Expanding AI's Memory: Google's Infini-attention

Infini-attention is a new approach directly integrating a compressive memory system into the standard Transformer model.

This feature helps the AI handle large amounts of information more effectively.

It does this by combining two methods of focusing on data:

•⁠ ⁠Local Attention: This is like having a spotlight that focuses closely on specific parts of the information at a time, which helps in understanding details.

•⁠ ⁠Long-Term Linear Attention: This is like zooming out for a broader view, helping the AI to remember and use information from much earlier in the text.

The dual attention mechanism operates within a single Transformer block, effectively maintaining performance while managing longer sequences.

If we thought Gemini's 1 million context window was impressive, imagine being able to feed endless data to a model.

This technology opens many new possibilities for developing AI tools that learn and operate over significantly longer timescales and data sequences.

Paper -> https://lnkd.in/e6qsRBC5