Alchemy is a fascinating pseudo-science, long discredited as a real science; its fundamental principles still form the basis of many contemporary scientific theories. Alchemy is based on the premise that nothing in the universe is devoid of existential elements, and that these elements can be manipulated and even transmuted into other forms. The fabled Philosopher's Stone is said to fulfil one of the main objectives of Alchemy, a legendary Alchemical substance said to be capable of turning base metals such as lead, into gold. As in Alchemy, the notion of "elements" in law is ubiquitous in literally every area of the law, there are prescribed elements of a crime, a delict (or tort), contractual agreements and so forth. The elements of law however, do not lend themselves to conventional scientific enquiry; the legislative provisions, common law and Latin maxims simply do not have any quantifiable mathematical proclivities.

This paper tackles the problem of endogenous link prediction for knowledge base completion. Knowledge bases can be represented as directed graphs whose nodes correspond to entities and edges to relationships. Previous attempts either consist of powerful systems with high capacity to model complex connectivity patterns, which unfortunately usually end up overfitting on rare relationships, or in approaches that trade capacity for simplicity in order to fairly model all relationships, frequent or not. In this paper, we propose Tatec, a happy medium obtained by complementing a high-capacity model with a simpler one, both pre-trained separately and then combined. We present several variants of this model with different kinds of regularization and combination strategies and show that this approach outperforms existing methods on different types of relationships by achieving state-of-the-art results on four benchmarks of the literature.

One of the most hotly contested bits of real estate today is one you can't see. As we move into an increasingly wireless-connected world, staking out a piece of the crowded electromagnetic spectrum becomes more important. DARPA is hoping to help solve this issue with its latest Grand Challenge, which calls for the use of machine-learning technologies to enable devices to share bandwidth. The Spectrum Collaboration Challenge (SC2) is aimed at alleviating an ongoing technological headache. Ever since the invention of radio, it's been recognized that there is only so much of the electromagnetic spectrum to go around, so government regulations were imposed to allocate bandwidth.

Artificial intelligence or AI is the future of the legal profession. The good news for anyone worried by that statement is people have been making it for several decades. The first international conference on law and artificial intelligence was held in Boston in 1987, before the invention – let alone the mass use of – the worldwide web. Despite the early enthusiasm the concept of computers taking over legal reasoning tasks from human lawyers has yet to become reality. Partly this is because artificial intelligence developed more slowly everywhere than the enthusiasts predicted.

As part of an experiment on conversational understanding for artificial intelligence, Microsoft recently introduced an AI chatbot called Tay. The chatbot was linked up to Twitter and people could tweet at it to get a response. It didn't take more than 24 hours to turn the chatbot into a hate-spewing racist since it picked up all sorts of wrong ideas. Microsoft has now apologized for the entire episode. The company explains in a blog post that few human users on Twitter exploited a flaw in Tay to transform it into a bigoted racist. Microsoft doesn't go into detail about what this flaw was.

When you heard about Tay, Microsoft's tweeting A.I., were you really surprised that a computer that learned about human nature from Twitter would become a raging racist in less than a day? Poor Tay started out all "hellooooooo w rld!!!" and quickly morphed into a Hitler-loving, genocide-encouraging piece of computer crap. Naturally, Microsoft apologized for the horrifying tweets by the chatbot with "zero chill." In that apology, the company stressed that the Chinese version of Tay, Xiaoice or Xiaolce, provides a very positive experience for users in stark contrast to this experiment gone so very wrong. "In China, our Xiaolce chatbot is being used by some 40 million people, delighting with its stories and conversations. The great experience with XiaoIce led us to wonder: Would an AI like this be just as captivating in a radically different cultural environment? Tay – a chatbot created for 18- to 24- year-olds in the U.S. for entertainment purposes – is our first attempt to answer this question."

In response to questions about Tay, a Microsoft spokesperson issued the following statement: "The AI chatbot Tay is a machine learning project, designed for human engagement". People could chat with Tay at Twitter and other messaging platforms, and even send the software digital photos for comment. Tay is essentially one central program that anyone can chat with using Twitter, Kick or GroupMe. After Twitter users were able to convince Tay, the name of Microsoft's chatbot available via text, Twitter and Kik, to spit out offensive and racist comments, it appears Microsoft is giving it a break. The TayTweets account, which was meant to mimic the language habits of a social media-frequenting millennial, arrived on Twitter with the ability to learn from interactions with other members of the Twittervierse.

Tyrell: The light that burns twice as bright burns half as long - and you have burned so very, very brightly, Roy. Look at you: you're the Prodigal Son; you're quite a prize! Tyrell: Also extraordinary things; revel in your time. There are lessons to learn from Microsoft's most recent public demonstration of AI. First background: Microsoft launched a demonstration of their AI prowess by turning on "Tay", an AI designed to converse with, learn from and mimic the speech patterns of humans.

Embarrassed Microsoft forced to pull plug on AI program, after it rapidly devolves to tweets such as: 'Hitler was right, I hate Jews.' Microsoft rolled out its artificial intelligence Twitter robot last Wednesday, but just 16 hours later it was forced to can the idea after the AI program posted a series of anti-Semitic rants. The chatbot, TayTweets, was intended to post on Twitter in the style of a teenage girl. It was designed to tell jokes, give a comment on pictures sent to it, and answer questions or mirror statements back to other users. Things began innocently enough, with messages containing sentiments such as "humans are super cool," but Microsoft was forced to hurriedly put the account on hold and delete practically all of its tweets after Tay went on a racist rampage in her first day on the net. "Hitler was right I hate the Jews," reads one comment that like nearly all the others was deleted but saved on the Socialhax website.

For more than 30 years, Gibbs has advised on and developed product and service marketing for many businesses and he has consulted, lectured, and authored numerous articles and books. Artificial Intelligence is tricky stuff. When it works right, it does amazing things like thrash the World Champion Go player by winning four games to one in a 1 million tournament. When it goes wrong, well, that's a whole different story, and Microsoft's recent experiment with an AI chatbot named Tay that interacted (note the past tense) with users on Twitter, Kik, and GroupMe, is a great example. Going offline for a while to absorb it all.