HackerTube.dev

Dan Tepfer: NPR Music Tiny Desk Concert

NPR Music · 133.5K views · 2019-09-04 · 18:27

Open on YouTube ↗

If playback is restricted in your region, try opening the original video. Use Mark watched to add it to your marked videos.

Overview

A Tiny Desk concert in which pianist Dan Tepfer plays with a Disklavier player piano driven by a program he wrote that responds to his playing. He performs four pieces from his Natural Machines project.

On Hacker News

HN points to it as an example of algorithmic, reactive live music that blends programming with jazz performance.

Recommended by 2 HN people across 2 months · HN mentions 2020–2023

Topics

Search by tags

What people said

voicedYoda · 2023-01 · Recommendation

I also enjoy Dan Tepfer's visualizations of audio and audio decay. This was his tiny desk concert: [VIDEO]

Read the original HN comment ↗
soulofmischief · 2020-07 · Recommendation

Are you familiar with Magenta? [0] It's not real-time, but definitely an important area of research. Also check out Dan Tepfer [1] who is doing amazing work with an algorithmic approach to reactive live performances, with great call and response tactics. I myself am slowly prototyping a fully artificial AI band which can be orchestrated using very high-level musical ideas and a big helping of intelligent randomization and algorithms based on music theory. I've been prototyping in Andrew Sorensen's Extempore [2] and have laid much of the groundwork like melody/harmony/rhythm generation as well as basic modulation of these elements to create longer musical structures which utilize motifs in multiple ways Currently it is a matter of shedding pre-computed tables of "nice" sounding progressions or purely random progressions, and creating a more fundamental approach which can derive the appropriate progressions from the given user parameters. I am also expanding the program's ability to generate aesthetically pleasing and unique singular motifs which drive these algorithmic compositions. I have a band leader / conductor module which provides cues and other synchronized data, which even without advanced motif generation and modulation still allows for things not currently possible in any non-code musical production software such as global dyamics, timing changes, progression sharing, (eventually) directing impromptu solos, etc. Reach out via email if you'd like to discuss more! [0]

Read the original HN comment ↗
dantepfer · 2021-11 · Reference

Hi everyone, Dan Tepfer here, co-creator of FarPlay. As a skeptic myself, I appreciate the skeptical tone of this thread. And I'd like to address a few points made here about FarPlay and low-latency audio. First, a little about me: I've been coding for most of my life (see [VIDEO] for my NPR Tiny Desk Concert of my improvised algorithmic music project Natural Machines) but I'm first and foremost a musician. I make my living playing concerts around the world as a pianist. During the pandemic, I used JackTrip to perform remote livestream concerts with some of the greatest musicians in jazz: Christian McBride, Cécile McLorin Salvant, Ben Wendel, Gilad Hekselman, Fred Hersch, Antonio Sanchez, Melissa Aldana, Miguel Zenon, Linda May Han Oh and others. This is just to say that music, and particularly rhythm, is very important to me, and that I care about low-latency audio as an active practitioner. Someone in this thread wrote that for rhythmic (groove) music, latencies of 3ms are noticeable, and latencies higher than 6ms are prohibitive. This isn't the case. Sound travels in air at about 1ft per ms, so a latency of 3ms is equivalent to playing with someone 3ft away from you, which is obviously unnoticeable. 6ms is equivalent to playing with someone 6ft away, which is also unnoticeable. James Brown grooved his ass off with his band spread out over a relatively wide area on stage, long before in-ear monitors, which confirms what the research says: even for advanced professional musi

Read the original HN comment ↗

Sources

Video by NPR Music, played through YouTube.

Data and selection notes

HN summaries and labels may contain AI errors. HN dates refer to discussions, not video publication.

HN Library: HackerTube export (2026-10-31) and open-index/hacker-news. Upstream summaries and classifications may contain AI errors.

Views, duration and playback status refresh separately from the published catalog. When an update fails, existing data remains visible.

Selection checks
  • SaaS & AI candidates: Topic keywords do not match
  • Editor-approved picks: Editorial review is required

Rule matches identify candidates. They do not guarantee video quality or financial results.

About the library and its sources