IN 2004, IN THE MAZE-LIKE aisles of Stanford's computer science department, I spoke to a man who resembled Santa Claus. This bearded man was John McCarthy, who coined the term Artificial Intelligence in the 1950s and was one of the founding fathers of Artificial Intelligence, along with Marvin Minsky. McCarthy spearheaded the effort for some time, including creating the language Lisp for the purpose of AI, among other innovations like time-sharing for computers, garbage collection, and lambda calculus. I was a graduate student studying natural language processing, and AI wasn't as cool as it is today. Neither was natural language processing.

When you shoot with the iPhone's built-in Camera app, there are various ways to tweak focus and exposure, both before and after you hit the shutter. You might first tap and hold or swipe to adjust and lock focus and exposure. After the shot, you have options for adjusting saturation, contrast, sharpness, and more. Microsoft Pix (free on the iTunes Store), a photo and video shooting and editing app for iOS, doesn't want you to work that hard. It offers an effortless point-and-shoot alternative to the iPhone Camera app with a promise of superior results.

MUMBAI: In order to understand its effects on the finance and accounting industry, Chartered Institute of Management Accountants, (CIMA) the world's leading and largest UK based professional body, conducted a global survey across select European, African and Asian countries. A majority of financial leaders are of the opinion that artificial intelligence helps enhance efficiency and accuracy of the business. This recent global study reveals that more than two-thirds (64%) of finance professionals from India encourage increasing automation as it saves time, money and helps ease the indecision process in their organisations. At a global level, Zimbabwe tops the chart with (75%) professionals supporting automation, followed by China with a 67% of acceptance. This indicates that accountants regard the impact of new technologies as an opportunity rather than a threat.

What if you could grow food in your backyard with little to no understanding of gardening? A new robotic system may make this a reality for everybody. Farmbot Genesis is an open source, autonomous farming system that is supposed to fit virtually anyone's backyard, greenhouse or rooftop.

PreSeries, a joint venture between BigML and Telefónica Open Future_, is an automated early stage investing tool built on top of the BigML Machine Learning platform. The ever increasing data available about companies, people, successes and other events, can be harnessed by the PreSeries Machine Learning technology to detect patterns that help investors identify new potential investments, track the performance of their portfolios, or see the potential impact of certain decisions, such as new hires, company location, etc. Please visit www.preseries.com for further details.

I spent the last day or two figuring out node.js and how to write node.js Now that both server and client side can use the same consistent set of machine learning algorithms written in pure javascript, for both training the algorithm, and for getting it to perform some task, we can think of interesting ways to distribute computational intensive training tasks from a server to many different browser client sessions. It may be possible to get browsers visiting a site to donate their browser sessions for the purpose of training a large machine learning algorithm on a small subset of a training data set, like a browser-based SETI@home. Even though a single browser running javascript will be a lot slower than a high performance dedicated machine, tens of thousands of distributed collaborating clients, even smartphone browser clients, may be a force to be reckoned with. Distributed training of neural networks is still an active area of research.

In part 1 I gave a brief introduction to classification. Just to recap, classification is the problem of identifying which group a piece of data belongs to. It's an example of supervised learning because the classifier predicts the classes based on the training data fed to it. An example of classification is finding out whether an email is spam or not. More formally, classification is about finding out a model that distinguishes one class of data from another so as to predict the class of data whose class is unknown.

The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery will take place in Riva del Garda, Italy, during September 19–23, 2016. This event is the premier European machine learning and data mining conference and builds upon a very successful series of 26 ECML and 19 PKDD conferences, which have been jointly organized for the past 15 years.

As odd as it sounds, chatbots can let customers communicate in a natural way with companies and greatly enhance the experience. As customers increasingly demand a better experience when they interact with companies, including insurers, help is coming from a counterintuitive source. It turns out that one of the best ways to be more personal is through… robots. More precisely, the answer is turning out to be chat robots, or "chatbots." People don't like having to phone call centers and wade through that phone tree -- "Para continuar en espanol, oprima uno… For billing, press 2; for…."

The dawn of the internet at the end of the 20th century marked one of the first significant shifts seen by the recruiting industry in decades. Online job boards, resume databases, and applicant tracking systems rapidly replaced Rolodexes, newspaper classifieds, cold calling, and piles of paper resumes. The abandonment of the archaic "head hunter" model significantly broadened the candidate pool and fundamentally changed the way recruiters sourced talent prospects. The digital generation of the 2000s refined this important evolutionary step. LinkedIn, launched in 2003, brought resumes and talent profiles onto a universally searchable database.