The solution isn't bigger models or more GPUs. It's creating that document of record layer that transforms dark data into something AI can actually trust.
DATA
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Using IoT for Predictive Maintenance Solutions
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How to Use #IoT for Predictive Maintenance
by @antgrasso #InternetOfThings #DigitalTransformation #Innovation #Technology #Tech -
AI Accuracy Fails With Unverified Data and Poor Data Quality
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Most organizations point AI at decades of unverified PDFs and disconnected engineering records, then wonder why accuracy drops through the floor.
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AI Projects Need Governed Accuracy Layers for Success
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AI projects fail because of missing governed accuracy layers.
— Lucian Fogoros (@fogoros) 15 avril 2026
Raw unstructured content needs transformation into documents of record before AI can reason against them with certainty. Partner content with Adlib. #adlib_iiot pic.twitter.com/q66wW9tJUOAI projects fail because of missing governed accuracy layers.
Raw unstructured content needs transformation into documents of record before AI can reason against them with certainty. Partner content with Adlib. #adlib_iiot -
Databricks AI Gateway Extends Unity Catalog Governance to Agentic AI
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AI Gateway in Databricks now extends Unity Catalog governance to agentic AI.
— Databricks (@databricks) 15 avril 2026
As agents call LLMs, pull data through MCP servers, and invoke external APIs, every step touches sensitive data and audit requirements. With the latest updates to AI Gateway, you can now bring all of… pic.twitter.com/WICCgaXxiEAI Gateway in Databricks now extends Unity Catalog governance to agentic AI. As agents call LLMs, pull data through MCP servers, and invoke external APIs, every step touches sensitive data and audit requirements. With the latest updates to AI Gateway, you can now bring all of
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Company Security Message Raises Trust Concerns Among Users
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I'm certain this isn't the message they intended to present, but this comes across to me as a company saying "we no longer trust in our own ability to keep your data secure" https://t.co/WtQRxvaAxr
— Simon Willison (@simonw) 15 avril 2026I'm certain this isn't the message they intended to present, but this comes across to me as a company saying "we no longer trust in our own ability to keep your data secure"
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Small Models Adaptation Challenges Beyond Fine-Tuning
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Small models are cheap to run, but expensive to adapt. The hard part is not only fine-tuning. It is the surrounding loop that involves collecting data, diagnosing failures, building evals, avoiding regressions, choosing curricula, and deciding when an update is safe. This new
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Three Keys for Companies to Master AI in 2026-2028
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My takeaway is simple: The next 2 to 3 years will reward companies that do 3 things well: → use AI internally, so leadership understands it firsthand
→ build with a clear path from pilot to industrialization
→ take control of their own models, data, and evaluation strategy -
Netflix and Prime Video recommendation systems use machine learning
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Oui et surtout attend qu'il découvre que les sytèmes de recommandations de Prime vidéo ou Netflix doivent s'entrainer sur les titres, descriptions, sous titres, images du film pour recommander des films aux personnes. On a même pas besoin d'aller jusqu'à l'IA génératif.
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Jane Street scales AI training on massive noisy datasets
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Not just using AI. @JaneStreetGroup is training massive models on noisy data, refining continuously, and deploying at scale. @CoreWeave
, powered by NVIDIA Vera Rubin, is the engine behind that ambition.