June was kind to macro hedge funds. They were up more than 3 per cent, in what was their best month since 2010, according to data from Hedge Fund Research, buoyed by long positions on the yen and -- for the most fortunate -- long on both the yen and the dollar, and short sterling. Currencies and currency-related trades have been among the few bright spots for hedge funds recently (along with gold, which has risen more than 30 per cent since the end of 2015, according to Credit Suisse). Riding the yen and dollar up and taking on derivative trades, such as shorting Chinese companies that have lots of US dollar debt and dollar costs, have been among the few clear trends to follow. But generally, these are challenging times for the industry both in the short and longer term.

In this post, we are going to introduce you to the Support Vector Machine (SVM) machine learning algorithm. We will follow a similar process to our recent post Naive Bayes for Dummies; A Simple Explanation by keeping it short and not overly-technical. The aim is to give those of you who are new to machine learning a basic understanding of the key concepts of this algorithm. A Support Vector Machine (SVM) is a supervised machine learning algorithm that can be employed for both classification and regression purposes. SVMs are more commonly used in classification problems and as such, this is what we will focus on in this post.

Ed Felten, the deputy U.S. chief technology officer for the White House Office of Science and Technology Policy, says humans have two major responsibilities when it comes to the development and advancement of artificial intelligence. The first, he says, is "to make the benefits of A.I. a reality." The second: "to address the risks of A.I." Felten was speaking to a roomful of people at New York University's Skirball Center for the Performing Arts at AI Now -- a summer lecture series co-sponsored by the White House that sought to examine and discuss key issues related to the future of A.I. technology. A.I. is at a crossroads, AI Now co-chairs Kate Crawford (a researcher at Microsoft Research) and Meredith Whittaker (the founder and lead for Google Open Research), pointed out. Private and public sectors need to work together to create some sort of feasible A.I. policy.

I had a recent meeting with a person who was introduced to Machine Learning for the first time. It was interesting to know how someone totally new to the field would interpret what Machine Learning would be. He could instantly connect the term learning with what most Data Scientists would call Reinforcement Learning. A machine could observe phenomena and refine itself by itself is what he thought.It is weird that the one branch of Artificial Intelligence a layman could best connect to is the one least studied. I hope that Google Deepmind's recent work in Deep Reinforcement learning would change this.

We were flattered when this recent BBC News article about legal technology included our company TrademarkNow. However, we were somewhat surprised that it questioned the use of AI for legal technology. "There are pitfalls with this approach in such a heavily regulated sector," according to the article, and it raised the controversial issue of AI-driven technology offering legal advice - a big taboo and, in most jurisdictions, restriction in the legal field. Mikael Kolehmainen, our CEO and co-founder, is a former practicing trademark attorney, so we're very familiar with the intricacies of designing software that offers legal advice vs. software that provides a much-needed, powerful digital tool to help lawyers' productivity and efficiency. Our products have always focused on the latter, and we've always done our best to be as clear as possible about this.

When you consider all the amazing things artificial intelligence can be used for, making beer probably isn't one of them. Unless I'm misunderstanding something, I thought the whole point of beer was to let us worry less about intelligence. But while many of the things artificial intelligence can be used for are far more boring than beer – I can only watch people lose to a robot at Jeopardy so many times – so maybe IntelligentX is actually on to something: The company has claimed to produce the world's first AI brewed beer. "AI is about making decisions," said IntelligentX co-founder Dr. Rob McInerney in a promotional video, "and when you're brewing beer, there's a lot of decisions that need to be made." For the products his brand makes, those decisions are run through a complex machine learning algorithm that is able to use customer feedback to "brew new versions which are more finely tuned to people's tastes," according to the company.

Automation and artificial intelligence (AI) is a growing necessity and benefit in the business world. As we enter the Fourth Industrial Revolution, the technological advances at the centre of this great business change will differ greatly from past industrial leaps forward. People experience constant changes and refinement in their understanding, and their ability to respond to situations. With advances and the growth of Big Data, organisations now have a rich feed of business, customer and decision-making data to feed into platforms powered by machine-learning algorithms.

Notably, the company acquired Mojang for 2.5 billion in September 2015 and then later purchased MinecraftEdu in January this year with an announcement that Minecraft Education Edition would be available in summer. Originally designed as an internal tool, the company announced that it would be made fully available under an open-source license. Now, with a new name, the company has publicly unveiled Project Malmo, which has been described as "a platform that uses the world of Minecraft as a testing ground for advanced artificial intelligence research." It is comprised of two components: a mod for the Java version of Minecraft and additional code that enables AI agents to become aware of and operate within the environment.

Microsoft has made some interesting moves in the education space as far as Minecraft is concerned. Notably, the company acquired Mojang for 2.5 billion in September 2015 and then later purchased MinecraftEdu in January this year with an announcement that Minecraft Education Edition would be available in summer. Leading on from these acquisitions, a team within Microsoft developed Project AIX to simulate a world where an AI can be tested out without posing a risk to humans. Originally designed as an internal tool, the company announced that it would be made fully available under an open-source license. Now, with a new name, the company has publicly unveiled Project Malmo, which has been described as "a platform that uses the world of Minecraft as a testing ground for advanced artificial intelligence research."

A designer's guide to AI. Leveraging user centered design principles, the author rightly states that AI will enable designers to create bespoke experiences right out of the box for each user. Importantly, these experiences need to a) create emotionally-aware relationships with the user, b) respond to needs that haven't yet been explicitly expressed, c) prevent negative emotional responses when a user is upset with an AI-caused result and d) be sensitive to sociology. A list of further reading resources is included. There's been a resurgence of neuroscience-inspired AI architectures in the past few years, with Numenta being one of the leaders. Their VP of Research, Subutai Ahmad, argues that environmental sensory inference and behavior generation are intricately tied together, and critical for learning really general purpose representations.