In this episode, host Peter Wang is joined by Dr. Patrick Kavanagh, an astrophysicist and software developer at the Dublin Institute for Advanced Studies. Patrick works on the James Webb Space Telescope (JWST), helping to write code that allows scientists to interpret the raw data they receive from space.

Patrick talks to Peter about cleaning telescope data sets to make them more scientifically useful, and more. Patrick's team working on the Mid-Infrared Instrument on the JWST writes software in Python to help deliver science-ready data to astronomers and astrophysicists. Patrick's work facilitates more precise study of distant stars and galaxies in a way that fosters public trust.

Peter Wang - https://www.linkedin.com/in/pzwang/

Dublin Institute for Advanced Studies - https://www.linkedin.com/school/dublin-institute-for-advanced-studies/

James Webb Space Telescope - https://webb.nasa.gov/

Check out these relevant resources:

• Dr. Patrick Kavanagh - EuroPython
• Python and James Webb
• Judy Schmidt (citizen scientist)

If you enjoyed today's show, please leave a 5-star review. For more information, visit anaconda.com/podcast.

#Computing #AI #Data #DataScience #Analytics

In the penultimate episode of season one, host Peter Wang and Carl Meyer, Software Engineer at Instagram (owned by Meta), discuss considerations around making Python faster while maximizing compatibility and performance.

Several years ago, Carl and his team started working on a project called Cinder in an effort to improve CPU efficiency across Meta's servers by "[optimizing] things at the level of Python runtime." While initially meant to serve as a stop gap, Cinder yielded impressive wins that transformed it into a premier and ongoing project at Instagram.

In addition to Cinder, Peter and Carl discuss:

- Carl's experiences with various programming languages like TI-Basic, Perl, and PHP

- Challenges around innovating on an established language with 30+ years of history

- The potential evolution of Python use cases and best practices

- And more!

Peter Wang - https://www.linkedin.com/in/pzwang/

Carl Meyer - https://www.linkedin.com/in/carljm/

Instagram - https://www.linkedin.com/company/instagram/

Cinder - https://github.com/facebookincubator/cinder

If you enjoyed today's show, please leave a 5-star review. For more information, visit https://www.anaconda.com/podcast.

#Computing #AI #Data #DataScience #Analytics

This episode's conversation between host Peter Wang and Ryan Abernathey, Associate Professor at Columbia University in the City of New York, explores climate science, scientific computing, data accessibility, and more.

Topics that Peter and Ryan cover include:

- Cloud computing

- Open data and collaboration

- Climate science and the private sector

- Open-source projects like Pangeo Forge and Xarray

Climate data is sometimes restricted in the way it flows between interested parties; the growth of private industry around data storage and dissemination has put up barriers to entry that can limit access to valuable systems and data. This is especially troubling to Ryan because these barriers often exclude some of the people who are most affected by climate change. He feels that usable information can and should be made accessible without undermining private interests.

Peter Wang - https://www.linkedin.com/in/pzwang/

Ryan Abernathey - https://www.linkedin.com/in/ryan-abernathey-32a70652/

Columbia University in the City of New York - https://www.linkedin.com/school/columbia-university/

Pangeo Forge - https://pangeo-forge.org/

Xarray - https://docs.xarray.dev/en/stable/

You can find a human-verified transcript of this episode here. - https://know.anaconda.com/rs/387-XNW-688/images/ANACON_%20Ryan%20Abernathey_HVT.docx.pdf

If you enjoyed today's show, please leave a 5-star review. For more information, visit https://www.anaconda.com/podcast.