In this discussion, a16z general partner Martin Casado examines the evolution and economics of AI, and how generative AI is set to change the landscape.
He explains the challenges faced by startups in the AI space, introduces the concept of the ‘AI mediocrity spiral’, and highlights the potential of generative AI in creating a new wave of iconic companies.
The Evolution of AI
AI has made significant progress over the past 70 years, solving real-world problems in various fields and even surpassing human capabilities in certain areas.
However, the economic viability for AI-native startups to displace large incumbents has been a challenge.
On the Cusp of a Major Transformation
We are on the cusp of a major transformation in the field of AI and computing more broadly.
The economics of generative AI are compelling and we should be prepared for a wave of innovation and change as a result.
Generative AI in Business
Generative AI has three emerging business areas: creativity, companionship, and copilot.
These areas can provide significant value to businesses and consumers, and have the potential to revolutionize various industries.
The Unit Economics of AI
Despite significant investment, the unit economics of certain AI applications, such as Robo taxi, are still not on par with human alternatives.
This illustrates the economic challenges faced by AI startups.
The Economic Inflection of Generative AI
Generative AI competes with the less evolved creative language center of the brain, leading to an economic inflection that could trigger a market transformation.
This suggests a promising future for generative AI startups.
AI’s Value to Large Companies
AI has added significant value to large companies like Meta, Google, and Netflix.
However, the challenge lies in enabling AI-native startups to break away and trigger a platform shift.
AI Mediocrity Spiral
Startups often find themselves in an ‘AI mediocrity spiral’ where they continuously hire more people to maintain quality as they grow.
This hampers scalability and prevents startups from achieving breakaway economics.
Challenges of Traditional AI
Traditional AI use cases often require accuracy in the tail of the solution space, which can be challenging for startups.
This involves hiring people for accuracy, adding a variable cost, and dealing with a long tail of solutions that require significant investment while the value decreases, leading to lower margins and scalability issues.
Potential of Generative AI
Generative AI, which can take a natural language input and output something like a conversation, image, or 3D model, has significant potential.
It offers economic advantages over traditional AI and competes with the less evolved creative language center of the brain, giving rise to a market transformation.
The new gen AI wave is kind of competing with the creative Language Center of the brain, it’s like 50k years old, it’s much less evolved and it turns out it’s incredibly competitive so much so that you actually have the economic inflection we look for for a market transformation. – Martin Casado
Third Epoch of Computing
The marginal cost of producing more of a good or service drops significantly with the use of AI, leading to a potential third epoch of computing.
This epoch could see the creation of a new wave of iconic companies due to the compelling economics of generative AI.
Addressing Job Loss Concerns
Despite concerns about job losses and value displacement due to AI, the demand for AI services is expected to increase as per Jevons’ Paradox.
This suggests that the drop in costs due to AI will lead to increased productivity and the creation of new jobs.
It’s not that the technology doesn’t work, it’s not that we can’t solve the problems, all of that has always been the case. It’s not even that we can’t monetize it, big companies are great at monetizing it. It’s that it’s very, very hard for startups to break away and if startups can’t break away, you don’t get a transformation. – Martin Casado
The Economic Drive of Generative AI
The shift towards generative AI is driven not just by capabilities, but by economics.
The potential economic benefits of generative AI are driving its rapid growth and adoption.
