Twitter boss Jack Dorsey said the company has been too aggressive in banning right-wing activists from the site, despite some of them apparently being connected to harassment campaigns. Mr Dorsey and his company have been repeatedly criticised over the decisions it makes around who should stay on Twitter and who should be banned. Activists on both the left and the right have accused the site of hosting extremists, and having either too strict or too weak policies on banning users from the site. Now he has taken to the Joe Rogan Experience podcast for an interview with the comedian, during which he suggested the company could be more lenient with such bans in the future. We'll tell you what's true.

According to the Center for Disease Control and Prevention, over 610,000 people die of heart disease every year, which is the leading cause of death for both men and women in the U.S. Fortunately, scientists at IBM and pharmaceutical giant AstraZeneca are investigating a machine learning framework that can suss out early ASC warning signs. It's described in a newly published paper ("Outcome-Driven Clustering of Acute Coronary Syndrome Patients using Multi-Task Neural Network with Attention") on the preprint server Arxiv.org. The team sourced a dataset containing the age, gender, personal disease history, habits, laboratory test results, procedures, ACS type, and nearly 40 other characteristics of 26,986 adult hospitalized patients across 38 urban and rural hospitals in China, which they fed to a neural network -- i.e., layers of mathematical functions loosely modeled after biological neurons. Said neural network was architected to predict four factors simultaneously: whether they'd experienced a major adverse cardiac event, or MACE, prior to ACS; whether they'd received antiplatelet medicine to prevent blood clots from forming in the coronary arteries; whether they'd been given beta-blockers, which reduce blood pressure; and whether they were prescribed statins, a class of drugs that help lower cholesterol levels (and in turn prevent heart attacks and stroke). The paper's authors next employed k-means clustering -- a statistical technique in which data points are allocated to collections by similarities -- to organize the patients into seven groups based on the classification data obtained from the neural network.

Recently we've been seeing computers playing games against humans, either as bots in multiplayer games or as opponents in one-on-one games like Dota2, PUB-G, Mario. Deepmind(a research company) made history when the news that their AlphaGo program defeated the South Korean Go world champion in 2016. If you're an intense gamer, probably you must have listened about Dota 2 OpenAI Five match, where machines played against humans and defeated world top Dota2 players in few matches (If you are interested about this, here is the complete analysis of the algorithm and the game played by the machine). So here's the central question, Why do we need reinforcement learning? Is it only used for games?

Too often we're told that if Australia is to compete globally in developing AI products, Australian researchers and companies must not be fettered by human rights concerns, because other countries certainly aren't. China, for example, is investing heavily in AI technology such as facial recognition to support its "social credit score" system, which involves conducting precise and determinative surveillance of its citizens. In the context of a global AI arms race, it is argued, Australia can't compete with one arm tied behind its back.

Retail stores guard against theft by installing security cameras, training staff to spot a shoplifter, and employing security guards to patrol each store. Japanese startup Vaak believes it can instead predict shoplifting before it happens using artificial intelligence. As Bloomberg reports, Vaak's software works by tapping into the live security camera feeds a retail store has installed. It then monitors customers looking specifically at their body language. If there are signs that someone is overly nervous, looking around a lot, fidgeting, or generally restless, the system contacts staff via a smartphone app.

TOKYO - Toyota is teaming up with the Japan Aerospace Exploration Agency on a planned mission to the moon, with the auto giant expected to develop a lunar rover, officials and local media said Wednesday. It will be the car manufacturer's first full-fledged entry into space exploration, after the company jointly developed a small robot sent to the International Space Station. "We are planning to cooperate with Toyota in an exploration mission to the moon," said a spokesman with JAXA. Details will be announced by JAXA and Toyota on Tuesday next week when the space agency hosts a symposium in Tokyo, the spokesman said. Toyota also confirmed plans to announce a joint project with JAXA "on mobility and a space probe" but declined to comment further.

Dr. Topol is a paid adviser to two AI health companies, Verily Life Sciences, a Silicon Valley-based company that used to be part of Google, and Voxel Cloud, a China-based company. A lot of consumers and even health-care professionals are wary of artificial intelligence. They see it as something that depersonalizes medicine. I had the same kind of bias going into this field. I spent a few years of research to figure out where we could take AI.

Developers are leading the charge within organisations on AI. This session will explore the evolving technology and infrastructures and the challenges of implementing ML and DL techniques. We'll also take a look at some of the hottest tech breakthroughs in AI.

With the potential of AI permeating all aspects of our lives, the scope of the technology to help people with hearing disability has increased. Multiple wearable devices with artificial intelligence AI, ML and NLP embedded in it are available in the market, making the lives of people with hearing disability easier. Language translation and captioning: Tech giants are already working in the field as part of its larger corporate social responsibility programme. Microsoft, as part of its inclusive mission, has developed headsets with its embedded AI-powered communication technology, Microsoft Translator for hearing impaired. The system uses automatic speech recognition to convert raw spoken language – ums, stutters and all – into fluent, punctuated text.

Have you ever tasted – or even heard of – zhoug, Spam musubi or ube? Have you ever topped pizza crust with hazelnut-and-cocoa spread? If you're in the $5.75 trillion food business, you need to know about these and other up-and-coming trends if you want to give your customers what they crave. A new Israeli startup, Tastewise, leverages the power of data to bring fresh info on food trends to the folks responsible for determining which dishes or products to serve next. "When I started talking with executives in the food-and-beverage industry, both large brands and restaurant owners, I found a huge gap of data and tools to help make decisions based on data," says Tastewise CEO and cofounder Alon Chen, formerly Google's chief marketing officer for Israel and Greece.