Austin, TX
Article
Austin, TX is a recurring place in the Astral Codex Ten archive, appearing 3 times across 3 issues between August 23, 2021 and April 10, 2023. The archive places it in contexts such as “AUSTIN, TX ( RSVP )”; “in Austin, TX this summer”; “Location: The Brewtorium, 6015 Dillard Cir A, Austin, TX 78752”. It most often appears alongside ACX, Athens, Boston.
Metadata
- Category: Places
- Mention count: 3
- Issue count: 3
- First seen: August 23, 2021
- Last seen: April 10, 2023
Appears In
- Meetups Everywhere 2021: Times And Places
- ACX Grants ++: The First Half
- Spring Meetups Everywhere 2023
Related Pages
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- ACX (3 shared issues)
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- Athens (3 shared issues)
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- Boston (3 shared issues)
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- Cambridge (3 shared issues)
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- facebook (3 shared issues)
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- Germany (3 shared issues)
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- India (3 shared issues)
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- Israel (3 shared issues)
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- Japan (3 shared issues)
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- Nigeria (3 shared issues)
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- Oxford (3 shared issues)
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- Scott (3 shared issues)
External Links
Source Context
Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.
AUSTIN, TX (RSVP) Contact: Silas Barta, sbarta[at]gmail[dot]com Time: 1:30 PM, Saturday, October 2 Location: Tables in the park area by pond behind Central Market 4001 N. Lamar Coordinates: https://w3w.co/loosed.balloons.elastic
Inline links: RSVP, https://w3w.co/loosed.balloons.elastic
#29: Present An Open-Source Python Library For Monte Carlo Techniques At the heart of all serious forecasting is a statistical tool known as Monte Carlo analysis. It allows you to quantify uncertainty by introducing randomness to the inputs of computational models and looking at the range of results. If you want a good example, you might recognize Monte Carlo techniques from Nate Silver’s election forecasts at 538. It's been a gold-standard throughout my career in the space industry, and I can attest to how powerful it is - I've used it to successfully send a rocket to Mars. However, there aren't any tools out there that make it easy for researchers to take their existing models and wrap a Monte Carlo around it. So, I wrote one. It's an open-source python library which I'm calling "monaco". I'm at a point in development where the basic feature set is complete and working well, and I'm looking to finish up the extended roadmap in the next few months. See the project github page for the code, examples, and a lot more info: https://github.com/scottshambaugh/monaco. I’m looking for $1000 to help me present version 1.0 of this tool to the scientific community at the 2022 SciPy Conference in Austin, TX this summer. That amount should cover conference fees, hotel, and airfare, and if you're feeling generous I could use additional funds for some external monitors and cloud compute time. My name is Scott Shambaugh, and if you’re interested in helping fund this please email me at wsshambaugh AT gmail.com. Thank you!
AUSTIN, TEXAS, USA Contact: Silas Barta Contact Info: sbarta[at]gmail[dot]com Time: Saturday, June 03rd, 12:00 PM Location: The Brewtorium, 6015 Dillard Cir A, Austin, TX 78752 Coordinates: https://plus.codes/862487GM+95 Event Link: https://www.lesswrong.com/events/HXxiXZ2xwDE9mK84L/austin-tx-acx-shelling-meetup-2023