Gtifn
Re:Tensorflow sucks
on Monday October 09, 2017 @10:53AM (#15434264)
https://fluxml.github.io/
In julia
Re:Tensorflow sucks
on Monday October 09, 2017 @10:52AM (#15434255)
Julia: https://fluxml.github.io/
Business model/plan(ing) for research heavy early stage ML startup
Hi everyone,Most information business planning aspects of tech startups applies to commercializing ideas that are closer to an MVP, are based on just engineering on top of some conventional science/technology or are reasonably close to execution.For a startup that is embarking on years of basic scientific research before we even have a prototype, how can they maintain focus in strategy and...
Re:The Limitations of Deep Learning
on Monday July 17, 2017 @06:49PM (#14792914)
What do you think about a bayesian interpretation of the above as MAP/MLE?
Re:Exploring Lazy Evaluation with Julia
on Monday June 05, 2017 @12:12PM (#14488727)
cool! How's the performance?
Re:Julia 0.6.0-rc1 new language features
on Tuesday May 09, 2017 @02:18PM (#14302558)
Are you talking about breaking modules (like linalg) out of base or changing the semantics and mechanics of modules?
I think the former is planned before 1.0?
If the latter, what do you think is the issue? Do you not like julia packages are separated into interface/abstract implementation and then concrete packages that can then have submodules that call each other?
Seems more modular than working around a python inheritance mess.
Re:Forecasting with Julia
on Tuesday May 09, 2017 @01:57PM (#14302385)
What languages do you use?
Re:CRISPR eliminates HIV-1 infection in live animals
on Tuesday May 02, 2017 @04:59PM (#14250516)
Just for biotech?
Re:Using D and std.ndslice as a Numpy Replacement
on Sunday January 03, 2016 @05:50PM (#10832958)
Thanks very much for your thoughts.
What do you think about the foundational tech of numba itself?
Do you think it is any more of a black box than say Julia? Is there anything about it that would impede extension into a more stable, predictable and feature rich product?
BTW looks like Intel is doing some stuff with Julia: https://github.com/IntelLabs/ParallelAccelerator.jl
There has also been alot of recent funding to Continuum and dev of numba seems to be going strong. Also some recent work with AMD.
Re:Using D and std.ndslice as a Numpy Replacement
on Sunday January 03, 2016 @05:02PM (#10832699)
As a former member of the Numba team, what is your outlook on the technology and the broader continuum ecosystem?
I'm looking at Numba and friends (Dynd, blaze) for a new stack, but I'm not sure where the development arc will end up vs say Julia. I'm also curious about the sustainability of Continuum's business model and practices in the medium and long term.
Any thoughts on this? I understand if you are limited in what you can say, but I'm open to any nuggets.
Re:Elemental: C++ library for distributed-memory linear algebra and op...
on Tuesday December 29, 2015 @12:11PM (#10807641)
I think distributed's scheduler has seen much iteration since then and is now based on tornado. I wonder if that changes your assessment.
Also what do you think of Julia's native distributed capabilities and this library here: https://github.com/shashi/ComputeFramework.jl
Re:Elemental: C++ library for distributed-memory linear algebra and op...
on Monday December 28, 2015 @09:31PM (#10804818)
How about dask's distrubted array? Do you know how the architecture and goals compare to Elemental?