BLCK VC + AWS Startups | Beyond the Hype Cycle: Navigating the Promises and Perils of GenAI
Hosted by BLCK VC and AWS Start Ups, "Beyond the Hype Cycle: Navigating the Promises and Perils of GenAI" will be an insightful discussion that explores the groundbreaking field of Generative Artificial Intelligence (GenAI) and its implications for investment opportunities.
During the panel, participants will go beyond the surface-level hype surrounding GenAI, diving deep into its promises and perils. This dynamic discussion will explore investment strategies, potential industry disruptions, and the challenges associated with this revolutionary technology. We will also talk through the ethical and social implications of GenAI, including privacy concerns, biases, and the need for responsible AI development.
Don't miss this opportunity to gain valuable insights on how to navigate the ever-changing landscape of GenAI.
Moderator
Maya Matthews is an investor at March Capital, where she focuses on the firm’s investments in B2B AI ML Applications & Infrastructure and Fintech. She has a particular interest in companies building next-gen generative AI functionality for the enterprise.
March Capital is an early growth stage venture capital firm based in Los Angeles, and sponsoring firm of the Montgomery Summit, a technology conference that attracts over 1,000 leading global entrepreneurs, investors, and corporate executives to Santa Monica. March has spent nearly a decade partnering with exceptional entrepreneurs to build category leading tech companies and scale them globally. If you are a founder building a B2B AI/ML application or infrastructure company, you can find Maya on LinkedIn.
Prior to joining March Capital, Maya was an Investor at Intel Capital, where she supported various business units in sourcing, analyzing, and executing private placements and acquisitions on behalf of Intel Corporation. Maya holds a bachelor’s degree from Columbia University in the City of New York.
Panelists
Afua Bruce is a leading public interest technologist who works at the intersection of technology, policy, and society.
Afua is the Principal of the ANB Advisory Group LLC, a consulting firm that supports organizations developing, implementing, or funding responsible data and technology. With her background in software engineering, data science, and artificial intelligence, combined with experience developing and deploying technology in and with communities, Afua incorporates an equity-based framework into her engagements.
Afua is an adjunct professor at Carnegie Mellon University and an affiliate at Harvard Kennedy School’s Berkman Klein Center. Afua’s newest book, The Tech That Comes Next: How Changemakers, Technologists, and Philanthropists can Build an Equitable World, describes how technology can advance equity.
Morgan Cheatham: Morgan Cheatham is a vice president in the New York City office where he focuses on investments in healthcare and life sciences from early to growth stages. He has a particular interest in companies leveraging unique datasets and computational methods to improve patient care from bench to bedside. Morgan works closely with a number of portfolio companies including serving on the board of FOLX Health.
Before joining Bessemer, Morgan worked at Goldman Sachs in the Consumer Retail and Healthcare Group in the Investment Banking Division. Prior to investment banking, he was a data scientist at Kyruus, a healthcare IT startup focused on patient access and provider data management.
Morgan is pursuing his medical degree at The Warren Alpert Medical School of Brown University and graduated magna cum laude from Brown University with a B.S. in neuroeconomics. You can follow his latest thinking on Twitter @morgancheatham.
Aaron Meglar empowers early-stage AI/ML startups with technology best practices, product advising, investor relationships, and go-to-market strategy at AWS. He has a background in Strategy Consulting, leading Machine Learning Engineering teams, as well as Product Management and Entrepreneurship with a Master's in Applied Data Science from the University of Michigan.
