Recommender Systems Origin Story

Recommender Systems Origin Story

Where did recommender systems come from, and how do we know when they're actually working? In part one of Data Skeptic's three-part Recommender Systems finale, Kyle traces the field from collaborative filtering and the Netflix Prize to matrix factorization and modern approaches, while exploring why accuracy alone can't capture what makes a recommendation useful, surprising, or meaningful.

Tämä jakso on lisätty Podme-palveluun avoimen RSS-syötteen kautta eikä se ole Podmen omaa tuotantoa. Siksi jakso saattaa sisältää mainontaa.

Jaksot(611)

Gestures Around the Ear

Gestures Around the Ear

The next evolution of wearable technology may not require new screens or controllers, but new ways to interact with the devices we already wear. Shimon explores how gesture-sensing earbuds could trans...

18 Loka 30min

Implicit Interactions

Implicit Interactions

How do we design robots and autonomous vehicles that understand the unwritten rules of human behavior? Kyle speaks with Cornell Tech professor Wendy Ju about implicit interaction, "Wizard of Oz" proto...

5 Loka 44min

The Lived Informatics Model

The Lived Informatics Model

The data we collect about ourselves can tell us a lot—but only if the technology collecting it actually fits into our lives. Daniel Epstein explores personal informatics, from fitness trackers and foo...

25 Syys 34min

Recommender Systems Today and Tomorrow

Recommender Systems Today and Tomorrow

In the final episode of our Recommender Systems season, we explore the growing questions of trust, manipulation, privacy, fairness, sustainability, and user control. From fake reviews and shilling att...

9 Syys 22min

Recommender Systems Optimization Goals

Recommender Systems Optimization Goals

In part two of the Data Skeptic Recommender Systems season finale, Kyle asks a deceptively difficult question: what should recommender systems actually optimize for? Drawing on conversations from acro...

1 Syys 31min

Social Choice for Fair Recommendations

Social Choice for Fair Recommendations

Recommender systems influence nearly every aspect of our digital lives—but what does it mean for those systems to be fair? Robin Burke joins Data Skeptic to discuss the history of recommender systems,...

27 Heinä 42min

News Recommendations

News Recommendations

News recommendation algorithms influence far more than what stories we click—they can shape our understanding of the world. In this episode, Kyle Polich speaks with Andreea Iana about responsible AI, ...

2 Heinä 46min

Suosittua kategoriassa Tiede

utelias-mieli
rss-mita-tulisi-tietaa
tiedekulma-podcast
rss-hereilla
rss-kasvatuspsykologiaa-kaikille
rss-poliisin-mieli
rss-bios-podcast
rss-totuuden-liepeilla
mielipaivakirja
rss-duodecim-lehti
rss-tiedetta-vai-tarinaa
rss-ja-ihminen-loi-alyn-aalto-yliopiston-tekoalypodcast
docemilia
rss-ranskaa-raakana
koodikahvit