Benjamin Laufer
@laufer.bsky.social
PhD student at Cornell Tech.
bendlaufer.github.io
bendlaufer.github.io
We describe these details in the paper, e.g. in the schematic below.
August 14, 2025 at 4:26 PM
We describe these details in the paper, e.g. in the schematic below.
Big picture: By treating ML models like organisms in an ecosystem, we can:
🌱 Understand the pressures shaping AI development
🔍 Spot patterns before they become industry norms
🛠 Inform governance & safety strategies grounded in real data
🌱 Understand the pressures shaping AI development
🔍 Spot patterns before they become industry norms
🛠 Inform governance & safety strategies grounded in real data
August 14, 2025 at 3:06 PM
Big picture: By treating ML models like organisms in an ecosystem, we can:
🌱 Understand the pressures shaping AI development
🔍 Spot patterns before they become industry norms
🛠 Inform governance & safety strategies grounded in real data
🌱 Understand the pressures shaping AI development
🔍 Spot patterns before they become industry norms
🛠 Inform governance & safety strategies grounded in real data
We found optimal evolutionary orderings over traits:
🔹 Feature extraction tends to be upstream from text generation. Text generation is upstream from text classification.
🔹 Certain license types precede others (e.g., llama3 → apache-2.0)
Here we show the top-20 licenses transitions over fine-tunes.
🔹 Feature extraction tends to be upstream from text generation. Text generation is upstream from text classification.
🔹 Certain license types precede others (e.g., llama3 → apache-2.0)
Here we show the top-20 licenses transitions over fine-tunes.
August 14, 2025 at 3:06 PM
We found optimal evolutionary orderings over traits:
🔹 Feature extraction tends to be upstream from text generation. Text generation is upstream from text classification.
🔹 Certain license types precede others (e.g., llama3 → apache-2.0)
Here we show the top-20 licenses transitions over fine-tunes.
🔹 Feature extraction tends to be upstream from text generation. Text generation is upstream from text classification.
🔹 Certain license types precede others (e.g., llama3 → apache-2.0)
Here we show the top-20 licenses transitions over fine-tunes.
In biology, traits get passed from parent to child — mutations are slow & often modeled as random.
In AI model families, mutations are fast and directed. Two sibling models tend to resemble each other more than they resemble their shared parent.
In AI model families, mutations are fast and directed. Two sibling models tend to resemble each other more than they resemble their shared parent.
August 14, 2025 at 3:06 PM
In biology, traits get passed from parent to child — mutations are slow & often modeled as random.
In AI model families, mutations are fast and directed. Two sibling models tend to resemble each other more than they resemble their shared parent.
In AI model families, mutations are fast and directed. Two sibling models tend to resemble each other more than they resemble their shared parent.
We measured “genetic similarity” between models from snippets of text - the metadata and model cards.
Models in the same finetuning family do resemble each other… but the evolution is weird. For example, traits drift in the same directions again and again.
Models in the same finetuning family do resemble each other… but the evolution is weird. For example, traits drift in the same directions again and again.
August 14, 2025 at 3:06 PM
We measured “genetic similarity” between models from snippets of text - the metadata and model cards.
Models in the same finetuning family do resemble each other… but the evolution is weird. For example, traits drift in the same directions again and again.
Models in the same finetuning family do resemble each other… but the evolution is weird. For example, traits drift in the same directions again and again.
In a new paper with @didaoh and Jon Kleinberg, we mapped the family trees of 1.86 million AI models on Hugging Face — the largest open-model ecosystem in the world.
AI evolution looks kind of like biology, but with some strange twists. 🧬🤖
AI evolution looks kind of like biology, but with some strange twists. 🧬🤖
August 14, 2025 at 3:06 PM
In a new paper with @didaoh and Jon Kleinberg, we mapped the family trees of 1.86 million AI models on Hugging Face — the largest open-model ecosystem in the world.
AI evolution looks kind of like biology, but with some strange twists. 🧬🤖
AI evolution looks kind of like biology, but with some strange twists. 🧬🤖
Big picture: By treating ML models like organisms in an ecosystem, we can:
🌱 Understand the pressures shaping AI development
🔍 Spot patterns before they become industry norms
🛠 Inform governance & safety strategies grounded in real data
🌱 Understand the pressures shaping AI development
🔍 Spot patterns before they become industry norms
🛠 Inform governance & safety strategies grounded in real data
August 14, 2025 at 2:59 PM
Big picture: By treating ML models like organisms in an ecosystem, we can:
🌱 Understand the pressures shaping AI development
🔍 Spot patterns before they become industry norms
🛠 Inform governance & safety strategies grounded in real data
🌱 Understand the pressures shaping AI development
🔍 Spot patterns before they become industry norms
🛠 Inform governance & safety strategies grounded in real data
We found optimal evolutionary orderings over traits:
🔹 Feature extraction tends to be upstream from text generation. Text generation is upstream from text classification.
🔹 Certain license types precede others (e.g., llama3 → apache-2.0)
Here we show the top-20 licenses transitions over fine-tunes.
🔹 Feature extraction tends to be upstream from text generation. Text generation is upstream from text classification.
🔹 Certain license types precede others (e.g., llama3 → apache-2.0)
Here we show the top-20 licenses transitions over fine-tunes.
August 14, 2025 at 2:59 PM
We found optimal evolutionary orderings over traits:
🔹 Feature extraction tends to be upstream from text generation. Text generation is upstream from text classification.
🔹 Certain license types precede others (e.g., llama3 → apache-2.0)
Here we show the top-20 licenses transitions over fine-tunes.
🔹 Feature extraction tends to be upstream from text generation. Text generation is upstream from text classification.
🔹 Certain license types precede others (e.g., llama3 → apache-2.0)
Here we show the top-20 licenses transitions over fine-tunes.
In biology, traits get passed from parent to child — mutations are slow & often modeled as random.
In AI model families, mutations are fast and directed. Two sibling models tend to resemble each other more than they resemble their shared parent.
In AI model families, mutations are fast and directed. Two sibling models tend to resemble each other more than they resemble their shared parent.
August 14, 2025 at 2:59 PM
In biology, traits get passed from parent to child — mutations are slow & often modeled as random.
In AI model families, mutations are fast and directed. Two sibling models tend to resemble each other more than they resemble their shared parent.
In AI model families, mutations are fast and directed. Two sibling models tend to resemble each other more than they resemble their shared parent.