We study the automatic reply of email business messages in Brazilian Portuguese. We present a novel corpus containing messages from a real application, and baseline categorization experiments using Naive Bayes and Support Vector Machines. We then discuss the effect of lemmatization and the role of part-of-speech tagging filtering on precision and recall. Support Vector Machines classification coupled with non-lemmatized selection of verbs and nouns, adjectives and adverbs was the best approach, with 87.3% maximum accuracy. Straightforward lemmatization in Portuguese led to the lowest classification results in the group, with 85.3% and 81.7% precision in SVM and Naive Bayes respectively. Thus, while lemmatization reduced precision and recall, part-of-speech filtering improved overall results.

In the field of General Game Playing the imperfectinformationgames present a special challenge for researchers.In general the search space is larger, and thelack of information requires a different decision makingtechnique. A simple Monte Carlo sampling using a particlefilter may serve for the simple games, but this soonfails when more complex games are played. The HyperPlaytechnique was one such ”simple” player, soonenhanced to HyperPlay-II capable of handling the mostcomplex of games. However, this technique is very resourcehungry and may not scale well for larger games.We explore the scalability of HyperPlay-II for a varietyof imperfect-information games and test some perfectinformationpruning techniques to see if they will improveefficiency.

Today I was invited to give a KeyNote Lecture about Artificial Intelligence in the beautiful city of Zaragoza, by Javier Khunel the CEO of the main business school there, media group Heraldo and CaixaBank, to a diverse audience of business owners, entrepreneurs, c level execs, intrapreneurs and many more, at a great venue The CaixaForum building. I have been in the field for the last 21 years, and the last ones as clear advocate of AI and Deep Learning, with a company in the field, and advising Emotiv Inc the Leader in Brain Computer Interfaces about Data Science and Artificial Intelligence. So it is fair to say that I play in a field I know very well. Anyway I always get my facts and figures up to date, and to my surprise I discover an amazing fact: the father of Artificial Intelligence according to the MIT Technology Review is from my own backyard so to speak, from the country I was born Spain. He develop a machine in 1912 called "El Ajedrecista" or "The Chess Player" a very limited precursor of IBM's Deep Blue, and the first true chess computer, but by all means a pioneer (electro mechanical) work in the Artificial Intelligence field, he also build an Algebraic Formula Machine and many other mostly unknown marvels.

It represents a particular pure quantum state of a specific isolated system of one or more particles. By choosing a specific system of coordinates, e.g.

April 5, 2016 – NEW YORK, NY – Persado, the leading cognitive content generation platform, today announced that it has closed a 30 million Series C financing led by Goldman Sachs, with participation from all previous investors Bain Capital Ventures, StarVest Partners, American Express Ventures and Citi Ventures. Persado fuses language with data to transform people into the most effective communicators. The only existing solution of its kind, and one of few to successfully productize and commercialize cognitive computing technologies to date, Persado's platform employs natural language processing and machine learning algorithms to generate the precise combination of words, phrases and images that motivate any audience, at scale, in real time. "Persado is revolutionizing how organizations communicate by propelling creativity into the data-driven age, arming brands with'smart content' that resonates with any audience, every time, and inspires them to act," said Alex Vratskides, CEO and Co-Founder of Persado. "This latest round of funding will enable us to continue investing in distribution and product development. It will also accelerate our expansion into more digital channels and potentially other sectors beyond marketing, such as pharmaceutical adherence, fitness and personal motivation, civic engagement, human resources and more."

We have long deemed ourselves to be at the pinnacle of cognitive abilities among animals. But that is different from being at the pinnacle of evolution in a number of very important ways. As Mark Twain pointed out in 1903, to presume that evolution has been a long path leading to humans as its crowning achievement is just as preposterous as presuming that the whole purpose of building the Eiffel Tower was to put that final coat of paint on its tip. Moreover, evolution is not synonymous with progress, but simply change over time. And humans aren't even the youngest, most recently evolved species.

A new eGames international gaming tournament will make its debut in Rio during this summer's Olympic Games. The event, launched as part of this week's London Games Festival, offers medals and national pride rather than cash prizes for the winners. The competition, backed by the UK government, will be run by the new International eGames Committee (IEGC). Britain, Canada, Brazil and the USA are the only confirmed entrants so far with more expected to follow. In Olympic years, both summer and winter, the eGames will take place in the host cities - with future tournaments planned for Pyeongchang in 2018 and Tokyo in 2020.

Search engines on large e-commerce sites often spit up a lot of results, which is great if you want to browse, but otherwise annoying. Twiggle thinks it has the solution. Internet conglomerate Naspers agrees, because it has led the Tel Aviv-based startup's 12.5 million Series A. Yahoo Japan, State of Mind Ventures (a returning investor), and Sir Ronald Cohen also participated in the round. Twiggle, which has raised 14.7 million so far, will launch on several e-commerce sites in August. It hasn't revealed who its clients are yet, but they will include other Naspers portfolio companies.

Microsoft CEO Satya Nadella has reshaped the company since taking over two years ago. Windows is still important, but it's no longer the only platform that matters: Microsoft is releasing software and supporting app development for Apple's iOS, Google's Android, and even its old enemy Linux. The infighting and aggressive dismissal of competitors is mostly gone. And Nadella has embraced cloud computing -- the idea that some customers don't want to run their own technology but would prefer to outsource it -- turning Microsoft into the clear No. 2 in the category after Amazon. We caught up with Nadella fresh off the company's Build conference for developers last week in San Francisco and ahead of the new Envision conference for business leaders, which kicks off Monday in New Orleans. Matt Rosoff: There was a lot of talk last week at Build about chatbots and artificial agents and "conversation as a platform." That idea is not new, right? I think I heard Bill Gates talking about it 15 years ago.

Many retailers today employ inventory management systems based on Re-Order Point Policies, most of which rely on the assumption that all decreases in product inventory levels result from product sales. Unfortunately, it usually happens that small but random quantities of the product get lost, stolen or broken without record as time passes, e.g., as a consequence of shoplifting. This is usual for retailers handling large varieties of inexpensive products, e.g., grocery stores. In turn, over time these discrepancies lead to stock freezing problems (see Ref. [1]), i.e., situations where the system believes the stock is above the reorder point but the actual stock is at zero, and so no replenishments or sales occur. Motivated by these issues, we model the interaction between sales, losses, replenishments and inventory levels as a Dynamic Bayesian Network (DBN), where the inventory levels are unobserved (i.e., hidden) variables we wish to estimate. We present an Expectation-Maximization (EM) algorithm to estimate the parameters of the sale and loss distributions, which relies on solving a one-dimensional dynamic program for the E-step and on solving two separate one-dimensional nonlinear programs for the M-step.