, which aren't structured or rule-based. Libratus, built by Brown and Sandholm, two computer science researchers at Carnegie Mellon University, did it.