Our Seattle Accelerator's third batch taught us a thing or two about the machine learning and data science space. Now, as we kick-off our fourth batch, we're excited to put those learnings and insights to use to help the next generation of machine learning and data science startups. Over the past four months, we've traveled North America, talked to more than a dozen VCs and investors, sifted through hundreds of applications, and consulted our mentors and startup alumni in search of high-caliber, mature startups that are ready to scale up their businesses through enterprise customer access. As a result of these efforts, we've selected 10 later-stage startups to join our Machine Learning Accelerator in Seattle. Collectively, the chosen startups have received 5.3M in average funding with 3M average annual recurring revenue.

The OrCam MyEye is the latest device in assistive technology. It is able to turn any text into speech with a click of a button and uses artificial intelligence to recognise people's faces.

At the Disrupt SF Hackathon today in San Francisco, a team of seasoned software engineers unveiled Pepper the Inflight Service Bot, a robot flight attendant that doesn't hate picking up barf bags, can circulate in a plane even when there's turbulence, and can speak to passengers in their own language. The hacker team for the Inflight Robot included Peter Ma, Eddie Aguilar, Diego Gonzalez, Brian Cottrell and Savalas Colbert. According to Ma, the team came together and was inspired to build a robotic flight attendant at Disrupt based on the APIs and tools made available to them here. They intend to develop the Inflight Robot further after the event, adding in further language capabilities, and other features.

Inbenta, a San Mateo, CA-based enterprise-grade artificial intelligence solutions, raised 12m in Series B funding. The round was led by Level Equity, with participation from Amasia and Scale Capital through its Amérigo Chile fund. In conjunction with the funding, founder and partner George McCulloch and Amasia chairman Ramanan Raghavendran joined Inbenta's board of directors. The company intends to use the funds to expand sales and marketing, and to further drive product development for its technology. Founded in 2005 by Jordi Torras, CEO, Inbenta has developed natural language processing (NLP) technology that powers search, chatbots, and self-service solutions for customer support and e-commerce.

Artificial intelligence technology is in the process of transforming our lives. We already have robotic vacuum cleaners, smart thermostats, and autonomous cars. And over the next 15 years, AI will continue to make inroads into nearly every area of our lives -- from education and entertainment to healthcare and security. But are we ready for that? Creating true AI is a notoriously difficult task.

Robotics and Artificial Intelligence are revolutionizing cars, investing, defense, and manufacturing. The Global X Robotics and Artificial Intelligence Thematic ETF (BOTZ) invests in companies with high exposure to the Robotics and Artificial Intelligence theme.

Engineers from Caltech have developed a method that uses data from satellite and street-level images, such as the ones that you can see in Google maps, to create automatically an inventory of street trees that cities may use to better manage urban forests. Their work is described in the proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, which was held in Las Vegas this summer. "Cities have been surveying their tree populations for decades, but the process is very labor intensive. It usually involves hiring arborists to go out with GPS units to mark the location of each individual tree and identify its species," says senior author Pietro Perona, the Allen E. Puckett Professor of Electrical Engineering in the Division of Engineering and Applied Science. "For this reason, tree surveys are usually only done every 20 to 30 years, and a lot can change in that time."

Microsoft has chosen the 10 machine learning and data science companies that will make up the fourth class of its Seattle Accelerator. The startups hail from all over the U.S. and focus on a variety of industries. All are later stage companies, and Microsoft said they have a collective average of 5.3 million in funding and 3 million in annual recurring revenue. As part of the program, startups will have access to individualized coaching and work with Microsoft's Sales and Azure Machine Learning teams to scale their businesses.

Useful quantum computers are closer to becoming a reality as some of the world's biggest corporations try to bring the technology from the lab into the practical world. A quantum computer utilizes subatomic particles called qubits to speed up the solving of complex computations. Near-term expectations for quantum computers range from solving optimization problems to quantum-encrypted communications, and more. With the help of CB Insights' investment, acquisition, and partnership data, we identified 18 corporate groups involved in the development of commercialized quantum computing hardware and software. They are a diverse group of players, ranging from tech industry behemoths to defense contractors to national telecommunications companies.