
Leaf ML framework ends development - andr
https://medium.com/@mjhirn/tensorflow-wins-89b78b29aafb#.ndfvodxov
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ktamura
What's really sad about this is that they had to give up Leaf because the
whole thing was VC-backed. Commercial support is a huge part of open source
software's viability.

I applaud their decision to pivot and shift their focus elsewhere to win. That
said, the irony is too great for me not to mention: open sourcing is now
recognized as a hugely democratizing force in the software world to upend
commercial giants, yet it's commercial giants that can afford to invest in the
long run and support open source projects (so that they can increase the
sphere of their influence).

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mjhirn
Thanks for sharing on HN. Rust community's discussion on Reddit:
[https://www.reddit.com/r/rust/comments/4ij2ub/googles_tensor...](https://www.reddit.com/r/rust/comments/4ij2ub/googles_tensorflow_wins_leaf_loses/)

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fchollet
They place an emphasis on Github star count, but that is a terrible usage
metric. Leaf got a lot of stars because it got a lot of HN exposure, but at
the same time Leaf had no users. Assumedly _that 's_ the real reason why they
are stopping development.

Here are the metrics that matter.

Over the lifetime of the project:

\- 14 contributors

\- 40 issues opened

\- 161 forks

In the past month:

\- 7 issues opened

\- 6 PRs opened

In the past week:

\- 0 issues opened

\- 0 PRs opened

In other words, a ghost town. The lesson here is that a lot of HN exposure
does not automatically convert into a lot of users.

~~~
mjhirn
Yes, we had trouble to attract the right community and convert the stars into
recurrent contributions, as there was less overlap between the Rust and the
general ML community than we anticipated. This bothered us a lot and played a
role in our decision to suspend Leaf.

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visarga
This is sad. Diversity of implementations is a plus.

