Dr. Ben Choi, associate professor of computer science at Louisiana Tech University, will present his research on a groundbreaking new technology that has the potential to revolutionize the computing industry during a keynote speech next month at the International Conference on Measurement Instrumentation and Electronics. Choi will present on a foundational architecture for designing and building computers, which will utilize multiple values rather than binary as used by current computers. The many-valued logic computers should provide faster computation by increasing the speed of processing for microprocessors and the speed of data transfer between the processors and the memory as well as increasing the capacity of the memory. This technology has the potential to redefine the computing industry, which is constantly trying to increase the speed of computation and, in recent years, has run short of options. By providing a new hardware approach, the technology will push the speed limit of computing using a progressive approach which will move from two values to four values, then to eight values, then to 16 values, and so on. Future computers could be built using this many-valued approach.

In recent years, big data and artificial intelligence (AI) have received overwhelming attention, however the interesting – even obvious – connection between the two hasn't often been explored. It is the combination of big data and AI working together that is now enabling business leaders to deliver new insights, efficiencies and even new functions that haven't been possible before. This is evident in the increasingly useful role big data and AI are playing in a broad spectrum of traditionally outsourced functions such as recruitment, HR, finance and supply chain, through to security and IT. The combination has already had a major impact on how the stock market works, synthesising more and more data to the point at which some people believe it will eventually be able to accurately predict both market trends and human influences on the market. At a more everyday level, Google uses deep learning to recognise objects in images, AI is the technology behind Facebook's Deep Face friend tagging feature and machine learning is the basis for Amazon's recommendation engine.

In an ongoing effort to extract more useful information and insights from massive volumes of structured and unstructured data, many organizations have turned to cloud based Hadoop big data analytics solutions such as Qubole. And as effective as these solutions are at capturing and analyzing large data volumes, their ability to interact with powerful Business Intelligence (BI) tools such as Machine Learning Libraries (MLL), is taking big data analytics capabilities to a whole new level. What follows is a look at 5 Machine Learning Libraries and the Big Data use case for each. MLlib features a host of common algorithms and data types, all designed to run at speed and scale. This makes MLlib a good fit for network security and other use cases such as predictive intelligence, customer segmentation for marketing purposes, and sentiment analysis.

Related: Robot revolution: rise of'thinking' machines could exacerbate inequality As a senior adviser to Hillary Clinton, Alec Ross travelled the world with the remit of cataloguing the best examples of innovation the human race has to offer. His trips took him to Korea, the Congo and Silicon Valley (and far enough overall he has calculated, to take him from the Earth to the moon twice, with a side trip from the US to New Zealand), and left him with a concern that the rate of change could leave many behind. From robots entering the workforce and leading to the very real prospect of redundancy within a decade for the million employees of Taiwan's electronics manufacturing giant Foxconn to genetic engineering unleashing the possibility of designer babies, the power of technology to reshape the world is reaching historic levels. But the people who have the most to lose from those changes are often the ones who get the least warning. That, says Ross, was his motivation for writing The Industries of the Future, which looks at six of the biggest waves of change about to hit the world.

PAPIs '15, the 2nd International Conference on Predictive APIs and Applications, took place in Sydney, Australia and featured 4 research presentations. The corresponding papers were compiled into proceedings that were published in the Journal of Machine Learning Research (Volume 50 of the Workshop & Conference Proceedings series; you can also download the whole proceedings in a single pdf here). The first paper of these proceedings gives us a behind-the-scenes look at Microsoft Azure ML, an MLaaS environment for authoring predictive models, experimenting with them, running them on a cloud infrastructure and publishing them as web APIs. The Azure ML team presents design principles, challenges encountered and lessons learnt while building the platform. While it is common for ML practitioners to measure models' performance via predictions' accuracy, the second paper of these proceedings by Brian Gawalt of Upwork focuses on concerns of software engineers who are in charge of deploying in production and scalability: models' throughput and response time.

Twice a week, we'll be highlighting the latest bot and artificial intelligence news here on the Bot or Not Medium blog. This week, we have bots running countries, companies and social engagements. Will bots eventually rule the world, like in the movies? See below for a summary, and stay tuned for more bots news next week! Real-time bots have grown exponentially smarter in the last decade.

We live in a world of information abundance. The ability to create, produce, market and distribute content in almost any form has become very easy. So easy that a shocking amount of what we're reading is created not by humans, but by computer algorithms - perhaps even this post;). In the most recent post on strategy4telcomediatech I highlighted the need to consider the role that'bots' play particularly in automating conversational commerce - 'sales and service'. In this post I take a look at the use of'bots' or algorithmic content in digital media, how it is shaping our consumption habits, content creation and some of the capabilities required in both traditional and new media organisations. Algorithms and natural language generators have been around for a while.

The writing is on the LED screen: our jobs are ours for as long as the robots don't want them. But no one could have predicted they'd come for the gallery guides first. The world's first humanoid robot has started taking tours at the Art Gallery of Western Australia (AGWA) – two a month, for now. It seems a cruel twist of fate to have art history graduates among the first to be made redundant by robots; they have a hard enough time finding work as it is. But when I travel to AGWA to meet the future of work, it is plugged into the wall, charging.

It was as far back as 1991 – when Nirvana's Nevermind was riding high in the album charts, Robin Hood: Prince of Thieves was the must-see film in cinemas; and escalating tensions led to the first Gulf War – that we had a sneak preview of how networked connectivity would eventually impact our lives. That year, researchers at the University of Cambridge Computer Labs invented the world's first webcam to solve their coffee problem. Frustrated by pointless trips down the hall to the coffee machine only to find the pot empty, they set up a video camera near the machine and networked it to a computer. Now they could see whether the coffee pot was full or empty in real time. Today billions of devices across the world are networked, sharing what they see, hear and otherwise sense with the internet.

In a disused military aircraft hangar buried deep in a granite hillside, Johan Tofeldt flicks a switch on the future of mining. "Look, no hands!" he beams, as the truck lurches backwards and executes a precise reverse. "It's a little heavy on the clutch, but then it's not designed for driver comfort." The cheerful Swede is sitting in a standard Volvo FMX heavy duty truck, a haulage industry workhorse. But where once there was a narrow bed behind the seat there is now a laptop and a tangle of wires.