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Red Hat AI 3.5 tackles the GPU queue that can stall AI pilots26m ago CNN Just Ran One of the Worst AI Puff Pieces We’ve Ever Seen in Our Lives About That “AI Actor” Tilly Northwood40m ago How Credit Genie keeps codebase docs fresh with OpenWiki41m ago Closing The Gap Between AI Ambition And Data Reality43m ago Universal Music is launching an AI music platform with ElevenLabs48m ago Top Pentagon Official Rejects Anthropic Researcher’s AI Warning2h ago Arlequin AI raises €28M to build novel AI models that learn complex relationships at scale52m ago SpaceX sues to block release of tax-break records for its Texas Terafab project52m ago Salesforce closes Fin and eyes $2bn Listen Labs, Business Insider reports54m ago Google brings Gemini for desktop app to Windows54m ago AI’s Hidden Apprenticeship Tax (And How Firms Can Avoid It)58m ago Abacus.AI Releases Three Open-Weight Smaug Models for Agentic Workloads1h ago Clay raises $115m at a $7.1bn valuation, more than double its 2025 price1h ago Before AI Agents Take Action, Enterprises Need A New Data Rule Book1h ago

Machine Learning Dev2 min reading time

PROOF-Gen: From Optimized Data to Better Distillation

Apple Research BlogPublished 16 days ago

Researchers introduced PROOF-Gen, a method that recovers successful task trajectories from failures by optimizing prompts per scenario, improving tool-calling model performance significantly on τ 2-bench and in deployed pipelines.

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