How are the largest VCs viewing the early stages of the AI Era, from the perspective of investment, technology moats, economics, early adoption and future use-cases.
SHOW: 879
SHOW TRANSCRIPT: The Cloudcast #879 Transcript
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SHOW NOTES:
IS SILICON VALLEY STILL THE CENTER OF TECH INNOVATION?
- Companies are investing tons of money
- Breakthrough results haven’t emerged yet (business models, profits)
- It’s not clear that there is a technology moat; but maybe a capital moat
- Model training costs are expected to rise 5x to 10x - worse economics??
- Lots of VC investment and vendor 2nd-order investments
- LLM costs are creating marginal cost of software (been since the mainframe)
- Model quality vs. price is improving, but price of the services (e.g. ChatGPT-Pro) is increasing - how much extra value is being delivered?
- How will open source impact AI?
- “If anything in life is certain, semiconductors are cyclical, commodity tech goes to marginal cost, and every new tech produces a bubble.”
- Today’s GenAI question - is it accurate and useful? How can we tell, and how can it improve (or does it need to)?
- Start with a simple concept - AI gives us unlimited interns - how can you extrapolate that? How would this have been extrapolated for the original internet (create content, translate language, write code, etc.)
- Use cases are still not easy to see beyond Chatbots (and variants), Coding Assistants
- Consulting revenue from GenAI is bigger than technology - and still most/many projects still in trials.
- Technology can take a long time to adopt - Cloud still only has 30% of workloads (15yrs old)
- 66% of CEO’s don’t expect their first GenAI app in production until sometime in 2025, 50% at least 2H of 2025.
- [Shadow AI] SaaS AI will accelerate adoption, if it follows Cloud pattern - external forces are more motivated to attack business “change” than internal teams
- [Build vs. Ecosystem] Do the LLM vendors become the application vendors? Where does the LLM start and stop (infra, platform, API, apps, etc.)
- [Learning from the customers] Do the LLM vendors use their knowledge advantage to build the apps?
- GenAI Apps Categories - Make something better, Replace something, Just do the thing
- “AI is just whatever is wrong/broken now” - How well does AI understand “broken”
- Will people be the biggest problem in AI progress?
- [Decoupling] Looks at global markets for Internet today - ecommerce/retail, food delivery, advertising, media, autonomous driving,
- [Elevator Example] Automation gets rid of people
- No real conclusion
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