SynopsisSkymind is an open-source, enterprise deep-learning provider based in San Francisco, California. They help large corporate teams build deep-learning applications for media, images and sound and time series data for finance, healthcare, telecommunications and the Internet of Things. TEAM: Nicole Zafrany 801270, Sam Benzaquen 801558, Manny Moldawsky 311119127 and Pablo Prisiallni 801421.Detailed description  Skymind is an early-stage company created in San Francisco(2014) by Chris Nicholson (CEO), and Adam Gibson (CTO). , but it’s quickly establishing itself as one of Silicon Valley’s premier sources of expertise on artificial intelligence in the enterprise. Their product is based on “deep learning,” a core technology in building AI. It seeks to remake computing by more closely mimicking the way the human brain processes information, giving machines more power to “learn” as time goes on. Its becoming an important tool for natural-language processing (NLP), computer vision, database predictions, pattern recognition, speech recognition, predictive analytics and fraud detection. With production-grade deep learning tools, enterprise teams can learn from their data more quickly, responding to the world in real-time. Skymind sells software and services based on Deeplearning4j, a popular tool that enterprise programmers used to detect fraud and recognize images for business. It is early to tell how much traction deep learning will get, but by seeing the market, and its first users  that are backing it up, which are Orange, Ericsson, and IBM.Market: AI technology- Deep Learning: Tractica forecasts that annual revenue for enterprise applications of AI will increase from $202.5 million(2015) worldwide to$11.1 billion(2024), representing an annual growth rate (CAGR) of 56.1%.AI systems will drive hardware sales at an even higher rate than the mission-critical systems have to date, especially graphics processing unit (GPU) chips. According to Statistics MRC, the Global Deep Learning Market is accounted for $1.95 billion in 2016 and is expected to reach $72.10 billion by 2023 growing at a CAGR of 67.4% during the forecast period. Rise of usage in various industries such as automotive, advertisement, medical and others. We believe that Skymind’s current business model will help penetrating the market in the best way. Having a free version for usage of mainly SMEs and a customized paid version for larger corporations will help spread awareness as quickly as possible. Hopefully leading Skymind to develop a more tailored product for small enterprises, at an affordable price.Concerns: Microsoft predicted that AI could become strong enough to pose a risk to society. The intellectual resistance to AI is likely to grow into political resistance in the coming years and some pundits are already advocating the establishment of government departments to provide oversight for AI systems, although this is currently a low priority for most governments. Being software, applications are also subject to all the same limitations as other software systems including bugs, hacking, and poor design.SummaryTotal actual funding amount of $6,320,000 shows that investors have faith in their vision. The enterprise solution, Skymind Intelligence Layer (SKIL), packages Deeplearning4j and other open sourced tools.  One of the reasons Skymind’s framework works so well is that it is coded in Java, the standard coding language for corporate solutions. This helps adoption and can be easier to work with than other solutions. They offer a great support system and programmers can call a service representative with any questions that might arise. AI is spreading throughout business and enterprise solutions. With companies like Skymind innovating and improving the system, artificial intelligence will continue to see quicker implementation and more creative applications.Nervana(deep learning startup), was acquired by Intel, and another, MetaMind, was acquired by Salesforce. Skymind partly stands out because it pushes open-source software (but now also a commercial distribution) and doesn’t dabble in hosted services or custom hardware.