Linear Digressions
Technology

Linear Digressions

by Katie Malone

In each episode, your hosts explore machine learning and data science through interesting (and often very unusual) applications. 896520

101 episodes
EN language
All Episodes
1
The Bitter Lesson
19:17 Mar 15, 2026
2
From Atari to ChatGPT: How AI Learned to Follow Instructions
25:53 Mar 9, 2026
3
It's RAG time: Retrieval-Augmented Generation
17:14 Mar 2, 2026
4
Chasing Away Repetitive LLM Responses with Verbalized Sampling
19:12 Feb 23, 2026
5
We're Back
2:58 Feb 16, 2026
6
A Key Concept in AI Alignment: Deep Reinforcement Learning from Human Preferences
19:13 Feb 14, 2026
7
The Impact of Generative AI on Critical Thinking
25:33 Feb 14, 2026
8
So long, and thanks for all the fish
35:44 Jul 26, 2020
9
A Reality Check on AI-Driven Medical Assistants
14:00 Jul 19, 2020
10
A Data Science Take on Open Policing Data
23:44 Jul 13, 2020
11
Procella: YouTube's super-system for analytics data storage
29:48 Jul 6, 2020
12
The Data Science Open Source Ecosystem
23:06 Jun 29, 2020
13
Rock the ROC Curve
15:52 Jun 21, 2020
14
Criminology and Data Science
30:57 Jun 15, 2020
15
Racism, the criminal justice system, and data science
31:36 Jun 7, 2020
16
An interstitial word from Ben
5:59 Jun 5, 2020
17
Convolutional Neural Networks
21:55 May 31, 2020
18
Stein's Paradox
27:02 May 24, 2020
19
Protecting Individual-Level Census Data with Differential Privacy
21:19 May 18, 2020
20
Causal Trees
15:27 May 11, 2020
21
The Grammar Of Graphics
35:38 May 4, 2020
22
Gaussian Processes
20:55 Apr 27, 2020
23
Keeping ourselves honest when we work with observational healthcare data
19:08 Apr 20, 2020
24
Changing our formulation of AI to avoid runaway risks: Interview with Prof. Stuart Russell
28:58 Apr 13, 2020
25
Putting machine learning into a database
24:22 Apr 6, 2020
26
The work-from-home episode
29:06 Mar 29, 2020
27
Understanding Covid-19 transmission: what the data suggests about how the disease spreads
25:25 Mar 23, 2020
28
Network effects re-release: when the power of a public health measure lies in widespread adoption
26:40 Mar 15, 2020
29
Causal inference when you can't experiment: difference-in-differences and synthetic controls
20:48 Mar 9, 2020
30
Better know a distribution: the Poisson distribution
31:51 Mar 2, 2020
31
The Lottery Ticket Hypothesis
19:45 Feb 23, 2020
32
Interesting technical issues prompted by GDPR and data privacy concerns
20:26 Feb 17, 2020
33
Thinking of data science initiatives as innovation initiatives
17:27 Feb 10, 2020
34
Building a curriculum for educating data scientists: Interview with Prof. Xiao-Li Meng
31:36 Feb 2, 2020
35
Running experiments when there are network effects
24:45 Jan 27, 2020
36
Zeroing in on what makes adversarial examples possible
22:51 Jan 20, 2020
37
Unsupervised Dimensionality Reduction: UMAP vs t-SNE
29:34 Jan 13, 2020
38
Data scientists: beware of simple metrics
24:47 Jan 5, 2020
39
Communicating data science, from academia to industry
26:15 Dec 30, 2019
40
Optimizing for the short-term vs. the long-term
19:24 Dec 23, 2019
41
Interview with Prof. Andrew Lo, on using data science to inform complex business decisions
27:46 Dec 16, 2019
42
Using machine learning to predict drug approvals
25:00 Dec 8, 2019
43
Facial recognition, society, and the law
43:09 Dec 2, 2019
44
Lessons learned from doing data science, at scale, in industry
28:00 Nov 25, 2019
45
Varsity A/B Testing
36:00 Nov 18, 2019
46
The Care and Feeding of Data Scientists: Growing Careers
25:19 Nov 11, 2019
47
The Care and Feeding of Data Scientists: Recruiting and Hiring Data Scientists
20:16 Nov 4, 2019
48
The Care and Feeding of Data Scientists: Becoming a Data Science Manager
24:45 Oct 28, 2019
49
Procella: YouTube's super-system for analytics data storage
29:48 Oct 21, 2019
50
Kalman Runners
15:59 Oct 13, 2019
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