[talolard]

I have a question on the compute aspect regarding your business model, hope I’m not being to nosy..

I tried HL, the experience was stellar (well done!) and it made me think...

To get AL working with a great user experience you need quite a bit of compute. How are you thinking about your margins, e.g the cost to produce what you’re offering versus what customers will pay for it?

[peadarohaodha]

Thanks for the feedback! It's a good question re compute. There are some fun engineering and ML research challenges that we are constantly iterating on that are related to this. A few examples - how to most efficiently share compute resources in a JIT manner (e.g. GPU memory) during model serving for both training and inference (where the use case and privacy requirements permit) - how to construct model training algorithms that operate in a more online manner effectively (so you don't have to retrain on the whole dataset when you see new examples) - how to significantly reduce the model footprint (in terms of memory and flops) of modern deep transformer models given they are highly over-parameterised and can contain a lot of redundancy.

this stuff helps us a lot on the margins point!