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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 project53m 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

Dev AI Research31 min reading time

Presentation: Architecting the Data Layer for AI Agents: from Transactional Systems to MCP and Semantic Models

InfoQ (AI, ML & Data)Published 12 days ago

Fabiane Nardon from TOTVS discusses challenges in adapting enterprise data systems for AI agents, emphasizing the need to prepare data optimized for AI's probabilistic reasoning rather than traditional deterministic transactional systems. She highlights the shift from deterministic to non-deterministic computational models to enhance enterprise AI applications.

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