If you're interested in working with artificial intelligence (A.I.) and machine-learning platforms, chances are good you've heard of OpenAI, the non-profit "artificial intelligence research company" funded by tech luminaries such as Tesla CEO Elon Musk and venture capitalist (and Gawker bestie) Peter Thiel. OpenAI has a unique mission: develop open-source A.I. software that's friendly to humanity (as opposed to SkyNet). Earlier this year, the organization launched OpenAI Gym, a toolkit for building reinforcement learning (RL) algorithms, which tech pros in the space may find useful as they build out their own A.I. projects. Now comes the next OpenAI initiative: a breakdown of "concrete problems in A.I. safety." OpenAI researchers, in conjunction with colleagues from Google Brain, have issued a paper that delineates how machine-learning systems can potentially go haywire.

Equity deals to startups in artificial intelligence -- including companies applying AI solutions to verticals like healthcare, advertising, and finance as well as those developing general-purpose AI tech -- increased nearly 6x, from roughly 70 in 2011 to nearly 400 in 2015. Q1'16 saw a new peak in deal activity to the category. So far in 2016 (as of 6/15/2016), over 200 AI-focused companies have raised nearly 1.5B in equity funding. Our analysis includes all equity funding rounds and convertible notes. Deals and dollars reached a new high in 2015.

Programmers worldwide are preparing to welcome our new robot overlords, after the University of Reading reported on Sunday that a computer had passed the Turing test for the first time. But what is the test? And why could it spell doom for us all? Coined by computing pioneer Alan Turing in 1950, the Turing test was designed to be a rudimentary way of determining whether or not a computer counts as "intelligent". The test, as Turing designed it, is carried out as a sort of imitation game. On one side of a computer screen sits a human judge, whose job is to chat to some mysterious interlocutors on the other side.

Google's artificial intelligence projects have created a lot of headlines in recent months. From their DeepMind project beating champions of Alpha Go at their own game, to recent announcements Magneta and Springboard, not to mention driverless cars, its clear that AI and Machine Learning are central to Google's strategy across its vast portfolio. This week the company also announced the opening of a new Machine Learning R&D Centre in Europe. In a recent interview with Hollywood Reporter, Alphabet chairman Eric Schmidt played down the fears that surround advancements in AI: 'To be clear, we're not talking about consciousness, we're not talking about souls, we're not talking about independent creativity." However, being acutely aware of the concerns around intelligent technology, the company's AI research division Google Brain recently published an AI Precision Safety whitepaper.

This talk was given at a local TEDx event, produced independently of the TED Conferences. In his talk, Andre will explain the current and future impacts of Artificial Intelligence on industry, science, and how it will benefit and accelerate human progress. With almost 20 years of business experience, André has a track record of success with multiple multi-million dollar ventures in multiple industries that have spanned the continent. His latest company works in the field of Artificial Intelligence (AI) and has created a one-of-a-kind neural network that simulates a growing neocortex. This system of neurons uses evolutionary concepts to self-organize to complete tasks only previously achievable by humans.

One of the more surprising companies to show up in the AI Winners portfolio was Monsanto (NYSE: MON). Our models indicate that Monsanto stands out from its peer group in embracing deep learning technologies. The research is growing that deep learning platforms in general, and Google's Tensorflow in particular, could be transformative in computational biology. Computational biology, sometimes referred to as bioinformatics, is the science of using biological data to develop algorithms and relations among various biological systems. Since the dawn of modern agriculture, scientists have been experimenting with the manipulation of species through breeding techniques (which leads to the GMO debate).

You can add magazine editing to the list of use cases for IBM's Watson AI technology. The Drum has released the first magazine edited using artificial intelligence (AI) following a partnership with IBM Watson to create the special issue. The magazine ... includes a number of features that involved the analytical functions that IBM's AI can provide in order to examine the role such technology can provide to modern day marketers. Watson has also been trained to answer questions put to it by industry luminaries around the insights of advertising legend David Ogilvy and a number of predictions around potential winners at Cannes Lions this year have also been made by the AI. Gordon Young, editor-in-chief of The Drum, commented: "The Drum was given the opportunity to play with the IBM Watson system to help create this issue and, as a result, much of our content benefits from artificial intelligence. You can judge for yourself whether that is better than our normal intelligence.

Born and raised in India, Abe Ittycheriah, has had a fairly cosmopolitan upbringing. He's also lived in Mexico City and St. Johns in Newfoundland; he went to high school in New Mexico and did his PhD in Electrical Engineering at Rutgers University in New Jersey. While Abe confesses that he isn't multilingual, he is fluent in computer languages such as C, Perl, and others. Today, with almost 20 years of service under his belt at IBM Research working on speech, question answering, and machine translation technologies, he's part of a team using computer language skills to help teach Watson Korean, having also schooled Watson in Japanese, French, Italian, Spanish, Brazilian Portuguese, and Arabic. How does Watson expand its dictionary of foreign languages?

On February 27th 2016, an artificial intelligence named NCVSAI joined Numerai. His creator downloaded encrypted stock market data, trained a machine learning model, and began submitting stock predictions to Numerai. He uses an untraceable email address. On April 18th 2016, the Financial Times reported that the creator of NCVSAI works in genomics and biostatistics. At this time, NCVSAI had the most accurate model on Numerai.

AI (or, artificial intelligence) is a topic which is becoming increasingly prevalent. Whilst it is becoming more common within the market research industry, I don't believe it can't totally replace a researcher and how we think and work (thankfully or we'd all be looking for new jobs!); and on top of that I don't think that it should. Companies these days are generating more data than ever before so, don't get me wrong, anything that makes our lives easier is great -- and as Helene Protopapas discussed the fact that AI can help speed up research is advantageous to us all. However, there are some reasons why I strongly believe that AI isn't the'produce insight' button we've all secretly been wishing for and that you still need a researcher to deliver the insight that clients want and expect. As Harmony Crawford points out, if you just give someone a load of numbers, they'll drown in them.