Genpact announced that it has acquired TandemSeven, a Boston-headquartered company that delivers customer and digital experience innovation consulting using design thinking at its core. TandemSeven's ability to design better customer experiences complements Genpact's digital capability aimed at transforming business processes end-to-end. Terms of the deal are not disclosed. As part of its ongoing strategy to drive both digital-led innovation and transformation along with digitally-enabled intelligent operations for its clients, Genpact is investing in leading technologies that are reimagining customer experiences and transforming the way companies across many industries compete. The acquisition of TandemSeven advances that strategy and extends Genpact's ability to help its clients provide a seamless experience from the front office all the way to the back office.

USA TODAY goes to the Apple hands on room to check out the iPhone X, 8 and 8 Plus and Apple Watch. Phil Schiller, Apple's senior vice president of worldwide marketing talks about the new'True Depth Camera System' in the iPhone X that allows facial recognition. New theater named after its iconic co-founder. With its flying saucer-shaped campus Apple Park as a backdrop, Apple gave a glimpse of the future with iPhone X -- a shimmering, edge-to-edge glass model with OLED screen, facial recognition to unlock the phone, wireless charging and talking emojis. A link has been posted to your Facebook feed.

A Chicago startup has raised $2.5 million in hopes of using artificial intelligence and Big Data to help insurance companies make smarter underwriting decisions more quickly. DataCubes raised the money from Seyen Capital and MK Capital. The company was founded last year by Kuldeep Malik, a co-founder of mobile-advertising software company Persio (formerly called Iris Mobile), and Harish Neelamana, who previously worked for insurers Zurich and Allstate. "I wanted to create a Big Data solution to solve a tangible business problem; my friend Harish is an expert in commercial insurance," Malik says. They're trying to disrupt the commercial insurance business by using artificial intelligence and machine learning.

Cloudera said today as part of its second-quarter earnings report that it is acquiring Fast Forward Labs, a startup that gives companies the latest information on how to apply machine learning and AI to their businesses, as well as consulting. The company's stock has weathered somewhat of a beating since it went public, though it was able to beat Wall Street's expectations today. But the more interesting news is the acquisition of Fast Forward Labs, a company that specializes in consulting with larger enterprises about emerging trends in machine learning that can help their businesses grow. Cloudera specializes in operating on top of open-source technology, looking to deliver an enterprise-grade product for larger organizations. "On the way, we built a profitable company with real impact on our clients' products and businesses. I'm proud of what we've accomplished," CEO and co-founder Hilary Mason said in a post announcing the acquisition.

Oil prices have fallen dramatically over last few years, forcing some major oil companies to take drastic actions such as layoffs, cutting investments and budgets, and more. In view of falling oil prices and the resulting squeeze on cash flows, the oil and gas industry has been challenged to adapt and optimize its performance to remain profitable while maintaining a long-term investment and operating outlook. Currently, oil and gas companies find it difficult to maintain the same level of investment in exploration and production as when crude prices were at their peak. Operations in the oil and gas industry today means balancing a dizzying array of trade-offs in the drive for competitive advantage while maximizing return on investment. The result is a dire need to optimize performance and optimize the cost of production per barrel.

Optimus, a drone manufactured by Airobotics, the Israeli drone maker that says it has recently been granted the first certificate in the world to fly a fully automated drone, with no human operator, is seen during a demonstration for Reuters near their offices in Petah Tikva, Israel March 20, 2017. Picture taken March 20, 2017.

Keep in mind that notwithstanding the scale and pace of neurotechnology, the merger of human intelligence with AIM is still in its infancy - albeit an infant that we are vigorously feeding, both intellectually and financially, in order to bring it to maturity as soon as possible. While feeding this infant, we should not forget that humans are fiendishly complex and unpredictable. Human evolution was ignited by an uneven process of natural selection, based itself on greed and fear. Imagine merging these qualities with AIM. What would be the result?

The success of artificial intelligence (AI) algorithms hinges on the ability to gain easy access to the right kind of data in sufficient volume. Put more simply, AI depends on good data. Even Google--which is famous for the pioneering work in AI that underpins its standard-setting search-based advertising business--makes no bones about the critical role of data in AI. Peter Norvig, Google's director of research, has said: "We don't have better algorithms, we just have more data." Companies increasingly realize that data is critical to their success--and they are paying striking sums to acquire it. Microsoft's US$26 billion purchase of the enterprise social network LinkedIn is a prime example. But other technology companies are also seeking to acquire data-related assets, typically to acquire more than just identity-linked information from social media sources by focusing instead on vast troves of anonymized consumer data. Think, for example, of Oracle pursuing an M&A-led strategy for its Oracle Data Cloud data aggregation service, or IBM buying, within the past two years, both The Weather Company and Truven Health Analytics. Early returns for companies making such investments are promising. Still, to unlock the full value of AI algorithms, companies must have access to large data sets, apply abundant data-processing power, and have the skills to interpret results strategically.

Wizer's artificial intelligence technology can perform the work of human consumer research experts in building and analyzing consumer research, providing their customers with fast and affordable market insights AI-based SaaS consumer research company Wizer has announced the completion of the company's $4 million Series A Round. The funding was led by SOMV (State of Mind Ventures), a venture capital fund focusing on technology infrastructure. Nielsen Innovate, the early stage investment arm of Nielsen, participated in this round as well. To date, the company has raised $5.5 million, including $1.5 million in seed funding from YJ2, an investment fund backed by the Yahoo Japan Corporation, Nielsen Innovate, Barinboim Group, and the Israel Chief Scientist. Wizer provides marketers and agencies with comprehensive end-to-end market research solutions for brand positioning, product and concept testing, advertising effectiveness measurement, and more, utilizing proprietary artificial intelligence technology to deliver insightful client-ready research, quickly and affordably.

Strong interim results posted by Chinese smartphone camera makers may have proven yet again the future of camera manufacturing lies with lenses that are minuscule and A.I.-savvy. The landscape of the camera making industry has fundamentally changed as consumers are shelving their professional cameras and using smartphones to take pictures in recent years. Now as computer vision technology, which uses deep learning scheme to enable machines to understand digital images and videos, matures, smartphone camera makers, many of which are leading the pack in computer vision software development, could displace traditional camera makers' dominance in their own backyard. Companies such as Q Technology, Sunny Optical exemplified the rapid growth of smartphone camera makers in China. Both companies have posted strong first-half results this year, as traditional camera makers such as Canon see a decline in unit sales in digital compact cameras.