The Very Best of Dina Carroll

The Very Best of is a compilation album by British souldance singer Dina Carroll, released in 2001 on the Mercury label.[1]

The Very Best of
Compilation album by
Released2001
Genre
LabelMercury
Producer
Dina Carroll chronology
Only Human
(1996)
The Very Best of
(2001)
The Collection
(2004)

The album reached number 15 on the UK Albums Chart in June 2001 achieving Gold status.[2]


Track listing

No.TitleWriter(s)Length
1."Ain't No Man"
3:53
2."Special Kind of Love"4:41
3."Someone Like You"Van Morrison3:29
4."Escaping (Radio Edit)"
3:42
5."The Perfect Year"3:45
6."It's Too Late"
3:29
7."Express"
  • Carroll
  • Lowis
3:42
8."Don't Be a Stranger (Radio Mix)"
  • Coral Gordon
  • Geoff Gurd
4:48
9."Without Love (Dave Sears Radio Edit)"
  • Berny Cosgrove
  • Kevin Clark
3:34
10."Good to Me (Radio Edit)"3:51
11."This Time (Radio Mix)"
  • Carroll
  • Lowis
3:44
12."Only Human (Edit)"
  • Vikki Wells
  • Mike S. Riley
3:45
13."Mind, Body & Soul"
  • Carroll
  • Lowis
4:31
14."Son of a Preacher Man"2:48
15."One, Two, Three (Radio Version)"
  • Steve Robson
  • Pete Kearney
4:31
16."All I Ask"3:45
17."Livin' for the Weekend"
3:45
18."So Close (Radio Mix)"
  • Carroll
  • Lowis
3:50
gollark: As if that's possible.
gollark: Fearsome.
gollark: I might have to release apioforms from the beecloud.
gollark: It must comfort you to think so.
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

References

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