Written by SVSG CTO & AI Practice Lead Geeta Chauhan The integration of AI and Deep Learning into the financial industry isn’t stopping anytime soon. The AI revolution is growing. Gartner predicts by 2018, 80% of data scientists will have deep learning in their toolkits and by 2019, deep learning will be a critical driver […]
As companies throughout the U.S. and the world race to develop new technology to make life in cities safer and easier, citizens’ attitudes ebb and flow with the headlines. Data collection, autonomous vehicles, smart city infrastructure—ideas like these often toe the line between utopian and dystopian future ideals. We are fortunate to be witnessing a […]
On Bloomberg Markets with Carol Massar, Matt Swanson – Managing Partner of Silicon Valley Software Group discusses how Artificial Intelligence can improve jobs & the workforce. Jim Whitehurst CEO Red Hat talks recent earnings and rethinking the organization in our era of disruption. Ken Herbert Managing Director and Analyst Canaccord Genuity discussing Boeing, Embraer forging a […]
Written by Bernard Fraenkel, Enterprise Practice Lead at Silicon Valley Software Group. Can you picture the day when your car insurance bill drops every month? This could very well happen as self-driving car manufacturers (SDCMs) take over the car insurance business. As it turns out, SDCMs have several powerful incentives to do so. Their primary motivation is to […]
Isn’t it curious that two of the top conferences on artificial intelligence are organized by NVIDIA and Intel? What do chip companies have to teach us about algorithms? The answer is that nowadays, for machine learning (ML), and particularly deep learning (DL), it’s all about GPUs. In his most recent Forbes Technology Counsel post, SVSG CTO […]
Advances in Machine Learning (ML) and Deep Learning (DL) technologies and techniques put greater demand on data centers and ML-optimized compute resources and bring a new wave of disruption to cloud providers. This will impact Amazon AWS, Microsoft Azure and other cloud providers as demand for the SMACK stack (spark, mesos, akka, cassandra, kafka) replaces […]
There’s no longer a debate as to whether companies should invest in machine learning (ML); rather, the question is, “Do you have a valid reason not to invest in ML now?”
In the last post, we highlighted the disruption that chatbot technologies are poised to make in call centers. To recap, we are seeing the trend that Generation X and Y have now shown a preference for text-based communication over voice. This results in consumers increasingly wanting to talk with brands via messaging platforms like Whatsapp and Facebook Messenger. Simultaneously, there has been an explosion of conversational A.I. technology tools and frameworks in which natural language processing can be used to automate customer support inquiries. As the last installment discussed, this trend provides a compelling opportunity for companies to drastically reduce the costs of running their call centers.
In 2014, Facebook acquired WhatsApp for $19 billion. That astronomical number set off waves of speculation as to what value Facebook could possibly see in a company with just 55 employees and roughly $20 million in revenue, although it had 500 million users. At last week’s F8 conference, that vision became a lot clearer, and it’s big. Chatbots will cause a near-term disruption in how businesses interact with consumers, and a long term paradigm shift in how people will interact with machines.