|
writer: |
|
|
topics:
|
|
|
source: |
|
|
summary: |
Ethan Mollick explores the driving force behind recent AI advancements: the pursuit of scale. Larger models, trained on more data with greater computing power, exhibit increased capabilities. This 'scaling law' has propelled AI into successive generational leaps, from ChatGPT's Gen1 to GPT-4's Gen2. Mollick outlines the five frontier Gen2 models (GPT-4o, Claude, Gemini, Grok 2, Llama) and their relative strengths. However, a newly discovered 'thinking' scaling law, demonstrated by OpenAI's o1 models, suggests AI can continue improving by allocating more compute to reasoning -- even if training scale hits limits. This dual-scaling approach virtually guarantees accelerated AI progress, bringing independent AI agents and complex problem-solving closer to reality.
|
> Please log in to post a comment.
Scaling: The State of Play in AI →
Writer
Ethan Mollick
Summary
Ethan Mollick explores the driving force behind recent AI advancements: the pursuit of scale. Larger models, trained on more data with greater computing power, exhibit increased capabilities. This 'scaling law' has propelled AI into successive generational leaps, from ChatGPT's Gen1 to GPT-4's Gen2. Mollick outlines the five frontier Gen2 models (GPT-4o, Claude, Gemini, Grok 2, Llama) and their relative strengths. However, a newly discovered 'thinking' scaling law, demonstrated by OpenAI's o1 models, suggests AI can continue improving by allocating more compute to reasoning -- even if training scale hits limits. This dual-scaling approach virtually guarantees accelerated AI progress, bringing independent AI agents and complex problem-solving closer to reality.
> Please log in to post a comment.