摘要： In this special guest feature, Arjun Kakkar, Vice President Strategy and Operations at Ekata, provides 9 practical and actionable principles for product managers and business leaders working to use machine learning for fraud detection.
摘要： Over the past few years, the financial services industry has made huge strides in adopting new technologies like artificial intelligence into its workflow. The cache of data that banks can access holds endless potential to create valuable new products and experiences for clients. With this progress, however, comes concerns around the ethical use of personal data in banking. But with the right business practices in place, banks can reap the benefits of AI while keeping customers in control of their data and protected from its misuse.
摘要： Salesforce Research published a groundbreaking paper, The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies, which applies AI and reinforcement learning to create tax policy for the first time.
摘要： Bitcoin has been unable to stay above the psychological barrier of $10,000 with just three days remaining before miner block rewards are cut in half.
摘要： The history of creating a replica of physical body dates back to yester years when miniatures were built before the actual development of products or buildings. The process was proven to be quite effective in the management of the development process.
摘要： Why do artificial intelligence projects fail? Let’s examine some recurring issues – and expert advice on how to avoid them and increase your AI project’s chances for success
摘要： What is sauce for the goose is sauce for the gander when it comes to implementing artificial intelligence in the capital markets industry insiders testified before the House Financial Services Committee’s Taskforce on Artificial Intelligence.
摘要： Big Data has swiftly become a dated, catch-all phrase in the online marketing lexicon, but it is undeniable that the amount of data and the speed at which is delivered, is still increasing at an exponential rate. For example, Gartner has predicted that enterprise data will grow 650 percent between by 2020, and IDC has stated that the world’s information now doubles approximately every 18 months.
