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Lendbuzz blends its founders’ early experiences with AI to disrupt traditional assessment methods and widen the pool of credit-worthy individuals.
This week, we look at a breakthrough artificial intelligence release from OpenAI, called GPT-3. It is powered by a machine learning algorithm called a Transformer Model, and has been trained on 8 years of web-crawled text data across 175 billion parameters. GPT-3 likes to do arithmetic, solve SAT analogy questions, write Harry Potter fan fiction, and code CSS and SQL queries. We anchor the analysis of these development in the changing $8 trillion landscape of our public companies, and the tech cold war with China.
This week, we look at:
What it means to ask questions and find answers
From asking simple questions that result in neobanks and roboadvisors. Who will win — Schwab or Robinhood?
To asking macro questions about the finance / high-tech competition. Who will win — Goldman Sachs or Google?
To asking profound questions about the nature of the work, and the art of finding your own questions.
We can't formulate the questions for you. But we can give you a framework of needs for both the individual, and the organization.
The questions that you ask are the answers that you will get.
Today's corporations and governments are in the business of defining the balance of these aspects of our participation in society and the economy. Beliefs about the immutability of different attributes about what makes a person (or an employee) and how economies are built (cutting the pie, vs. growing the pie) determine the policy decisions you make, top down. As the core example this week, let's take Deutsche Bank. Facing pricing pressure and headwinds in several of its businesses, Deutsche is responding with a plan to fire 18,000 employees by 2022 and an announced investment of €13 Billion in technology and innovation by 2022. They even spun up a hipster-colored neobank as a proof point. Wall Street ain't buying it.
In this conversation, we chat with Kevin Levitt who currently leads global business development for the financial services industry at NVIDIA. He focuses on global trends in accelerated compute and AI for consumer finance – including fintech, retail banking, credit card and insurance. Prior to joining NVIDIA, Kevin served as Vice President of Business Development at Credit Karma, and Vice President of Sales for Roostify.
More specifically, we touch on the role data plays in the financial industry, how the needs of financial institutions have changed, the age of big data, the definitions between artificial intelligence and machine learning, how to train an AI algorithm, the reasoning behind the incredible amount of parameters machine learning solutions consume, the fundamental purpose of AI/ML in financial services, what NVIDIA’s platforms comprise of, and lastly the future of AI/ML.
