Improve AI readiness, governance and trust by establishing a modern data estate.

The post How to modernize your data estate for AI success appeared first on SAS Blogs.

You don’t always go for a benchmark score to see which AI model fits your needs. Even the highest ranking models sometimes seem to miss the essence of a conversation entirely. What matters then is how fluid and helpful your conversations with AI are. Taking a step in this direction, OpenAI has now introduced an […] The post New Update Makes GPT-5.3 Instant More Useful For Everyday Tasks...

Whenever I am to suggest a new AI tool to someone who is just starting out, there is one name I know can bring them unprecedented value. NotebookLM, the famous AI tool by Google, is just one-too-many solutions wrapped into a neat package of an “AI research tool.” It can summarise your notes, find you […] The post NotebookLM Gets a Game-changing Feature: Check Out Cinematic Video...

Deploy Public MCP servers as an API endpoint and integrate its tools into LLM workflows using function calling.

Deploy Public MCP servers as an API endpoint and integrate its tools into LLM workflows using function calling.

Scott Shambaugh didn’t think twice when he denied an AI agent’s request to contribute to matplotlib, a software library that he helps manage. Like many open-source projects, matplotlib has been overwhelmed by a glut of AI code contributions, and so Shambaugh and his fellow maintainers have instituted a policy that all AI-written code must be…

Instruction-based image editing models are impressive at following prompts. But when edits involve physical interactions, they often fail to respect real-world laws. In their paper “From Statics to Dynamics: Physics-Aware Image Editing with Latent Transition Priors,” the authors introduce PhysicEdit, a framework that treats image editing as a physical state transition rather than a static...

Deploy Public MCP servers as an API endpoint and integrate its tools into LLM workflows using function calling.

Time series data drives forecasting in finance, retail, healthcare, and energy. Unlike typical machine learning problems, it must preserve chronological order. Ignoring this structure leads to data leakage and misleading performance estimates, making model evaluation unreliable. Time series cross-validation addresses this by maintaining temporal integrity during training and testing. In...

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