SoftBank Group Corp. has secured pledges from Microsoft Corp. and other investors of around $108 billion for a second Vision Fund aimed at investing in technology firms. The Japanese conglomerate itself plans to invest $38 billion in the fund, it said in a statement. Others set to join include Apple Inc. and Taiwan's Hon Hai Precision Industry Co. (Foxconn) -- both investors in the first fund. Notable for their absence on the list of state and corporate backers were the sovereign wealth funds of the two countries that formed the cornerstone of its first fund: Saudi Arabia and Abu Dhabi, as well as investment bank Goldman Sachs. SoftBank said it is still talking to potential investors and that it expects the fund's anticipated capital to grow.

A British teenager whose obsession with video games caused years of arguments with his despairing mother has won almost £1m and become an overnight star after finishing second in the hugely popular Fortnite World Cup. Essex schoolboy Jaden Ashman, 15, competing under the name Wolfiez, finished runner-up with his Dutch team-mate Dave John (Rojo) in the duos event, landing a $2.25m (£1.8m) prize fund, which they will split. Ashman was one of several UK gamers to fly to New York to take part in the tournament where 100 competitors, many aged between 12 and 16, battled it out for a total prize pot of $30m – the largest ever for an esport event. While many of those taking part were professional Fortnite gamers with legions of fans, Ashman was a relative unknown with only a few thousand followers on social media. The teenager put his success down to the many hours he has devoted to Fortnite since the day it came out in September 2017, sometimes playing it for up to eight hours a day.

Almost 70,000 gamers are set to crowd Los Angeles Convention Center for the annual E3 expo, a highlight on the video game calendar. Some of the top attractions are esports, with competitions throughout the week attracting fans in droves. Inside an 8,000-square-foot state-of-the-art esports training facility in Santa Monica, California, the five players who compete in "League of Legends" for Team Liquid push their bodies to the limit. "I play eight-to-12 hours a day, not including our games on the weekends," Jake Puchero tells me over the phone. It takes a lot of mental focus and physical stamina." Puchero, better known by his in-game name "Xmithie," is a 28-year-old professional "League of Legends" player for Team Liquid. For those not following esports, "League of Legends" is an online multiplayer game that pits two teams of five players against each other in an online battle arena, and it's one of the most popular sporting events on the planet. More people now watch the League of ...

BANGKOK - The launch of facial recognition technology at two Indian airports and plans to place it in police stations have stoked fears over privacy and increased surveillance among human rights groups in the country. The "paperless biometric technology" launched in Bengaluru airport this week identifies passengers by their face, doing away with the need to present boarding passes, passports and other identity documents, according to a statement from the airport in India's tech capital. Another airport in the southern Indian city of Hyderabad is also testing facial recognition technology this month. While airlines, airports and the companies developing the software promise greater security and increased efficiency, some technology analysts and privacy experts say the benefits are not clear, and come at the cost of privacy and greater surveillance. This is particularly true of India, which does not have a data protection law or an electronic surveillance framework, said Vidushi Marda, a lawyer and advisor at human rights group Article 19.

In this post, I'll take a look at how you can compare regression models. Comparing regression models is perhaps one of the trickiest tasks to complete in the "comparing models" arena; The reason is that there are literally dozens of statistics you can calculate to compare regression models, including: This list isn't exhaustive--there are many other tools, tests and plots at your disposal. Rather than discuss the statistics in detail, I chose to focus this post on comparing a few of the most popular regression model evaluation techniques and discuss when you might want to use them (or when you might not want to). The techniques listed below tend to be on the "easier to use and understand" end of the spectrum, so if you're new to model comparison it's a good place to start. The first question you should be asking is: How well do I know my data?

The recent debate between the Associated Press and Facebook about the success of removing content posted by terrorist organizations should be a wake-up call concerning content moderation capabilities on these kinds of platforms. Facebook data indicates the removal of 99% of terrorism content, while AP contends that Facebook's success is only 38%. The point here is that machine learning adds a limited capability to human content mediation. The current state of the art in machine learning in this area is far from meeting expectation and is a fantasy, created around the magical tool of artificial intelligence (AI). Terrorist networks will continue to exploit advanced technology in the areas of social network mapping and terrorist recruitment to benefit from the AI arms race.

In a bid to promote democratisation and to fill in the gaps in domain expertise, AutoML or automated machine learning came to the fore. There is a lot of talk about democratisation of data science nowadays. But, who is doing what? Datasets are being open-sourced by tech majors along with frameworks and platforms that can assist the user in deploying pretrained models. Auto-Keras is an open source software library for automated machine learning (AutoML).

While it's not unimportant, a lot of the groundwork when developing a new fragrance is done by evaluating data, and that's something artificial intelligence is highly qualified to do. In a partnership between IBM Research and Symrise, a global producer of fragrances and flavors based in Germany with clients such as Estee Lauder, Donna Karan, Avon, Coty and more, the first AI-developed scent is now available for purchase in Brazil. Philyra became the artificial intelligence (AI) apprentice IBM created that perfumer David Apel worked alongside to create two new fragrances for Brazilian cosmetics company O Boticário in time for the country's Valentine's Day holiday this year. They were specifically looking for a fragrance to sell to Generation Z and millennials who they knew would be intrigued by a fragrance created by AI. This collaboration officially launched AI into the fragrance industry.

Harry Potter fans will remember Professor Albus Dumbledore's nifty memory reviewer - the Pensieve. Throughout the series, several characters used it to store their memories and rewatch them to derive insights. Taking this concept from fiction to reality, Gaurav Shrivastava, Co-founder of Zimmber, built a transparent data machine - called Pensieve - AI with Co-founder Prahlad Routh. The two were ecstatic about implementing text analytics in the legal domain and the ample growth of Machine Learning (ML) and Artificial Intelligence (AI). The duo identified that legal tech could be a thing if Natural Language Processing (NLP) is used rightly, and started Pensieve in Mumbai in 2017.

While it's not unimportant, a lot of the groundwork when developing a new fragrance is done by evaluating data, and that's something artificial intelligence is highly qualified to do. In a partnership between IBM Research and Symrise, a global producer of fragrances and flavors based in Germany with clients such as Estee Lauder, Donna Karan, Avon, Coty and more, the first AI-developed scent is now available for purchase in Brazil. Philyra became the artificial intelligence (AI) apprentice IBM created that perfumer David Apel worked alongside to create two new fragrances for Brazilian cosmetics company O Boticário in time for the country's Valentine's Day holiday this year. They were specifically looking for a fragrance to sell to Generation Z and millennials who they knew would be intrigued by a fragrance created by AI. This collaboration officially launched AI into the fragrance industry.