Trying to make sense of the numbers alongside GenAI models making your head hurt? 405B, 7B, 70B … lets try and clear things up.
TDLR; those numbers are parameters. 7 Billion, 70 Billion parameters or adjustable levers to configure the model.
The magic of LLMs lies in the math! Parameters are the Building Blocks of AI Brains 🧠 Parameters are the adjustable values that an LLM uses to make predictions. Think of them as the AI’s neurons, working together to process and generate language.
High Parameter Models like Meta new Llama3.1 405B
👍 Pros:
▶ Unparalleled accuracy: They can capture subtle patterns and relationships in language, leading to state-of-the-art results.
▶ Flexibility: With more parameters, these models can adapt to a wide range of tasks and domains.
▶ More nuanced understanding
▶ Better at complex tasks
▶ Broader knowledge base
👎 Cons:
▶ Require more computational power
▶ Longer training time
▶ Potentially higher costs
Low Parameter Models like OpenAI GPT-4o-mini (~8B):
👍 Pros:
▶ Efficiency: They require less computational power, making them more accessible and environmentally friendly.
▶ Faster inference
▶ Lower computational requirements
▶ Easier to deploy on devices – think Edge AI
👎 Cons:
▶ Simplified accuracy: While still impressive, these models might not achieve the same level of accuracy as their high-parameter counterparts.
▶ Limited flexibility: With fewer parameters, these models might not be as adaptable to different tasks and domains.
▶ May struggle with nuanced tasks
▶ Limited knowledge breadth
Related to the parameters are Model Weights, AKA The Crown Jewels of AI 👑
Model weights are the specific values assigned to parameters after training. They represent the model’s learned knowledge and are crucial to its performance. Some foundational model owners chose to make model weights available to the public and some chose to keep them private.
Why Keep Them Secret?
▶ Protect intellectual property
▶ Prevent misuse or creation of malicious models
▶ Maintain competitive advantage
Why Open Them Up?
▶ Foster innovation and research
▶ Enable model fine-tuning for specific applications
▶ Promote transparency and trust in AI
The numbers game in AI is complex, but understanding it is key to grasping the future of technology. Whether you’re a tech enthusiast or a business leader, knowing these numerical nuances can help you build your AI Literacy.
