We uncovered the following insights and trends: • Semi-autonomous vehicles are the stepping stone to fully autonomous vehicles. Most car manufacturers and technology companies have taken Tesla's lead and are offering features like self- parking, adaptive cruise control, emergency braking and semi-hands off driving in highway/interstate conditions. Semi-autonomous features help consumers become comfortable with the idea of robots taking the wheel.

Salesforce ( CRM) continued its stellar performance in 2016, with its top line growing at more than 25% in the first three quarters of the fiscal year and beating market expectations. Additionally, the company's added focus on improving its bottom line started to pay dividends, with its earnings per share for the first nine months growing appreciably from -$0.03 in 2015 to $0.34 in 2016. Moreover, during the year, Salesforce made a number of acquisitions and made a push in the e-commerce and artificial intelligence domains, opening up avenues for further growth. Apart from this, the company also affirmed its goal of $10 billion in revenues, which it expects to achieve by the end of next year. Despite a good performance in the first three quarters of the year, Salesforce's stock is currently trading 12% lower than its price in January, owing to a tougher market environment and relatively soft performance in the second quarter.

Amazon's 2016 has been record breaking on many fronts. The company recorded its sixth consecutive quarterly profit (previously, it mostly hemorrhaged cash). Meanwhile, this year marked Amazon's growing strength in hardware with its hit Echo home automation hub Amazon Echo, and its companion voice assistant Alexa. The company has also become force in entertainment, debuting a line of hit original shows through its Amazon Video Prime service. It's hard to imagine how Amazon could top 2016, but here are some likely moves by the Seattle-based Goliath in 2017: To save money over the past year, Amazon has been seeking to take over more shipping duties from the likes of UPS and FedEx by leasing trucks, planes, and ships.

Salesforce (NYSE:CRM) continued its stellar performance in 2016, with its top line growing at more than 25% in the first three quarters of the fiscal year and beating market expectations. Additionally, the company's added focus on improving its bottom line started to pay dividends, with its earnings per share for the first nine months growing appreciably from -$0.03 in 2015 to $0.34 in 2016. Moreover, during the year, Salesforce made a number of acquisitions and made a push in the e-commerce and artificial intelligence domains, opening up avenues for further growth. Apart from this, the company also affirmed its goal of $10 billion in revenues, which it expects to achieve by the end of next year. Despite a good performance in the first three quarters of the year, Salesforce's stock is currently trading 12% lower than its price in January, owing to a tougher market environment and relatively soft performance in the second quarter.

This by itself is of course nothing new, as Israel keeps attracting the attention of top global funds looking for great deal flow outside of Silicon Valley, NYC and Boston; large corporates interested in tapping into innovation coming out of Israel; and large scale startups acquiring smaller Israeli startups as a strategy to get a foot in the Startup Nation door. Given all that, it is no surprise that funding for Israeli startups has reached a record high in 2016 with Israeli tech companies raising $4.6 billion this year, up from $4.4 billion in 2015. The growth in funding is supported in part by massive influence of Chinese investors who "want a piece" of Startup Nation too and invest directly in companies as well as in Israeli VC funds. On the flip side, 2016 was the year we saw a major decline in exits of Israeli companies which took a plunge of 67% compared to the previous year, with no huge, billion dollar Waze-type exits. While global market dynamics definitely played a role here, this is also a sign of maturity of the Israeli tech ecosystem where startups are less excited to sell early and strive to grow bigger companies.

Expedia is the most recognisable brand in the world of online travel and owns several others, including Hotels.com and Trivago. Its companies operate more than 100 branded points of sale in over 60 countries. As a parent company, Expedia has made a steady flow of acquisitions over the past 15 years, and last year stepped up its M&A strategy with the takeovers of online travel agencies Travelocity and Orbitz, and holiday rental website HomeAway. A major goal in this M&A activity is to control and maintain Expedia's market-leading position in an increasingly competitive market for online travel booking, and is reflective of a general industry trend towards consolidation. Expedia was the first online travel giant and has been at the forefront of the transition in the way people book holidays, but that counts for little in the disruptive world of digital.

While many models are purposed for detecting the occurrence of significant events in financial systems, the task of providing qualitative detail on the developments is not usually as well automated. We present a deep learning approach for detecting relevant discussion in text and extracting natural language descriptions of events. Supervised by only a small set of event information, comprising entity names and dates, the model is leveraged by unsupervised learning of semantic vector representations on extensive text data. We demonstrate applicability to the study of financial risk based on news (6.6M articles), particularly bank distress and government interventions (243 events), where indices can signal the level of bank-stress-related reporting at the entity level, or aggregated at national or European level, while being coupled with explanations. Thus, we exemplify how text, as timely, widely available and descriptive data, can serve as a useful complementary source of information for financial and systemic risk analytics.

Virtually everywhere you look, Bay Area tech businesses are running into walls. Smartphones were revolutionary and lucrative, but the U.S. market is saturated, and Apple's iPhone sales have fallen for three quarters. The "app economy" has matured, with more people using existing apps than downloading new ones. And Facebook, which has filled users' news feeds with so many ads it can barely add more, is predicting its revenue growth will slump next year. Silicon Valley needs its next big thing, a focus for the concentrated brain power and innovation infrastructure that have made this region the world leader in transformative technology.

In the race to build the best AI, there's already one clear winner As Google, Facebook, Microsoft, and Baidu take turns leapfrogging each other in artificial intelligence innovation, one company stands to profit from any outcome: Nvidia. Graphics processor units, the company's biggest moneymaker, have become the industry standard for deep learning, a flavor of artificial intelligence widely used by tech companies to build personal virtual assistants, image recognition for tagging photos, and even the software behind self-driving cars. Despite talks from Microsoft and Google about developing their own proprietary chips, almost every major tech company is partnered up with Nvidia and uses its hardware. Last month, Microsoft announced a partnership to work with Nvidia's AI-tailored DGX-1 supercomputer, and Google's recently revamped cloud services will offer the option to run on Nvidia GPUs in 2017. Facebook's open-source Big Sur design for their server racks also rely on Nvidia hardware.

As Google, Facebook, Microsoft, and Baidu take turns leapfrogging each other in artificial intelligence innovation, one company stands to profit from any outcome: Nvidia. Graphics processor units, the company's biggest moneymaker, have become the industry standard for deep learning, a flavor of artificial intelligence widely used by tech companies to build personal virtual assistants, image recognition for tagging photos, and even the software behind self-driving cars. Despite talks from Microsoft and Google about developing their own proprietary chips, almost every major tech company is partnered up with Nvidia and uses its hardware. Last month, Microsoft announced a partnership to work with Nvidia's AI-tailored DGX-1 supercomputer, and Google's recently revamped cloud services will offer the option to run on Nvidia GPUs in 2017. Facebook's open-source Big Sur design for their server racks also rely on Nvidia hardware.