🧠AI’s $100bn question: The scaling ceiling
The reason experts are so split on whether or not we're on an exponential path to AI is that intelligence is multi-dimensional. You can be both exponentially exploding/scaling in one dimension and stagnating in another. You can be both superhuman and subhuman at the same time. People tend to focus on the dimensions most salient to their inclination... See more
The mainstream narrative around AI has changed from “maybe the hype will blow over” to “guess this is the next big thing,” but people disagree about how big. Bigger than social media? Bigger than smartphones? Bigger than fire?
Eli Lifland • Ai 2027
You need to scale, but not necessarily by increasing headcount. Instead, scale through synthetic capacity:
AI workflows.
AI agents.
AI tools.
AI Is Evolving —And Changing Our Understanding Of Intelligence | NOEMA
Blaise Agüera y Arcasnoemamag.com
In three words: deep learning worked.
In 15 words: deep learning worked, got predictably better with scale, and we dedicated increasing resources to it.
That’s really it; humanity discovered an algorithm that could really, truly learn any distribution of data (or really, the underlying “rules” that produce any distribution of data). To a shocking deg... See more
In 15 words: deep learning worked, got predictably better with scale, and we dedicated increasing resources to it.
That’s really it; humanity discovered an algorithm that could really, truly learn any distribution of data (or really, the underlying “rules” that produce any distribution of data). To a shocking deg... See more