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New Investments, Fresh Capital, Recent Exits, Mark Momentum for Benhamou Global Ventures PALO ALTO, CA –(Marketwired – June 28, 2017) – Benhamou Global Ventures (BGV), an early-stage venture capital firm with deep Silicon Valley roots and an exclusive focus on enterprise information technology opportunities in global markets, announced the final close of their third fund with $80 million of investable capital. Investors in the third fund include both existing LPs as well as new international and institutional LPs including several US, European, Israeli and Chinese investors. Extending the strategy of fund BGV II, BGV III will focus on enterprise IT sectors including cyber security, cloud-based infrastructure services and applications, web scale infrastructure, advanced analytics and artificial intelligence as well as industrial Internet of Things (IOT). The firm will continue its cross-border investment strategy, identifying and investing in promising companies originated in Israel, Europe and Asia and helping them build a presence in Silicon Valley. BGV has made 5 investments from the BGV III fund recently: Bayshore Networks, an emerging leader in Industrial IOT cyber security was completed in March 2017 and was syndicated with Trident Capital. The company secures and protects critical Industrial IOT assets. Secret Double Octopus (SDO) is an Israeli cyber security company whose breakthrough technology enables a password-free environment with trust channels established via a mobile phone app. That investment was completed in April 2017 and was syndicated with JVP, Iris Capital, and Liberty Media Ventures. Sherpa Digital Media, an emerging leader in Augmented Reality for the enterprise, was completed in June 2017 and was syndicated with Rally Ventures. The company securely manages, measures and automates video content and reaches customers, prospects and employees across all devices and locations. 6d bytes, an emerging leader in robotics, machine vision and AI, was completed in June 2017 and was syndicated with Partech and leading angel investors such as Plug and Play. The company is transforming the way the food and beverage industry approaches the preparation and serving of healthy foods. Drishti, a computer vision spin-off of SRI (Stanford Research Institute, Menlo Park) joined the BGV portfolio in June 2017 and was syndicated with Andreessen Horowitz (a16z). It provides a highly innovative solution to improve the efficiency of human operators in manufacturing assembly lines. “We are grateful to enjoy the support of exceptional repeat and new investors in fund III to implement our investment strategy,” said Eric Benhamou, founder and general partner of Benhamou Global Ventures. “The sales of Grid Dynamics (acquired by TeamSun) and of Zentri (acquired by Silicon Labs) in Q1 2017 are a further evidence of the success of the BGV model.” The partners of BGV III are Eric Benhamou, Anik Bose, Eric Buatois, Yashwanth Hemaraj, Marina Levinson, Amir Nayyerhabibi, Janice Roberts based in BGV’s Palo Alto office, and Barak Ben Avinoam (based in BGV’s Tel Aviv office in Israel). About Benhamou Global Ventures BGV is an early-stage venture capital firm with deep Silicon Valley roots, with an exclusive focus on enterprise technology opportunities in global markets. BGV currently has 25 active companies in its portfolio. The BGV team of 8 investment professionals has successfully built and implemented a cross-border venture-investing model with companies from Israel, Europe and Asia. Eric Benhamou, former chairman and CEO of 3Com, Palm and co-founder of Bridge Communications, founded the firm in 2004. Comprised of an experienced partnership team of global operating executives and investors, BGV is often the first and most active institutional investor in a company and has a powerful network of technical advisors, executives and functional experts who actively engage with its portfolio companies. The company has offices in Palo Alto, California and Tel Aviv, Israel. For more information, visit www.benhamouglobalventures.com.
