🔍 Exploring AI’s Future: Are We in an Anti-Bubble?
This week, I dove into Acquired’s “Google: The AI Company” episode, and it was a revelation. Here’s what stood out:
- Efficiency of Nature: Greg Corrado from Google Brain reminds us that nature operates in the most energy-efficient manner. Can AI mirror this efficiency?
- Competing with Nature: As we develop AGI, we’re attempting to match the power of the human brain, which astonishingly uses just 20 watts.
- Evolution of Machines: The growth trajectory of AI models mirrors the historical rise of computers, reminiscent of the IBM 7090 era.
Key Insights:
- Current AI architectures may be overestimating power and compute needs.
- Local AI capabilities will likely outpace cloud models.
- A shift towards more efficient, less power-hungry AI is on the horizon.
As we navigate this landscape, are we underestimating the transformative potential of AI? 🤔
💬 Join the conversation! What’s your take on the future of AI and its market dynamics? Share your thoughts below!
