Scenario: At some point in the next ten years, a variety of AI models are starting to be broadly deployed in the economy. In an effort to begin automating their research process and ignite an intelligence explosion, a frontier AI lab designs a feedback loop to make their largest and...
Disclaimer: The views expressed in this document are my own, and do not necessarily reflect those of my past or present employers. In a recent interview at the Commonwealth Club of California, Stuart Russell compared training GPT-4 to training a dog with negative reinforcement. Although there are obvious (and not-so-obvious)...
Scenario: At some point in the next ten years, a variety of AI models are starting to be broadly deployed in the economy. In an effort to begin automating their research process and ignite an intelligence explosion, a frontier AI lab designs a feedback loop to make their largest and newest model (LLM-X) more agentic. In many respects, LLM-X resembles the reasoning models of today, but because it was trained on more than 100 times as much effective compute as its predecessor, it has significantly improved capabilities in many domains. Unlike today's models, LLM-X is often able to maintain a reasonable perspective on what its priorities are, allowing it to autonomously complete... (read 1130 more words →)
Disclaimer: The views expressed in this document are my own, and do not necessarily reflect those of my past or present employers.
In a recent interview at the Commonwealth Club of California, Stuart Russell compared training GPT-4 to training a dog with negative reinforcement. Although there are obvious (and not-so-obvious) limitations to this analogy, conceptualizing of GPT-4 as a partially domesticated, alien canine with a knack for Python code seems substantially more useful to me than calling it "[a mere program] run on the well-worn digital logic of pattern-matching" (which is how Cal Newport recently characterized the mind of ChatGPT, despite the sparks of AGI in GPT-4).[1] In any case, Russell's comparison prompted me... (read 6287 more words →)