Fwd: FW: S3D Distinguished Speakers Series: Satish Chandra - Tuesday 11/12

[Artur Dubrawski]

I know this will be of interest to many of us.

Cheers
Artur

---------- Forwarded message ---------
From: Linda Campbell <lv2c at andrew.cmu.edu>
Date: Tue, Nov 12, 2024, 2:24 AM
Subject: FW: S3D Distinguished Speakers Series: Satish Chandra - Tuesday
11/12
To: <ml-seminar at cs.cmu.edu>


S3D Distinguished Speakers Series



Tuesday, November 12, 2024

12:00 p.m. – 1:15 p.m.   Google calendar
<https://calendar.google.com/calendar/event?action=TEMPLATE&tmeid=MXZsZHM5bHI3MGhjdjhpbmoxMThmZWdmbWIgYW5kcmV3LmNtdS5lZHVfbjBscGtkaWFyYTJhdWhqaXVjbmpsbmVoYzhAZw&tmsrc=andrew.cmu.edu_n0lpkdiara2auhjiucnjlnehc8%40group.calendar.google.com>

In person at TCS 358

Overflow/watch room TCS 460

Or online via Zoom:
https://cmu.zoom.us/j/98473836934?pwd=Sm1ZK0dzamF4eEZHNmlGbFFYK0RmQT09
*Lunch provided starting at 11:40 a.m.*



*Title:*  AI in Software Engineering at Google



*Speaker:*  Satish Chandra, Principal Engineer, Core Developer Group, Google



*Abstract:*  The availability of large code corpora, coupled with advances
in machine learning have made it possible to build software development
tools grounded in statistical principles, paving way for capabilities that
were not possible with technologies that relied on program semantics alone.
In the last couple of years, large language models have taken the world by
storm, and have shown remarkable ability to create, explain, critique and
debug code.   In this talk, I will provide an overview of this area both
from a research as well as technology point of view. I’ll describe how at
Google we have been working on weaving AI capabilities in developer
workflows, how we collect data, how we prioritize our work, and the impact
that this work is showing. I will discuss how model quality and user
experience interact in interesting ways that have a material implication on
the success of such tools. I will share some thoughts on how the field is
evolving from its erstwhile focus on code completion to higher-level
tasks.  Finally, I will discuss the role of benchmarks in our community,
and what we can do to push the state of the art together at a higher pace.



*Bio:*  Satish Chandra is a researcher at Google, where he applies machine
learning techniques to improve developer productivity. His work has spanned
many areas of programming languages and software engineering, including
program analysis, type systems, software synthesis, bug finding and repair,
software testing and, of course, application of AI to software development.
His research has been widely published in leading conferences in his
field.  Satish Chandra obtained a PhD from the University of
Wisconsin-Madison, and a B.Tech from the Indian Institute of
Technology-Kanpur, both in computer science. He is an ACM Distinguished
Scientist and an elected member of WG 2.4.



*Upcoming S3D Seminar Series Talks*



January 29:  Nick Feamster*

February 5:  Vladimir Filkov*

April 30:  Danah Boyd*



Links available to recordings are here.  Usually published a couple of days
after the talk.

https://s3d.cmu.edu/events/distinguished.html
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