Source: http://www.marketwired.com/press-release/bgv-closes-third-fund-makes-new-investments-2224138.htm
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Anik Bose (BGV General Partner) and Niranjan Venkatesan (BGV intern and Kellogg MBA student) share their perspective on innovation and value creation in computer vision. Computer vision is defined as tasks that include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions. In layman’s terms, computer vision is an arm of artificial intelligence (A.I.) that focuses on enabling machines to “understand” images by processing and analyzing them on a pixel-by-pixel basis, rather than relying on human-controlled categorization data, such as keywords and descriptions. Getting computers to recognize objects just like human beings do remains elusive; 100% accuracy and reliability is almost impossible. As a reference point, the human eye delivers 91% recognition. New technologies such as deep learning are evolving that promise to increase accuracy and reliability dramatically, but these technologies need more research before they can become mainstream. These technologies are modeled on a neural network and will allow the conversion of an image to text or speech. Deep learning will also enable the conversion of text or speech to image or video and the two together can enable tagging, searching, and indexing of a video or image just like text. Some of these new software technologies can deliver a recognition accuracy of 95%. Intellivision, a BGV portfolio company, is able to deliver 98% accuracy for specific vertical applications. Early M&A activity in the computer vision space by larger companies is a lead indicator of the large market potential. The most prominent acquisition being Intel’s recent $15bn acquisition of Mobile eye. Adoption Challenges While the computer vision market forecasts are significant, we believe there are several adoption challenges that must be addressed for the market opportunity to be realized. Key adoption factors include image data privacy concerns, lack of data accuracy, quality and ubiquity, automotive regulations, evolving industry standards and dependence on analytic platforms and applications. These factors, along with operational challenges such as costs, increases in video/image data driven by higher security needs, inability to maintain and fit legacy systems to the new requirements and the difficulties associated with scaling pilots in addition to high bandwidth requirements for hardware, are all rate limiting factors influencing the timing and size of the actual market opportunity. The Venture Investment Opportunity We believe that the computer vision technology stack can be broken down into three layers: a) hardware – This includes cameras, sensors, chipsets and video cards; b) solution frameworks – This includes image-processing algorithms, analytics/deep learning algorithms; c) application – This includes facial recognition, AR/VR and 3D imaging applications. This stack must be applied to proprietary data needed to train the algorithms required to solve specific customer problems. Access to such data will be the long-term differentiator for the winning companies, sometimes more important than the technology stack itself. We believe that there are six specific areas where innovative startups can play a strong role in value creation. These are:
  • Robotics Vision – Driven by demands for the following: safety, quality, reliability, and ease of use, cost efficiencies, benefits of 3D over 2D technology, rapid deployment, and penetration of smart camera in retrofit robotic systems. Key early adopter industries will be automotive and food processing. 6dbytes is an innovative robotics software orchestration company that is targeting the food-processing industry.
  • Visual inspection/Machine Vision – Manufacturers prefer machine vision for visual inspections for their high speed and repeatability of measurements. This accuracy, along with the ability to safely and reliably identify flows and defects in products without disrupting or delaying processes, will create strong demand for computer vision. Key early adopter segments are likely to be the electronics and automotive industries. Drishti is another innovative startup that aims to revolutionize the manufacturing assembly line by digitizing human actions based on technology that can enable non-intrusive and real time observation.
  • Augmented Reality – Applications such as improved logistics in a warehouse, remote monitoring, trouble-shooting and hands free access to contextual information are expected to drive the adoption of AR. Retail and transportation are expected to be early adopter segments. Augment is a startup seeking to transform the retail shopping experience with AR. They are one of the first companies targeting the enterprise B2B space with an end- to-end AR platform.
  • Video Analytics – Intelligent video surveillance to respond to rising threats along with increased demand for business intelligence and adoption of cloud and analytics are also creating the need for computer vision technology. Early adopter markets are likely to be public safety and defense. Intellivision is an innovative BGV portfolio company that provides intelligent video analytics and smart camera solutions for retail, smart home and IOT markets.
  • 3D Imaging – The automotive and construction sectors are progressively adopting 3D imaging solutions for designing, previewing and rectifying the final version of the end products. Fast-paced adoption is expected in healthcare as well for surgical applications and diagnosis.
  • Image/Facial Recognition – Applications will increasingly value code recognition, digital image processing, object recognition, pattern recognition and optical character recognition.   Media and entertainment is expected to be a lead early adopter segment. Finally, facial recognition will be driven by applications such as law enforcement, surveillance, mobile device authentication as well as targeted advertising in retail.
In conclusion, we believe that the analysis of content via computer vision and artificial intelligence is no longer a concept being discussed only in academia. It is an area where we expect to see significant startup innovations that will empower and disrupt existing industries over the next ten years.
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