University of Delaware

Department of Physics and Astronomy

Biden School of Public Policy and Administration

Data  Science Institute

also Rubin...

federica b. bianco

she/her

AI literacy can save us (... well, if anything can)

Do Androids Dream of Exploding Stars?

University of Delaware

Department of Physics and Astronomy

Biden School of Public Policy and Administration

Data  Science Institute

federica b. bianco

she/her

Grad student

Since 2019 we study the sky (and more!) mostly with AI

Postdoc

experiment driven science -∞:1900

theory driven science 1900-1950

the fourth paradigm - Jim Gray, 2009

computationally driven science 1950-1990

experiment driven science -∞:1900

theory driven science 1900-1950

the fourth paradigm - Jim Gray, 2009

computationally driven science 1950-1990

Frank Rosenblatt, 1958

The Navy revealed the embryo of an electronic computer today that it expects will be able to walk, talk, see, write, reproduce itself and be conscious of its existence.

The embryo - the Weather Buerau's $2,000,000 "704" computer - learned to differentiate between left and right after 50 attempts in the Navy demonstration

NEW NAVY DEVICE LEARNS BY DOING; Psychologist Shows Embryo of Computer Designed to Read and Grow Wiser

July 8, 1958

when did the first Neural Network in astronomy review came out?

Join at

slido.com

#1771 215

1988

CSP: Constraint Satisfaction Problems

1988

early 1990s

number of arXiv:astro-ph submissions with abstracts containing one or more of the strings: ‘machine learning’, ‘ML’, ‘artificial intelligence’, ‘AI’, ‘deep learning’ or ‘neural network’.

"In 1994, Ofer Lahav, an early trailblazer, wryly identified the ‘neuro-skeptics’—those resistant to the use of such techniques in serious astrophysics research—and argued that ANNs ‘should be viewed as a general statistical framework, rather than as an estoteric approach’ [8]. Unfortunately, this scepticism has persisted. This is despite the recent upsurge in the use of neural networks (and machine learning in general) in the field [...] Most of the criticism of machine learning techniques, and deep learning in particular, is levelled at the perceived ‘black box’ nature of the methodology."

Input (observables)

x

y

Output

(observable)

??

x

y

physics

Input (observables)

Output

(observable)

Input

x

y

Prediction

function

Input

x

y

b

m

m: slope 

b: intercept

Prediction

Input

x

y

b

m

m: slope 

b: intercept

parameters

x

y

learn

goal: find the right m and b that turn x into y

goal: find the right m and b that turn x into y

Prediction