Sorry, forgot to add link to meet the speaker: https://calendar.google.com/calendar/selfsched?sstoken=UVBVTVF0X25Nd09LfGRlZmF1bHR8ZWQ5MmNlYWMxODI4OWVkNmUzNGU3OTE4ZDExMGI0YTk

On Mon, Sep 10, 2018 at 11:06 AM Michael Noukhovitch <mnoukhov@gmail.com> wrote:
This week we have Viral Shah from Julia Computing giving a talk on Fri September 14 2018 at 10:30 in room Z315 (in Pavilion Claire McNicoll). It's not our usual room but it'll be a regular room for the next two months :)

Will this talk be streamed ? Yes
And you can sign up to meet the speaker here:

if there's a tea talk, you should always GOTO it
Michael

TITLE On Machine Learning and Programming Languages

KEYWORDS ML/DL infrastructure, Programming Languages

ABSTRACT
We ask, what might the ideal ML language of the future look like? Our thoughts are published in this blog post: https://julialang.org/blog/2017/12/ml&pl As programming languages (PL) people, we have watched with great interest as machine learning (ML) has exploded -- and with it, the complexity of ML models and the frameworks people are using to build them. State-of-the-art models are increasingly programs, with support for programming constructs like loops and recursion, and this brings out many interesting issues in the tools we use to create them -- that is, programming languages. While machine learning does not yet have a dedicated language, several efforts are effectively creating hidden new languages underneath a Python API (like TensorFlow) while others are reusing Python as a modeling language (like PyTorch). We'd like to ask -- are new ML-tailored languages required, and if so, why?  Now that Julia 1.0 is released, we will also discuss how Julia evolved to get where it is today, and how it might evolve to taking on some of the challenges posed by machine learning

BIO
Dr. Viral Shah is a co-creator of the Julia project and Co-founder and CEO of Julia Computing. He has had a long-term track record of building open-source software. Apart from Julia, he is also co-creator of Circuitscape, an open-source program which borrows algorithms from electronic circuit theory for ecological conservation. In the Government of India, he was an early member of the country’s national ID project - Aadhaar, where his work on re-architecting India’s social security systems led to a significant increase in social and financial inclusion, while simultaneously saving the exchequer over a billion dollars in slippage. The experiences of implementing technology at such scale for a billion people are collected in his book: Rebooting India. Viral has a Ph. D. from the University of California at Santa Barbara, in Computer Science.