EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hacker News·9d ago·5 min read
What if AI worked at 1.000.000 tokens per seconds?
TL;DR
This thought experiment explores the implications of an AI processing 1,000,000 tokens per second, highlighting the complexities of input and output rates. It emphasizes that while parallel processing can increase throughput, individual stream completion times remain variable.
✦ Why It Matters
Consider the implications of token processing speeds when designing AI applications to set realistic performance expectations.
Key Takeaways
- Explore parallel processing capabilities in your AI models.
- Use interactive calculators to visualize token dynamics.
- Set realistic expectations for AI response times.
- Consider individual stream completion times in performance planning.
Full Summary
The concept of an AI operating at 1,000,000 tokens per second serves as a thought experiment rather than a current capability. It illustrates how a model's input and output rates differ, particularly when handling large requests.
For instance, processing 10,000 streams at 100 tokens per second achieves the total of 1,000,000 tokens per second, but this does not indicate when any single stream will finish. The article includes interactive calculators to help visualize these dynamics.
Understanding these mechanics is crucial for developers working with AI models, as it can influence design decisions and performance expectations. The exploration of token processing speeds sheds light on the potential and limitations of AI in real-time applications.