AD – Thanks to Skillshare for sponsoring this video! The first 500 people to use my link will receive a free one-month trial of Skillshare: https://skl.sh/drbecky07241 | AI, or artificial intelligence, seems to be a buzzword that cannot be escaped these days. It's everywhere. And astrophysics is no exception with a steady increase in the number of published research papers using or mentioning AI tools such as machine learning and deep learning. In this video, let's discuss what AI actually is: what can it do, what can't it do, because there's a lot of misinformation, before discussing 4 ways we as astrophysicists use AI AI: i) data classification, ii) finding strange things (anomaly detection), iii) data inference and iv) simulation emulation. This is by no means an exhaustive list, I'm sure many of my colleagues are also using AI in other ways for research, not to mention using well-known tools like GitHub's Copilot for help write code, or chatGPT to help with inspiration when trying to summarize research papers or grant proposals into abstracts. AI may have changed the way we work as astrophysicists, but it has not yet changed astrophysics itself. The key word though is *yet*, because with the rate of AI advancement we're seeing, who knows what the next decade might bring!

Classify galaxy shapes in images from the all-new Euclid Telescope to help train an AI deep learning algorithm – https://galaxyzoo.org/

Discover Katie Bouman's TED talk explaining how the black hole image is made by the Event Horizon Telescope team: https://www.youtube.com/watch?v=BIvezCVcsYs

Smith and Geach (2023) – https://arxiv.org/pdf/2211.03796
Kembhavi and Pattnaik (2022) – https://link.springer.com/article/10.1007/s12036-022-09871-2
Fotopoulou (2024) – https://arxiv.org/pdf/2406.17316
Huppenkothen et al. (2023) – https://arxiv.org/pdf/2310.12528
Walmsley et al. (2020) – https://arxiv.org/pdf/1905.07424
Walmsley et al. (2023) – https://joss.theoj.org/papers/10.21105/joss.05312
Bowles et al. (2021) – https://arxiv.org/pdf/2012.01248
Huertas-Company et al. (2023) – https://arxiv.org/pdf/2305.02478
Robertson et al. (2023) – https://arxiv.org/pdf/2208.11456
Yu et al. (2019) – https://arxiv.org/pdf/1904.02726
Osborn et al. (2020) – https://arxiv.org/pdf/1902.08544
Muthukrishna et al. (2019) – https://arxiv.org/pdf/1902.08544
Sooknunan et al. (2021) – https://arxiv.org/pdf/1811.08446
Cheng et al. (2021) – https://arxiv.org/pdf/2009.11932
Tohill et al. (2024) – https://arxiv.org/pdf/2306.17225
Muthukrishna et al. (2022) – https://arxiv.org/pdf/2111.00036
Pérez-Carrasco et al. (2023) – https://iopscience.iop.org/article/10.3847/1538-3881/ace0c1
Mohale and Lochner (2024) -https://arxiv.org/pdf/2311.14157
Angeloudi et al. (2024) – https://arxiv.org/pdf/2407.00166
Rose et al. (2024) – https://arxiv.org/pdf/2405.00766
Conceição et al. (2024) – https://arxiv.org/pdf/2304.06099

00:00 – Presentation
01:33 – What is AI? Machine learning vs deep learning
05:46 – AD – Skills sharing
07:17 – (i) Data classification
11:21 a.m. – (ii) Anomaly detection
13:29 – (iii) Data inference
3:07 p.m. – (iv) Simulation emulation
5:40 p.m. – The impact of AI on astrophysics
7:19 p.m. – Bloopers

Video filmed on a Sony ⍺7 IV

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My new book, /"A Brief History of Black Holes/

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