The tech world's book-nerd-in-chief wants you to add two books to your list of summer science reads. To get up to speed on artificial intelligence, Microsoft cofounder and philanthropist Bill Gates recommends Nick Bostrom's Superintelligence and Pedro Domingos's The Master Algorithm. Gates never misses an opportunity to plug books he likes, and yesterday (June 1) at Code Conference he took a detour from his and Melinda Gates's talk of philanthropy to recommend these two titles. "Certainly it's the most exciting thing going on," he said of artificial intelligence. "It's the holy grail, it's the big dream that anybody who's ever been in computer science has been thinking about."

The 1832 reform act was a response to social change in the evolving industrial landscape of pre-Victorian Britain. It introduced new parliamentary constituencies. It eliminated "rotten boroughs": small constituencies controlled by a handful of voters. It also gave the vote to those men with "freehold ownership of land". Votes to those men who own freehold on land is distant from universal suffrage, but the freehold land movement soon developed.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

Ecommerce companies have seen a slower quarter. According to Business Today, investors in India have turned cautious about placing big bets on ecommerce start-ups and the party is clearly over. The total VC money invested and the numbers of deals have dropped from a peak of 43 deals worth 831 million in March 2015 to just 24 transactions worth 112 million (Rs 730 crore) in less than a year according to Economic Times. In a similar state, brands from leading ecommerce markets like SEA and the Middle-East are looking at tighter marketing budgets and greater value for their mobile ad spends (the focus is on metrics like In-App user engagement and conversions).

A Liquid Big Data Platform uses cloud technology and agile ways of working to enable organisations to share and analyse large volumes of data together for their mutual benefit. If this model is scaled to a global level where any organisation (both large and small) anywhere in the world could use it collaboratively, what new business models could potentially emerge? Many organisations are already exploiting Big Data driven Machine Learning to improve their services in real time (such as search engine optimisation, medical diagnosis and fraud detection). In the so-called "arms race", big name tech, automotive and pharmaceutical companies are reportedly spending billions of dollars annually to realise their own IP in this area of Artificial Intelligence. A potential strategic implication is that these first movers will create barriers of entry that prevent other competitors (including small or medium sized enterprises) using AI as a disruptive source of rapid, responsive service design and organisational agility.

"The important thing is to understand what causes an engaged employee to become disengaged, and to focus action on reducing the rate this happens." Andrew Marritt (pictured right) is the founder of OrganizationView, a prominent people analytics firm based in Switzerland. He is also the creator of Workometry, a tool for capturing and understanding employee feedback. This technology uses machine learning techniques to gather and make sense of large volumes of employees' comments in real-time. In fact, the tool uses computational linguistics, a computer technique that identifies what employees talk about and makes sense of thousands of texts in different languages. Indeed, it has all the benefits that you would expect from a modern tool, such as the responsive design for the mobile age.

IBM is busy reshaping itself for the future, moving out of commodity hardware and chip manufacturing and further into higher end, value-added services. At the heart of the new strategy is the artificial intelligence machine Watson, around which IBM now intends to build a business in cognitive computing. The vision of the 105-year-old company is that Watson works in tandem with users, doing the heavy-lifting analytics, but ceding the judgement to humans. In particular, it wants to help make sense of the data now pouring out of the Internet of Things (IoT). As part of the remodelling, the IBM is making some large investments in Europe, in areas including cloud computing, artificial intelligence and data analytics.

Why did I bother writing this? Well, here is one of the most trivial yet life-changing insights and worldly wisdoms from my former professor that has become my mantra ever since: "If you have to do this task more than 3 times just write a script and automate it." By now, you may have already started wondering about this blog. I haven't written anything for more than half a year! Okay, musings on social network platforms aside, that's not true: I have written something -- about 400 pages to be precise. This has really been quite a journey for me lately. And regarding the frequently asked question "Why did you choose Python for Machine Learning?"

In Forrester's US B2B eCommerce Forecast: 2015 to 2020 they quote that "74% of B2B buyers research, at least one-half of their work purchases online. With that percentage nearly doubling to 56% by 2017, B2B sellers will see a significant volume of offline business move online in the next few years." Taking those facts further, at the Forrester Sales Enablement Forum, a study by Andy Hoar, Principal Analyst at Forrester, revealed that he expected 22% of B2B Sales jobs go by 2020. With Enterprise purchases taking place more and more online This means the traditional B2B sales person is being replaced by Search Engines, YouTube, websites etc. The Diagram above is Forester's view on what will replace the B2B Salesperson.

We're happy to announce Magenta, a project from the Google Brain team that asks: Can we use machine learning to create compelling art and music? Soon we'll begin accepting code contributions from the community at large. If you'd like to keep up on Magenta as it grows, you can follow us on our GitHub and join our discussion group. First, it's a research project to advance the state of the art in machine intelligence for music and art generation. Machine learning has already been used extensively to understand content, as in speech recognition or translation.