Claude 2, the latest conversational AI from Anthropic, contains roughly 12 billion parameters according to official company statements. This pales in comparison to models like OpenAI‘s GPT-3 at 175 billion parameters and Google‘s PaLM topping over 500 billion.
But Anthropic‘s constrained model size is intentional, stemming directly from their rigorous focus on AI safety and protocol they term "constitutional AI." So why exactly is Claude 2 so "small" relative to some competitors? And what tradeoffs does this entail?
The Significance of Parameters in Language Models
First, let‘s define what parameters mean for neural networks like Claude 2. Each connection between artificial neurons has an associated "weight" term that is adjusted during training to perform tasks better. These trainable weights plus "bias" terms that allow flexibility comprise a model‘s parameters.
So for Claude 2, 12 billion parameters means 12 billion such tuned weight and bias quantities across its entire network architecture that allow it to conduct natural language conversations. The more parameters, the more complex concepts a model can potentially learn to grasp.
For example, GPT-3 leverages 175 billion parameters to obtain impressively broad abilities – but at the cost of potential harms from emergent behavior in such an unfathomably large system.
Constitutional AI: Prioritizing Safety and Security
Anthropic intentionally constrains the scale of models like Claude 2 as part of their rigorous focus on AI safety through "constitutional AI":
"We develop AI systems using constitutional techniques to make them helpful, harmless, and honest."
Key facets of their approach include:
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Intelligibility – Claude 2 resists full optimization for scale to remain interpretable by humans. This allows better understanding of its reasoning and limitations.
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Controllability – More modestly sized models enable easier alignment techniques to be applied that are resilient to distributional shift.
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Auditability – Reducing overall parameters simplifies fact-checking for unintended biases and assessing model behaviors.
As Dario Amodei, Anthropic‘s CEO, stated, they want to prevent emergent risks:
"We intentionally opted for a model size small enough to meaningfully constrain emergent behavior while still being useful for conversations."
Responsible Plans for Gradual Scale Expansion
Make no mistake though – Anthropic does plan to dramatically expand Claude 2‘s model capacity over time. Their public roadmap sets goals to exceed 100 billion parameters by 2026.
But this will occur incrementally while rigorously enforcing constitutional guardrails:
- Staged Expansion – Model size will grow slowly through carefully defined steps instead of massive leaps.
- Adversarial Probing – Each proposed version undergoes extensive testing to measure sensitive attributes before approval.
- Parameter Caps – Growth trajectories have ambient limits based on what safety guarantees can be reasonably maintained.
This constitutionally-constrained approach is very different from the rapid 10x-100x model scale explosions we‘ve repeatedly seen in the AI field. Anthropic accepts some compromises in Claude‘s capabilities early on to allow responsible scaling while retaining security properties like auditability.
Claude 2 Parameter Count in Context
To put Claude 2‘s 12 billion parameters into context, here is how model size has evolved for several prominent natural language AI systems over recent years:
| Model | Year Introduced | Parameters |
|---|---|---|
| GPT-3 | 2020 | 175 billion |
| PaLM | 2022 | 540 billion |
| Claude | 2022 | 12 billion |
| GPT-2 | 2019 | 1.5 billion |
| BERT | 2018 | 340 million |
As you can see, Claude 2 sits far below leading models but well above early predecessors – a very intentional choice by Anthropic to strike a balance.
Conclusion
In summary, Claude 2 relies on 12 billion trainable parameters to conduct informative conversations while avoiding potential downsides from massive models that evade understanding or control.
Anthropic‘s focus on constitutional AI contends with ethical dilemmas head-on by constraining scale and retaining strict safety standards. But Claude will gradually grow in knowledge – they plan for over 100 billion parameters by 2026 through a staged roadmap centered on transparency and oversight.
This principled approach allows Claude to help users while avoiding unintended harm – the core of Anthropic‘s mission as leaders in AI safety.
