Machine learning applications are storing the financial services industry with institutions and regulatory bodies putting technology into real use. Real-world applications, however, are not where the change happens as talented scientists are looking to revolutionize the hardware behind machines with quantum computing capabilities. Rigetti Computing, a company based in California, is a curious example and a source of important findings.
Pick #1. A Startup Uses Quantum Computing to Boost Machine Learning
Researchers at Rigetti Computing, a company based in Berkeley, California, used one of its prototype quantum chips – a superconducting device housed within an elaborate super-chilled setup – to run what’s known as a clustering algorithm. Clustering is a machine-learning technique used to organize data into similar groups. Rigetti is also making the new quantum computer – which can handle 19 quantum bits, or qubits – available through its cloud computing platform, called Forest, today.
“This is a new path toward practical applications for quantum computers. Clustering is a really fundamental and foundational mathematical problem. No one has ever shown you can do this.” – Will Zeng, Head of Software & Applications at Rigetti.
There is currently a remarkable amount of excitement surrounding efforts to develop practical quantum computers. Big technology companies, including IBM, Google, Intel, and Microsoft, as well as a few well-funded startups are racing to build exotic machines that promise to usher in a fundamentally new form of computing.
IBM recently announced that it has built a quantum computer with 50 qubits, and Google is widely rumored to have a device of similar scale. The company also revealed a range of partners for its quantum project, including JPMorgan Chase, Daimler AG, Samsung, Hitachi, and Oak Ridge National Laboratory. These companies want to see what quantum machines might be able to do in a range of applications including financial modeling, chemistry, and route optimization.
There is good evidence that quantum machines can be used to solve cryptographic challenges and to simulate new material. And there is hope that algorithms such as Rigetti’s will eventually transform the world of machine learning and AI.
Pick #2. Overstock is turning into a Bitcoin tech company
Patrick Byrne, the CEO of Overstock.com, wants to possibly sell off the retail business and focus on Overstock’s ownership of 10 blockchain companies through its venture capital subsidiary, Medici Ventures. He has also formed a joint venture with Peruvian economist Hernando de Soto called De Soto, Inc., a company that would use blockchain technology to form a property registry providing land rights to people in the developing world.
“Blockchain is going to change the world more, I think, than the internet has,” said Byrne, who believes that many people will gradually abandon government-backed currencies if more countries encounter currency failures like in Zimbabwe and Venezuela.
Pick #3. The First $100-Billion-Dollar Blockchain Company Could Be the Next SAP
I see today’s enterprise blockchain startups and those in the coming years as the next generation of enterprise database companies. SAP has a market cap of over $135 billion with over $23 billion in revenues last year, and Oracle has a market cap of over $209 billion with over $37 billion in revenues. Oracle positions itself as the world’s number one enterprise database company with dozens of core products from middleware solutions to servers to databases.
The next generation of global enterprise database companies might not just be based on technologies acquired from the region, but wholly originated from Asia. For example, Blocko, which went through our accelerator in Seoul in 2015, has become the leading enterprise blockchain company in South Korea with over 90% market share. Their blockchain-as-a-service platform, Coinstack, has been implemented at Samsung, LG CNS, Hyundai, and many other multi-billion corporations. For the Korea Exchange, they created a blockchain-based OTC trading market, which decreased transaction time from two to three days to one day. This resulted in cost savings of $73 million this past year.