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4 GoKawiil briefs on this topic

CSA Survey: Most DLP Tools Detect Data Loss After It Already Occurred

A Cloud Security Alliance survey conducted with Jazz found that 73% of organizations experienced at least one confirmed data loss incident in the past two years, and only 16% said their DLP tools blocked the most serious incident before data left the organization. The survey also found that while nearly half of security teams rank GenAI tools as their top exfiltration risk, fewer than a third can produce routine reports showing sensitive data sent to such tools, and only 22% strictly block GenAI-related data transfers.

AI Model Mimics Jazz Pianists' Styles Using Cross-Attention Technique

Researchers fine-tuned a transformer-based AI called Aria on performances by twelve jazz pianists, incorporating a cross-attention layer to embed individual styles. The model's ability to generate stylistically accurate continuations was confirmed through classification tests, with conditioned outputs correctly attributed to the intended pianist 70% of the time. Listeners can compare different pianist styles from a single prompt, demonstrating the model's nuanced style replication.

Blog post rebuilds John Coltrane's hand-drawn tone circle as an interactive widget

A music theory blog post reconstructs a circular diagram that John Coltrane once sketched and gave to Yusef Lateef, who later referenced it in his own book on scales. The diagram overlays chromatic scales onto the circle of fifths/fourths, and the post turns it into an interactive tool letting users rotate keys and highlight harmonic shapes, including patterns connected to Coltrane's composition 'Giant Steps'.

Spotify, YouTube, Amazon Music profiles of dead jazz greats hijacked by AI-generated tracks

Streaming profiles for deceased jazz musicians including Sonny Criss, Jean Carne, Red Nichols and Jimmie Noone have been flooded with new, AI-generated songs falsely credited to them. The tracks, uploaded under a publisher called 'Ami bacuk' and a fabricated artist name, feature generic anime-style cover art and cannot be traced to existing recordings or identified by music-ID tools.