On with Kara Swisher: Can Smaller AI Startups Compete in the AI Race?

Podcast Information:

• Title: On with Kara Swisher
• Host: Kara Swisher, Vox Media
• Episode: Can Smaller AI Startups Compete in the AI Race?
• Release Date: May 26, 2025

In the May 26, 2025 episode of "On with Kara Swisher," award-winning journalist Kara Swisher delves into the burgeoning landscape of artificial intelligence (AI) and the viability of smaller AI startups in an industry increasingly dominated by tech giants like OpenAI, Microsoft, and Google. Joining her are two esteemed guests: Gary Rivlin, a Pulitzer Prize-winning investigative reporter and author of AI Valley, and Christy Weiskill, Senior Advisor for Innovation and Entrepreneurship at Johns Hopkins University. Recorded live at the Johns Hopkins University Bloomberg Center, the episode offers an insightful exploration into the dynamics shaping the AI sector today.

The AI Funding Landscape

Kara Swisher kicks off the discussion by highlighting the explosive growth in AI funding. “According to PitchBook, AI and machine learning startups took home about half of the venture capital dollars in North America last year,” she states at [00:22]. However, she points out a significant concentration of funding: “In the first quarter of 2025, $40 billion went to OpenAI,” raising concerns about the accessibility of capital for smaller startups.

Gary Rivlin echoes these sentiments, explaining that the dominance of large corporations in AI funding poses a substantial barrier for emerging companies. “AI is so expensive that there's very few startups that really can afford to be playing basic stuff like text to video, text to audio, large language models,” Rivlin remarks at [05:47]. He fears that foundational AI work will increasingly be monopolized by big tech firms, limiting innovation from smaller entities.

The Role of Universities and Fundamental Research

Christy Weiskill emphasizes the critical role that universities play in the AI ecosystem. “[...] the foundations of the tech industry actually come from a lot of the work that happens at universities,” she explains at [07:49]. Weiskill underscores that institutions like Johns Hopkins are pivotal in translating academic research into marketable technologies, particularly in life sciences and healthcare.

Rivlin adds a historical perspective, noting the cyclical nature of AI funding and research: “In the 50s, 60s, it was government-funded research. [...] My big fear is, you know, the Chinese have said by 2030 they want to be dominant in AI and if we're cutting off this basic research, I think we're giving them a big advantage,” he warns at [08:58]. This highlights the geopolitical stakes tied to AI research and development.

Regional Differences: Silicon Valley vs. Baltimore

The conversation shifts to the geographic concentration of AI innovation. Christy Weiskill discusses efforts to position Baltimore as a tech hub comparable to Silicon Valley. “[...] Johns Hopkins and Baltimore will not dominate that. We already are,” she asserts at [16:36]. However, she acknowledges the challenges faced by regional startups in securing funding and scaling their innovations amidst the dominance of established tech centers like San Francisco.

Gary Rivlin concurs, pointing out the migration of venture capital to San Francisco: “[...] OpenAI anthropic. A lot of the other big AI companies are in San Francisco. The venture capitalists used to famously be all in Menlo Park. They now have outposts in San Francisco,” he notes at [12:03]. This centralization further marginalizes smaller startups outside these primary hubs.

AI's Impact on Life Sciences and Healthcare

A significant portion of the discussion centers on the intersection of AI and life sciences, where AI holds transformative potential. Weiskill highlights specific applications such as early cancer detection and predictive diagnostics: “Imagine a world where you could just, with a simple algorithm, detect pancreatic cancer,” she illustrates at [24:35]. These advancements promise not only improved quality of life but also life-saving medical interventions.

Rivlin acknowledges the optimism surrounding AI in healthcare but cautions against overhyping its capabilities. “I am totally with both you that AI and healthcare is gonna be extraordinary for humanity. But why do you have to say it's gonna wipe out cancer in 10 years?” he questions at [21:17]. This balance between potential and realism is crucial in shaping public and investor expectations.

The Hype and Reality of AI

Kara Swisher and her guests address the pervasive hype surrounding AI, particularly the exaggerated claims made by techno-optimists. Rivlin criticizes the overpromising narratives, stating, “It's like this is where Silicon Valley, the tech bros get themselves in trouble. They're overhyping and AI has a problem,” at [21:18]. He argues that such hyperbole can lead to unrealistic expectations and potential backlash against AI technologies.

Moreover, Rivlin expresses concerns about public perception and regulatory lag, “Pew did a poll. The majority of people are fearful of AI,” he notes at [22:04]. He emphasizes the need for regulated and transparent AI development to align technological advancements with societal norms and safety.

Future Prospects and Policy Recommendations

As the episode nears its conclusion, the focus shifts to the future trajectory of AI and the policies needed to foster a healthy innovation ecosystem. Both Rivlin and Weiskill advocate for strategic government support and thoughtful regulation to sustain fundamental research and prevent the monopolization of AI advancements by a few large corporations.

Rivlin stresses the importance of regulatory frameworks that ensure AI development is both responsible and inclusive: “We could put in some pretty modest regulations that make sure that the general public is there with these AI companies,” he suggests at [37:09]. Weiskill complements this by highlighting the necessity of maintaining robust federal funding for university research, which is the bedrock of sustained AI innovation.

Conclusion

Kara Swisher wraps up the episode by reiterating the critical balance needed between fostering innovation and managing the consolidation of power within the AI industry. “On with Kara Swisher is produced by Christian Castor, Russell, Kateri Yocomb, Dave Shaw, Megan Burney, Megan Cunane and Kaitlyn Lynch,” she concludes, emphasizing the collective effort to navigate the promise and peril of AI.

Key Takeaways:

• Funding Concentration: A significant portion of AI venture capital is being funneled into large players like OpenAI, potentially stifling smaller startups.
• Foundation of Research: Universities remain pivotal in AI innovation through foundational research, especially in life sciences and healthcare.
• Geographical Hubs: Efforts to establish regional tech hubs outside Silicon Valley, such as Baltimore, face challenges amid centralized venture capital dynamics.
• Realistic Optimism: While AI holds transformative potential, especially in healthcare, overhyping its capabilities can lead to public distrust and unrealistic expectations.
• Policy and Regulation: Thoughtful government policies and sustained funding for research are essential to ensure balanced and inclusive AI development.

This episode provides a comprehensive overview of the current state of the AI industry, highlighting both the immense opportunities and the significant challenges faced by smaller startups in a landscape increasingly dominated by established tech giants. By integrating expert insights from industry veterans and academic leaders, Kara Swisher effectively captures the multifaceted nature of the AI race and its implications for future innovation.

Notable Quotes:

• Gary Rivlin on AI funding concentration: “AI is so expensive that there's very few startups that really can afford to be playing basic stuff like text to video, text to audio, large language models.” [05:47]

• Christy Weiskill on the role of universities: “The foundations of the tech industry actually come from a lot of the work that happens at universities.” [07:49]

• Gary Rivlin on overhyping AI: “They’re overhyping and AI has a problem.” [21:18]

• Christy Weiskill on AI’s potential in healthcare: “Imagine a world where you could just, with a simple algorithm, detect pancreatic cancer.” [24:35]

• Gary Rivlin on the importance of regulation: “We could put in some pretty modest regulations that make sure that the general public is there with these AI companies.” [37:09]