[gopalv]

> Many of us have a strong sense that the future of ML involves models built by large teams in industry environments

The gradient of current moment is that whatever approach is optimized to use more data and more compute is much easier to invest in than something which can do more with less, but with a significant number of possible dead-ends.

At some point, this will have diminishing returns, but until that is hit, this makes sense as a purely return-on-investment for both research progress and business returns.