Darwin’s finches sprinted to evolve when food sources changed. For decades, nothing—then sudden transformation. AI follows the same pattern & it’s accelerating.
Every morning, I wake up wondering what breakthrough will propel the ecosystem forward.
Last week, it was DeepSeek v2. This morning, a Hugging Face researcher announced that he could induce reasoning on the major advance of the last three months in one of the smallest models, a 3B parameter model.
The pace of innovation hasn’t stalled. The S-curve growth in model performance continues. But faster!

The first birds of AI soared with sheer scale—massive datasets and vast transformer architectures.
Their children specialized, dividing large models into smaller, more efficient Mixture of Experts (MoE) architectures.
Their grandchildren now do something even more remarkable: narrating their reasoning, self-correcting, and improving their own responses.
Here’s a rough timeline of how AI evolution has compressed in just the last two years:

GPT-4 set a new performance benchmark in ELO, an overall AI benchmark. Claude 3 surpassed it 366 days later.
GPT-4 Turbo set the next high bar, which Gemini 1.5 Pro matched just 11 days later.
GPT-4.0, the first model with true deep reasoning, arrived in September 2024. Google’s Gemini 2 Deep Reasoning matched it 141 days later.
This year, DeepSeek achieved the same level of reasoning—this time in just 41 days.

We’ve gone from year-long leaps to breakthroughs happening within weeks. The trend is clear: compression of progress. What once took years now takes months, then weeks, and soon, perhaps, mere days.
At this rate, the next AI revolution might not just arrive in the next quarter—it might arrive by the time you wake up tomorrow.
Who knows what that bird will look like?
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