Tom Abbs

Tom Abbs (born 1972) is an American multi-instrumentalist and filmmaker. He works primarily in the fields of jazz, free jazz, and free improvisation, and plays double bass, tuba, cello, violin, didgeridoo, and wooden flute, often playing several of these instruments simultaneously.[1]

Tom Abbs
Born1972 (age 47–48)
Seattle, Washington
GenresAvant-garde jazz
Occupation(s)Musician
Instrumentsdouble bass, tuba, cello, violin, didgeridoo, flute

Originally from Washington state, he has lived New York City since 1991, and is based in Brooklyn, New York. He attended The New School's Jazz and Contemporary Music program, studying with Reggie Workman, Buster Williams, Joe Chambers, Brian Smith, Junior Mance, Arnie Lawrence, Chico Hamilton, and Arthur Taylor. He began his full-time performing career in 1992.

He has worked with Lawrence "Butch" Morris, Charles Gayle, Daniel Carter, Cooper-Moore, Steve Swell, Roy Campbell, Jr., Sabir Mateen, Ori Kaplan, Jemeel Moondoc, Assif Tsahar, Borah Bergman, Billy Bang, Andrew Lamb, and Warren Smith. Abbs is currently a member of the collective groups Triptych Myth, Yuganaut, and Transmitting (with Napoleon Maddox and Jane LeCroy). He also leads the band Frequency Response and tours with his solo multimedia project Multifarious. He has collaborated with the painter M. P. Landis.[2]

Abbs is also the founder of the arts coalition Jump Arts, which has presented performances and workshops throughout New York City from 1997 to 2002; since that time the organization has dedicated itself to artist services through fiscal sponsorship and media services.

He was the general manager of ESP-Disk from 2007 to 2010 and founded Northern Spy Records in the fall of 2010 which he co-owns with Adam Downey.

Discography

With Roscoe Mitchell

With Tryptych Myth

gollark: > There is burgeoning interest in designing AI-basedsystems to assist humans in designing computing systems,including tools that automatically generate computer code.The most notable of these comes in the form of the first self-described ‘AI pair programmer’, GitHub Copilot, a languagemodel trained over open-source GitHub code. However, codeoften contains bugs—and so, given the vast quantity of unvettedcode that Copilot has processed, it is certain that the languagemodel will have learned from exploitable, buggy code. Thisraises concerns on the security of Copilot’s code contributions.In this work, we systematically investigate the prevalence andconditions that can cause GitHub Copilot to recommend insecurecode. To perform this analysis we prompt Copilot to generatecode in scenarios relevant to high-risk CWEs (e.g. those fromMITRE’s “Top 25” list). We explore Copilot’s performance onthree distinct code generation axes—examining how it performsgiven diversity of weaknesses, diversity of prompts, and diversityof domains. In total, we produce 89 different scenarios forCopilot to complete, producing 1,692 programs. Of these, wefound approximately 40 % to be vulnerable.Index Terms—Cybersecurity, AI, code generation, CWE
gollark: https://arxiv.org/pdf/2108.09293.pdf
gollark: This is probably below basically everywhere's minimum wage.
gollark: (in general)
gollark: <@!319753218592866315> Your thoughts?

References
  1. All About Jazz
  2. Mplandis.com Archived 2009-02-18 at the Wayback Machine


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