The tools, announced at Amazon's annual cloud event in Las Vegas, aim to help the company's cloud customers incorporate functionality such as natural language processing, but without long waits often associated with AI-related projects. Amazon says it is making this possible by integrating machine learning into the two new stand-alone services. "There's no machine-learning expertise required for either of these services. They're just plug and play. You don't have to get into all the weeds and get the training data and label the data and all those sorts of things," said Matt Wood, vice president for artificial intelligence services at Amazon Web Services.

Its creator says it can predict whether a baseball pitch will land inside or outside of the strike zone. Tipper was developed by Nick Bild, a serial creator who seems to have an unquenchable thirst to create and innovate. He makes apps, trains neural networks, and literally has a gold badge in'problem solving' on HackerRank. He says he was inspired to build Tipper while sitting idle in traffic, pondering the world from an engineer's point of view. A modified Nerf tennis ball launcher is programmatically fired with a solenoid. A 100FPS camera is pointed in the direction of the launcher and captures two successive images of the ball early in flight.

The city of Portland, Oregon, is considering a unique ban on facial recognition software that could limit how private companies use it. Current bans on facial recognition technology, such as ones in San Francisco and Oakland, California, only affect city agencies such as police departments. If the Portland City Council passes the pending legislation next year, officials may copy those efforts and add private retailers and airlines to the ban. Portland Commissioner Jo Ann Hardesty is spearheading the proposed ban, citing concerns of privacy, consent and civil rights. "The technology is currently extremely biased against people of color and women," Hardesty said at a September work session on the ban.

Amazon Web Services (AWS) has packaged up another in-house Amazon capability and made it available to customers, having announced Contact Lens for Amazon Connect on Tuesday. CEO Andy Jassy has touted that Contact Lens for Amazon Connect -- the company's omnichannel cloud contact centre service -- will stitch together new abstractions for machine learning so AWS customers can have an easy to consume function. "Amazon Connect is one of the fastest growing services in the history of AWS … off to a blazing start," he said during the day one keynote of AWS re:Invent in Las Vegas. "Using the same customer service technology Amazon has used … it's really easy to use." According to Jassy, Connect is the first call centre in the cloud with machine learning in mind.

The Internet of things (IoT) has a significant potential to fall into the endless pit of a buzzword- vagueness, and it merely is an ecosystem of various kinds of objects that are connected through the Internet. These kinds of objects ranging from cell phones and wearables to machines, generate a constant and massive amount of data every day. The artificial intelligence (AI) also often falls into the same trap. The goal of artificial intelligence in the new IoT scenario is not only to use the humongous data to extract meaningful insights but also to help IoT integrated setups to derive higher value. It implies the machine's intelligence, where the device gains the capabilities of simulating a real human brain.

GitGuardian, a cybersecurity platform that helps companies detect sensitive data hidden in public and private code repositories, has raised $12 million in a series A round of funding led by London-based Balderton Capital, with participation from GitHub cofounder Scott Chacon and Docker co-creator Solomon Hykes. Founded out of Paris in 2017, GitGuardian scans all GitHub public activity in real-time to identify private data such as database login credentials, API keys, cryptographic keys, and more. The company works with more than 200 API providers, spanning payment systems, cloud services, messaging apps, crypto wallets, and more to ensure private information that does leak out into the public domain is identified swiftly and the company is notified. The French startup said that it has sent out more than 400,000 alerts since its inception. The type of private data that GitGuardian is looking to protect is what is known in the industry as "secrets," and includes anything that can be used by unauthorized third-parties to access a system (e.g. a cloud or database) -- such as passwords and API tokens.

LONDON – From the Luddite movement in the early nineteenth century to the writings of prominent economists like John Maynard Keynes and Wassily Leontief generations later, the prospect of automation has always raised serious concerns about jobs. Keynes and Leontief doubted there would be enough jobs left for workers to do. The impact of today's digital technologies on the labor market raises three questions. Will there be enough jobs for workers to do? Where will these jobs be?

A robot arm strikes a tennis ball, serving it at 220 miles per hour. From the opposing side of the court, another robot returns the serve and the two machines engage in a 427 stroke rally. An automated umpire decides, instantly, that the ball was out by a hair's breadth. This is the hypothetical, somewhat dystopian image conjured by Chris Brauer, director of innovation at the Institute of Management Studies at Goldsmiths, University of London, at a recent panel discussion about the use of data analytics and technology in tennis. While steeped in tradition, tennis has embraced technology on multiple fronts: coaching, umpiring and fan experiences.

Communication networks have evolved drastically in the last decade. Whereas networks largely used to provide dumb connectivity pipes interconnecting its end users, current network technology is tightly interconnected with the cloud, leading to a plethora of advanced services, a drastic increase in network usage, and strongly evolved data and control planes. Software-based functionality is now deeply changing the nature of both the control and data plane of our networking infrastructure through SDN and NFV technology respectively. This has introduced tremendous programmability and flexibility but also a range of uncertainties in the performance, security and management of our networks. Less functionality is now specified in standardized protocols or hardcoded in our data plane hardware.

As a birthplace for global tech disrupters, Europe -- home to the likes of Spotify and Skype -- still lags behind the US and China and their juggernauts such as Apple, Alibaba, Google and Amazon. The continent is also falling behind North America and east Asia in artificial intelligence, as measured by investment and patent activity. A fragmented digital market, limited risk capital and onerous bureaucracy are several reasons cited for Europe playing catch up to Silicon Valley. However, Europe's more regulated, activist political culture has proved to be an asset, as highlighted by many of the region's start-ups tackling social-services issues in the "tech for good" sector and working directly with central and local governments in "govtech". Europe's start-ups reflect its public service traditions, says Paul Duan, founder of Bayes Impact, a non-profit group that built an AI -powered job counsellor.