The article also touches on the potential impact of regulation on AI startups. Christian Noske, a partner at NGP capital, suggests that regulation could add cost to the product development cycle and strengthen the position of Big Tech companies. However, Bell sees regulation as a potential lucrative market for companies building tools to help AI vendors comply. The article concludes by noting that the choice between open source and closed source may matter less than the overarching go-to-market strategy for startups.
Key takeaways:
- Startups are delineating along two clear lines in the generative AI boom: proprietary and closed source approach versus open sourcing their models, methods and datasets.
- Open source AI innovation can foster a sense of trust in customers through transparency, while closed source models are less explainable and thus a harder sell to boards and executives.
- Regulation could potentially add cost to the product development cycle, strengthening the position of Big Tech companies and incumbents at the expense of small AI vendors, but it could also be a lucrative market for companies building tools and frameworks to help AI vendors comply with regulations.
- Customers are often more interested in solving a business problem than the underlying model and whether it’s open source, and startups recognizing this will have a leg up in the overcrowded field for AI.