Overview
Artificial Intelligence is a fascinating field. To gain an understanding of the AI landscape, we conducted in-depth interviews with 42 individuals, primarily AI researchers at high-tech companies actively working on cutting-edge projects, along with 10 founders of AI startups at the Series B funding stage or later, and experts from leading companies like AI21 Labs and Cohere.
Background: This research was conducted as part of an independent study that used the Research-Driven Innovation process at Stanford Graduate School of Business, overseen by a faculty sponsor with extensive experience as a technology entrepreneur and executive. The research team had complementary skill sets, consisting of a Stanford MBA candidate who previously founded a software startup and led AI product incubation at Google, and a Stanford MSx candidate who previously led corporate strategy and investments at multinational companies.
Scope: Bottlenecks and emerging opportunities in the AI landscape. Initially, the project focused on challenges in dataset acquisition for large language models. The scope was expanded during the project due to the nature of interviews.
Intended Audience: This series is meant for anyone invested in the future of AI. This includes AI practitioners, business leaders, students, and investors.
Limitations: This series is not a comprehensive review of all AI research. Much more work is needed to provide an in-depth understanding of the many broad fields of artificial intelligence research.
Why This Series Matters:
Bringing AI’s potential to transform society to fruition demands a clear understanding of challenges and opportunities. This series aims to provide clarity, offering a research-backed perspective that goes beyond anecdotal evidence and industry buzz. We address key questions:
What are the true limitations of today's AI, and what are the most urgent unsolved problems?
Where is cutting-edge research headed, and what breakthroughs are on the horizon?
How are industry dynamics – from open-source to data control – influencing AI's trajectory?
What strategic actions can businesses, researchers, and policymakers take to drive innovation and responsible development?
Series Outline:
This series will provide an exploration of the AI landscape, structured as follows:
Introduction (This Article)
Methodology
Who We Interviewed
Key Research Domains
Directory of AI Research
Primer: A synthesized overview of the current AI landscape, drawing on both the research literature and our interview findings. This provides a broad, accessible introduction to the key trends and players.
The Bottleneck Breakdown: Analyzing the Critical Challenges in AI Development: A deep dive into the most significant obstacles hindering AI progress, including evaluation, data, talent, and infrastructure. This focuses on the core research findings and their implications.
Future Articles: Further explorations of specific topics, emerging trends, and strategic recommendations.
Join the Conversation:
We encourage active engagement with this series. Share your perspectives, contribute to the discussion, and help us collectively navigate the exciting and challenging future of AI. What questions do you have? What insights resonate with you? Let us know through the contact form.