Today the Zillow Group is a public company with 645 million in revenue that also operates websites for mortgage and real estate professionals -- and completed the acquisition of its nearest competitor, Trulia, last year. From the start, Zillow offered the "Zestimate," its value-forecasting feature for homes in locations across the United States. Currently, Zillow claims to have Zestimates for more than 100 million homes, with 100-plus attributes tracked for each property. The technology powering Zestimates and other features has advanced steadily over the years, with open source and cloud computing playing increasingly important roles. Last week I interviewed Stan Humphries, chief analytics officer at Zillow, along with Jasjeet Thind, senior director of data science and engineering.
Big data platform vendors are increasingly focusing on churning through unstructured data, especially for text, audio and even security applications like insider threat analysis. Among the companies emerging in this industry segment is Digital Reasoning, a well-connected cognitive computing company that has helped the U.S. military track terrorists online while working with financial markets to spot insider trading. The company, which recently expanded beyond the Capital Beltway to Nashville, rolled out the latest version of its Synthesys cognitive computing platform this week that combines machine learning, natural language processing, computer vision and pattern recognition. The combination is intended to boost the quality of unstructured data analysis while reducing the amount of time needed to get the desired results. Version 4 of the Digital Reasoning platform released on Tuesday (June 21) is based on proprietary analytics tools that apply deep learning neural network techniques across text, audio and images.
It makes sense for large technology companies like Google and Microsoft to open source AI and machine learning solutions because they have overlapping vertical interests in providing vast cloud services. These come into play when a certain machine learning library becomes popular and users deploy it on the cloud and so forth. It is less clear why financial services companies, which play a much more directly correlated zero sum game, would open up code that they paid the engineering team to create. It's interesting that hedge funds, traditionally thought to be the most secretive of financial institutions, have been proactive in pushing an open source software agenda. AQR Capital Management was probably patient zero when it came to opening up their code around data storage – and this move, shepherded by software engineer Wes McKinney, kickstarted the popular Pandas libraries project.
The artificial intelligence market is expected to grow to USD $16.06 Billion by 2022. The McKinsey Global Institute says, "Recent advances in machine learning can be used to solve a tremendous variety of problems--and deep learning is pushing the boundaries even further." One such company set to take advantage of this emerging market is ASX-listed BrainChip Holdings (ASX:BRN) which is headquartered in Aliso Viejo, California. They have developed a Spiking Neuron Adaptive Processor (SNAP) that essentially mimics the human brain: autonomous and unsupervised learning, evolves and associates information. According to CEO Louis DiNardo, SNAP has many applications, which includes surveillance, casino operations, and even investing.
Taiwan-based visual analytics company Viscovery has announced raising 10 million in funding from its lead investor China Development Industrial Bank, in a bid to accelerate the growth of the platform's global video data analytics and contextual advertising solution. GD1 Fund, H&Q Asia Pacific, and iStart (Softbank China's Venture Capital early fund) also participated in this round. The company's Viscovery Discovery Service (VDS) provides video data analysis, search optimisation and other value added services to clients across the region, including those in Taiwan, South Korea and China. The data is then analysed in order to determine the best context. According to the company, clients find this technique more effective in finding video content, instead of just searching through keywords in the title or description.