SITALWeek #454 Stuff I Thought About Last Week (Last Month!)

Summary

Summarized wtih ChatGPT

The article discusses the competition between Microsoft and Google in the AI space, highlighting the importance of cost-effective AI solutions. It suggests that as AI technology advances, companies might replace human workers with AI, leading to significant changes in the job market and economy. The author expresses uncertainty about the timeline for these changes but believes they will have a major impact on society.

Key Takeaways:

1. Monitor advancements in AI technology and their potential to replace human jobs.
2. Consider the cost-effectiveness of AI solutions when making business decisions.
3. Stay informed about developments in quantum computing and their implications for AI.

Highlights from Article

The principal-agent problem describes a misalignment of objectives between two parties working together. Often, the principal has a certain outcome in mind and seeks the help of the agent to achieve that outcome. However, if the agent has a different set of incentives, both parties may end up failing at their given task.

it’s no surprise that the data show that Google’s Gemini models operate at the highest level of intelligence per dollar cost, which may be the driving force of recent share gains with developers

• Google operates its own data centers and thus is incentivized to reduce costs. OpenAI does not

becoming the leading AI platform would appear to be Google’s opportunity to lose, although the race is far from over.

I think the salient question for AI (and, frankly, humanity!) is: How much AI reasoning can you get for a human-equivalent salary? In other words, for a certain salary, how much compute power will it take to match or outperform a human (assuming the AI can collaborate with other humans/AIs using the same methods and tools a human would).

LLMs are shifting from a pure token-in/token-out model to a test-time scaling model, which may offer us better inroads for estimating costs. Essentially, they are thinking harder before spitting out a reply; thus, rather than just predicting the next words in a response using a probability model (see You Auto-Complete Me), they are doing some deep thinking to arrive at more accurate, useful answers.

AI replacing human decision making and reasoning (including high-value R&D that could lead to a new Age of Wonder) is one of two vectors that I see as interesting in the coming years. The other interesting vector is in entertainment. AI models are getting remarkably good at creating compelling, realistic video

This existential transition for the investment industry from liquid public markets toward creating broader appeal for more highly levered private assets comes with lower liquidity and increased systemic risks.

• More PE money means less stability

All material owns to the authors, of course. If I’m highlighting or writing notes on this, I mostly likely recommend reading the original article, of course.

See other recent things I’ve read here.