However quickly artificial intelligence evolves, however steadfastly it becomes embedded in our lives -- in health, law enforcement, sex, etc. -- it can't outpace the biases of its creators, humans. Microsoft Researcher Kate Crawford delivered an incredible keynote speech, titled "The Trouble with Bias" at Spain's Neural Information Processing System Conference on Tuesday. In Crawford's keynote, she presented a fascinating breakdown of different types of harms done by algorithmic biases. As she explained, the word "bias" has a mathematically specific definition in machine learning, usually referring to errors in estimation or over/under representing populations when sampling. Less discussed is bias in terms of the disparate impact machine learning might have on different populations. "An allocative harm is when a system allocates or withholds a certain opportunity or resource," she began.

International Business Machines' (IBM) research laboratory in Zurich, Switzerland has developed a new generic preprocessing building block that could make the speed by which machine learning algorithms can absorb new information faster. Such development is expected to largely benefit the booming AI industry. According to IBM Zurich mathematician Thomas Parnell, they have developed a generic solution to the AI learning process with a 10 times speedup. "To the best of our knowledge, we are first to have generic solution with a 10x speedup. Specifically, for traditional, linear machine learning models -- which are widely used for data sets that are too big for neural networks to train on -- we have implemented the techniques on the best reference schemes and demonstrated a minimum of a 10x speedup."

Warnings about artificial intelligence launching World War III--including a few flares sent up by Elon Musk--are an unfair scourge on an AI sector that sees itself making life easier and helping traditional companies survive. That's the view of Chris Boos, chief executive officer of Germany-based software firm Arago, who told MarketWatch in an interview that anything produced by a process can, should and will be run by AI, allowing human beings to be the creative thinkers and doers they were designed to be. Arago advises mostly non-tech, established-economy Fortune 500 businesses on their AI adoption. "Within the next 2-3 years AI will be able to run any business process, which makes AI one -- potentially the only one -- defensive measure the established economy has against intrusion from the high-tech world," said Boos. For now, the sci-fi hyperbole can wait.

AI DETECTS DECEIT, AMPLIFYING SOCIAL INTELLIGENCE Researchers from Unanimous AI and Oxford University presented a research study at the Future Technologies Conference 2017 demonstrating that groups of networked users, when connected in real-time systems online, can detect deceit in human facial expressions with significantly fewer errors than individuals can detect on their own. The study -- Using Swarm AI to Detect Deceit in Human Faces -- engaged 168 randomly selected participants......

It seems like robots could learn from roaches. Researchers from the University of Cologne in Germany have discovered a change in roaches' gait that could help teach robots to walk. Animal's gait was previously only analyzed in fast mammals. Researchers have now found that arthropods that run quickly, like roaches, change their gait at mid-speed. Experts said the change in gait in roaches (Nauphoeta cinerea) is similar to the way horses switch from trop to gallop.

Microsoft has set up an internal "AI University" in a bid to help it overcome the skills shortage in the booming field of artificial intelligence (AI). Chris Bishop, the director of a Microsoft Research lab in Cambridge, UK, told Business Insider that the Microsoft AI University is one of several schemes Microsoft has implemented to address the lack of talent in the field of AI, where there's fierce competition between tech firms to hire the best people. "We have a thing called AI University, which is an internal education programme so that people who are incredibly smart and capable but trained in a different domain can quickly learn about machine learning both in a foundational sense but also in a practical sense of how to use it," said Bishop. When it comes to AI talent, Microsoft is competing with the likes of Amazon and Apple, who also have research offices in Cambridge, as well as DeepMind (owned by Google), Facebook, Twitter, and many others. The global battle for talent is raging because of the potential AI breakthroughs that bright minds stand to make in the next few years thanks to recent advances in computation power and the availability of vast data sets.

Deep learning is changing the way we use and think about machines. Current incarnations are better than humans at all kinds of tasks, from chess and Go to face recognition and object recognition. In particular, humans have the extraordinary ability to constantly update their memories with the most important knowledge while overwriting information that is no longer useful. The world provides a never-ending source of data, much of which is irrelevant to the tricky business of survival, and most of which is impossible to store in a limited memory. So humans and other creatures have evolved ways to retain important skills while forgetting irrelevant ones.

While machine learning and artificial intelligence (AI) have been used in supply chain applications for some time, there is an ongoing arms race to more effectively leverage both machine learning and artificial intelligence in demand planning solutions in new ways. Demand planning is one of the key applications in supply chain planning (SCP) suites. In ARC's recent global market study on this market, demand applications account for just under a third of a $2 billion plus market. And these applications are often the wedge purchase; the SCP solution that is first implemented by a company that then goes on to purchase other solutions in the suite. Machine learning works by taking the output of an application (for example, a forecast), examining that output against some measure of the truth, and then adjusting the parameters or math involved in generating the output (forecast), and seeing if the adjustments lead to more accurate outputs.

Bitcoin Press Release: Signals Network provides sophisticated machine learning algorithms to help cryptotraders build their investment strategies. November 22, 2017, Prague, Czech Republic -- Crypto trading strategies are about to become a lot smarter. Signals, a Prague based startup, is building a platform to connect traders with data scientists. Signals will have an interface where traders will be able to assemble machine learning-powered trading strategy with a few clicks. Signals is going to offer sophisticated machine learning algorithms to anyone, and its team wants to achieve that by building a network open to cryptotraders and data science developers.

It is that time of the year again and 2017 is over before we knew it. The Year of Intelligence brought us a lot of progress and change; from over-hyped ICO's to algorithms that created secret languages. As every year since 2012, I provide you with seven of the most important technology trends for 2018 to help you, and your business, prepare for the next year. One thing that we can state is that we are on our way to enter the 4th Industrial Revolution. Many of the technologies that have been promised for decades are constantly improving and are now reaching a point of maturity. Once that happens, it will radically change our societies, how we work and how we live. However, we are not there yet.