The AI Impact Tour: Exploring Auditing Methods for AI Models
As the deadline approaches, there is only one week left to request an invite to The AI Impact Tour on June 5th. This exclusive event offers a unique opportunity to delve into various methods for auditing AI models. If you don’t want to miss out on this incredible chance, find out how you can attend.
The Myth of Research and Development (R&D)
Research and development (R&D) is often seen as a chimera – a creature with two distinctive heads on one body. On one hand, researchers have strong academic backgrounds and contribute to the field through publishing papers, applying for patents, and working on ideas that may take years to come to fruition. They ask tough questions and find innovative answers, delivering long-term value. On the other hand, developers are valued for their practical skills and problem-solving abilities. They focus on producing measurable results in rapid cycles. While critics argue that development teams simply package and repackage products, it is the nuts and bolts of a product that drive adoption. In a basketball analogy, the players would come from the development department, while the research team questions the rules of the game itself.
The AI Audit in NYC: June 5th
Next week in NYC, top executive leaders will gather at the AI Audit event to discuss strategies for auditing AI models. This invite-only event promises to provide insights into ensuring optimal performance and accuracy across organizations. Secure your attendance to this exclusive event before it’s too late.
The Shift in AI Barriers and Value Drivers
The AI space is experiencing a significant shift. While S&P or Fortune 500 companies still prioritize hiring AI researchers, the rules of the game are changing. Large software companies, for example, no longer consider physical assets like buildings or supply chains as their core assets. Instead, they recognize that their enormous lumps of code, which used to take decades to replicate, are now their most valuable assets. AI-powered auto coding can build new homes in a few hours at just 1% of the typical cost. This dramatic shift in barriers to entry and value drivers has implications for the AI moat, the metaphorical barrier that protects a business from competition. Today, long-term and defensible business moats come from the product, users, and surrounding capabilities rather than research breakthroughs. The best sports teams excel not just because of innovative strategies but also because of their community, brand, and product offering.
Where AI Dollars Deliver Returns
Companies like OpenAI, Google, Meta, Anthropic, Cohere, Mosaic Salesforce, and many others have invested heavily in hiring large research teams to build better LLMs (large language models). However, securing patents and prizes does not guarantee a strong return on investment (ROI) for an AI startup. Today, the development side of AI, which transforms new LLMs into products, is where the difference is made. Whether it’s a new startup creating what was once deemed impossible or an existing company integrating new technology to provide exceptional offerings, long-term and lasting value is created by AI capabilities in three core domains.
– Infrastructure for AI: As AI adoption increases, companies must adapt their infrastructure to meet evolving computational requirements. This includes dedicated chips and data network layers that facilitate the flow of AI data throughout the organization.
– Utility: The gap between LLMs learning and poaching talent from others is narrowing. In large organizations, the challenge lies in applying this technology to specific use cases. Companies that enable non-AI specialists to harness the benefits of LLMs will find success.
– Vertically-focused LLM products: With the changing rules of the game, new products become possible. Creative founders will enhance the world with products that were previously unthinkable.
The Bottom Line
The key to success in AI has shifted from groundbreaking research to building practical applications. While research lays the foundation for future advancements, development translates those ideas into value. The new AI moat lies in exceptional AI-powered products, not groundbreaking research. Companies that excel in building user-friendly tools, infrastructure for smooth AI integration, and entirely new LLM-powered products will be the future winners. As the focus shifts from defining the game’s rules to mastering them, the race is on to develop the most impactful applications of AI.
In conclusion, the AI Impact Tour offers a valuable opportunity to explore auditing methods for AI models. With a shift in the AI landscape, it’s important to understand the changing rules and focus on practical applications rather than solely relying on groundbreaking research. The future winners in AI will be those who excel in building user-friendly tools and leveraging AI capabilities in infrastructure and utility domains. Don’t miss out on this exclusive event that could shape the future of AI.