[arauhala]

Aito builds a model for predictive queries in millisecond scale. It requires heavy optimizations and preparations in DB to reach the performance. The indexes are optimized for statistics, and there are extra datastructures not found in normal DBs.

The ML is also implanted inside the database to minimize various overheads, and to have direct access to data & invested. if you need to do thousands of statistical operations in 10ms, just IPC can become a huge overhead. You want to put data & math in same process.

Overall, its all based on tight AI+DB integration to enable the instant modeling.

[lumost]

can you share details about the "instant modeling" capability? while simple copula's and correlation matrices may be calculable in milliseconds, larger models are likely to have more performance considerations and training latencies.

[arauhala]

It's done for discrete data. Operations on such data can be optimized to pretty extreme level. Aito scales to around million rows and million features before slowing down too much.

We believe we can make it scale to 10m or 100m rows in the future. Maybe more

[lumost]

got it, any plans on supporting models requiring backprop/gradient descent?