PodcastsRank #37287
Artwork for Tomayto Tomahto

Tomayto Tomahto

EducationPodcastsENunited-states
5 / 5
I say tomayto, but you say tomahto. Why? What cognitive, economic, racial, or social factors led you to say tomahto and I tomayto? How did you acquire the ability to produce and perceive coherent sentences? These are some questions that linguists attempt to answer scientifically. Led by Talia Sherman, a Brown University undergrad, this podcast explores language: what it is, how it works (both cognitively and in practice), and its relationship to politics, history, pedagogy, AI, neuroscience, psychology, anthropology, computation, and more! Questions? Email tomaytotomahtopodcast@gmail.com
Top 74.6% by pitch volume (Rank #37287 of 50,000)Data updated Feb 10, 2026

Key Facts

Publishes
N/A
Episodes
34
Founded
N/A
Category
Education
Number of listeners
Private
Hidden on public pages

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Public snapshot
Audience: Under 4K / month
Canonical: https://podpitch.com/podcasts/tomayto-tomahto
Reply rate: Under 2%

Latest Episodes

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Data Science and Machine Translation w/ John DeNero

Wed Jan 21 2026

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We've been told time and time again that we need to understand data in context: it's an ethical imperative. Not every language gets an LLM; not every population fully understands a technology that's deployed in their community with or without everyone's consent; and certainly we're told that we will make better, safer conclusions with our data if we understand the context. John DeNero looks at things differently: instead of an ethical imperative for understanding data in context, John talks about a structural one. For example, accurately translating language necessitates understanding the context. It's almost as if he read a bunch of French critical theory, thought about deconstruction, and realized that a structural imperative has an ethical valence as well—and vice versa. It's not a paradox, it's deconstruction. This interview covers John's work as a professor of data science and computer science, his experience as a senior research scientist at Google Translate, thoughts on AI and language, and keeping up with the slang of today's youth. John DeNero is the Faculty Director of Data Science Undergraduate Studies (DSUS) and Associate Teaching Professor in the UC Berkeley EECS department. He is the co-founder and Chief Scientist at lilt. John's website Google Scholar A Class-Based Agreement Model for Generating Accurately Inflected Translations This episode is dedicated to MukhammadAziz Umurzokov and Ella Cook, the two Brown University students who passed away on December 13th, 2025.

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We've been told time and time again that we need to understand data in context: it's an ethical imperative. Not every language gets an LLM; not every population fully understands a technology that's deployed in their community with or without everyone's consent; and certainly we're told that we will make better, safer conclusions with our data if we understand the context. John DeNero looks at things differently: instead of an ethical imperative for understanding data in context, John talks about a structural one. For example, accurately translating language necessitates understanding the context. It's almost as if he read a bunch of French critical theory, thought about deconstruction, and realized that a structural imperative has an ethical valence as well—and vice versa. It's not a paradox, it's deconstruction. This interview covers John's work as a professor of data science and computer science, his experience as a senior research scientist at Google Translate, thoughts on AI and language, and keeping up with the slang of today's youth. John DeNero is the Faculty Director of Data Science Undergraduate Studies (DSUS) and Associate Teaching Professor in the UC Berkeley EECS department. He is the co-founder and Chief Scientist at lilt. John's website Google Scholar A Class-Based Agreement Model for Generating Accurately Inflected Translations This episode is dedicated to MukhammadAziz Umurzokov and Ella Cook, the two Brown University students who passed away on December 13th, 2025.

Key Metrics

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Pitches sent
8
From PodPitch users
Rank
#37287
Top 74.6% by pitch volume (Rank #37287 of 50,000)
Average rating
5.0
Ratings count may be unavailable
Reviews
2
Written reviews (when available)
Publish cadence
N/A
Episode count
34
Data updated
Feb 10, 2026
Social followers
36

Public Snapshot

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Country
United States
Language
English
Language (ISO)
Release cadence
N/A
Latest episode date
Wed Jan 21 2026

Audience & Outreach (Public)

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Audience range
Under 4K / month
Public band
Reply rate band
Under 2%
Public band
Response time band
Private
Hidden on public pages
Replies received
Private
Hidden on public pages

Public ranges are rounded for privacy. Unlock the full report for exact values.

Presence & Signals

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Social followers
36
Contact available
Yes
Masked on public pages
Sponsors detected
Private
Hidden on public pages
Guest format
Private
Hidden on public pages

Social links

No public profiles listed.

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Monthly listeners49,360
Reply rate18.2%
Avg response4.1 days
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Frequently Asked Questions About Tomayto Tomahto

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What is Tomayto Tomahto about?

I say tomayto, but you say tomahto. Why? What cognitive, economic, racial, or social factors led you to say tomahto and I tomayto? How did you acquire the ability to produce and perceive coherent sentences? These are some questions that linguists attempt to answer scientifically. Led by Talia Sherman, a Brown University undergrad, this podcast explores language: what it is, how it works (both cognitively and in practice), and its relationship to politics, history, pedagogy, AI, neuroscience, psychology, anthropology, computation, and more! Questions? Email tomaytotomahtopodcast@gmail.com

How often does Tomayto Tomahto publish new episodes?

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