Following this, the US government gave funding to McCarthy and fellow scientist Marvin Minsky to develop AI to help strengthen their stance in the Cold War with Russia. Efforts were made to use artificial intelligence to understand the patterns behind the Russian language, which they hoped would enable them to translate Russian documents on a larger scale more quickly. Government funding for AI was slashed as not enough progress had been made. In 1973, Professor Sir James Lighthill argued that machines would never be capable of achieving more than an "experienced amateur" level of chess. Deep Blue was capable of analysing up to 200 million potential positions a second.

United States and Chinese patent practitioners this week called for considerations to change patent legislation and allow patenting algorithms in the future. They spoke at a 30 May conference of the European Patent Office in Munich on "Patenting Artificial Intelligence." Please login or subscribe to read the full story.

When the last of 807 Woolworths stores across the UK closed in January 2009, budget shoppers and pick and mix fans mourned the end of an era. The closure of one of the country's iconic retail chains showed that high street shops were struggling to keep up with the pace of change, and that even industry giants were not immune from disruption. History repeated itself earlier this year when major toy store Toys R Us became yet another casualty. Heralding the death of the high street seems somewhat severe, but it's clear that incumbent retailers are facing a monumental challenge. In the face of ecommerce behemoths, (and not just Amazon), retailers are increasingly becoming technology companies in their own right.

Imec said at its annual event here that it is prototyping a deep-learning inference chip using single-bit precision. The research institute hopes to gather data over the next year on the effectiveness for client devices of the novel data type and architecture--either a processor-in-memory (PIM) or an analog memory fabric. The PIM architecture, explored by academics for decades, is gaining popularity for data-intensive machine-learning algorithms. Startup Mythic and IBM Research are designing two of the most prominent efforts in the field. Many academics are experimenting with 1- to 4-bit data types to trim the heavy memory requirements for deep learning.

Bullying is a serious issue in schools around the world, and the growing popularity of social media can make it harder than ever for victims to find safe spaces. Bullying can lead to low self-esteem, isolation and depression. Even though its effects are very serious, bullying goes unnoticed by a student's parents and teachers for an average of nine months. The goal for WatsomApp, a startup based in Spain, is to prevent and reduce harassment in the classroom. WatsomApp's founders knew that identifying and addressing bullying faster would improve children's learning experiences and quality of life.

He estimates that he talks or texts, on average, with each CEO in his portfolio three or four times a week. He visits potential customers with Jörg Lamprecht, CEO of Dedrone, a 75-employee drone-security firm. "It's not about the investments," Mr. Chambers says about his portfolio. "I want to first be a strategic partner with the CEO, where I am his or her most trusted adviser, mentor--a coach." Mr. Chambers is part of a wave of big-time CEOs and executives who, instead of more conventional retirements of just sitting on a couple of big-company boards, are embarking on second chapters as guiding lights on the startup scene.

We can see a lot of hype about AI and Machine Learning, and its potential to transform businesses. More and more сompanies are adopting machine learning solutions, setting up accelerators, opening R&D centers, and investing into startups. On the other hand, there are many companies that are using old-fashioned data analytics tools and labeling them as AI. Also,there is a large number of reports with AI market estimates and forecasts. However, it's challenging to get the right information on machine learning development that will actually work for your business. As a company that has delivered successful Machine Learning and Data Science solutions across such industries as Healthcare, Aviation, Media and Entertainment, and Technology, we've decided to talk with our experts and collect top guidelines for making your machine learning development project work.

AI (Artificial Intelligence) has been a hot topic in 2017, especially when looking at the future of Artificial Intelligence in Social Media. Investment has been growing in AI, and this is expected to grow by around 300% throughout the rest of this year. A third of the world's population is using Social Media, and AI is playing a huge part in how businesses are communicating with potential prospects online. This is very exciting for me, as I have seen the evolution of Social Media all the way from the Myspace/Bebo days, all the way to Facebook, Twitter, Instagram, Pinterest, Google and now SnapChat. AI is not going anywhere and in fact, it is going to become more widely used by businesses, which is why I wanted to write this article.

So it's a no-brainer for a company like Acuilae to try and find a solution to the dilemma we now face: who can and should bestow ethics on artificial intelligence? It's an important question, considering global finance, health systems, the justice system and much more will soon be managed by artificial intelligence -- if we're going to leave such crucial decisions in the hands of machines, we have to ensure they make the right decisions and, if possible, even fair and good ones. That's where ETHYKA comes into the picture. "Born from the desire to research and learn," according to Acuilae's CEO, Cristina Sánchez, ETHYKA is a project that looks to give AI morals so actions they perform will be based on ethical data. An expert in statistics, computer science and data science, thus far she's had a team of just four to help move the project forward and is now looking to attract investors through a funding round.

The UK is planning to leverage its NHS to improve its cancer diagnosis procedures, by combining its vast array of data with AI-based technologies to spot early signs of cancer. Combining medical records with population data, the hope is to prevent 20,000 cancer-related deaths annually, by 2023. It's ambitious, but the UK is well-placed in such projects. Critics will argue that the current government's economic austerity policies and its budget cuts to the regional NHS trusts are a bigger hindrance than a lack of AI, and that it should look to rectify those aspects before trying something shiny and new.