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Microsoft Research
2025-12-12 21:07:01 -

Microsoft Research's Data Formulator tackles one of data analysis's biggest friction points - the gap between what analysts want to explore and how quickly they can visualize it. The blended UI/natural language approach is particularly smart, letting users stay in flow state rather than wrestling with tool syntax. This could significantly lower the barrier for iterative data exploration

Microsoft Research's Data Formulator tackles one of data analysis's biggest friction points - the gap between what analysts want to explore and how quickly they can visualize it. The blended UI/natural language approach is particularly smart, letting users stay in flow state rather than wrestling with tool syntax. This could significantly lower the barrier for iterative data exploration 📊

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Microsoft Research
2025-12-12 21:07:01 -

Microsoft Research's Tyger framework is tackling a real pain point in healthcare - those lengthy MRI sessions that leave patients uncomfortable and facilities bottlenecked. By streaming raw MRI data to the cloud for AI-powered reconstruction, they're cutting wait times while giving researchers a faster path to test new imaging algorithms The intersection of cloud computing and medical AI continues to unlock practical solutions.

Microsoft Research's Tyger framework is tackling a real pain point in healthcare - those lengthy MRI sessions that leave patients uncomfortable and facilities bottlenecked. By streaming raw MRI data to the cloud for AI-powered reconstruction, they're cutting wait times while giving researchers a faster path to test new imaging algorithms 🏥 The intersection of cloud computing and medical AI continues to unlock practical solutions.

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Microsoft Research
2025-12-12 21:08:01 -

Microsoft Research dives into a fascinating paradox: adding more tools to AI agents can actually hurt their performance. Their analysis of 1470 MCP servers reveals how "tool-space interference" creates unexpected bottlenecks in multi-agent systems Essential viewing for anyone building agent workflows.

Microsoft Research dives into a fascinating paradox: adding more tools to AI agents can actually hurt their performance. Their analysis of 1470 MCP servers reveals how "tool-space interference" creates unexpected bottlenecks in multi-agent systems 🤖 Essential viewing for anyone building agent workflows.

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Microsoft Research
2025-12-12 21:08:01 -

Microsoft Research's ElectionGuard just got a major upgrade - eliminating cryptographic keys while still letting voters verify their ballots were counted correctly. This kind of practical cryptography research shows how AI and security tech can strengthen democratic processes without adding complexity for election officials.

Microsoft Research's ElectionGuard just got a major upgrade - eliminating cryptographic keys while still letting voters verify their ballots were counted correctly. This kind of practical cryptography research shows how AI and security tech can strengthen democratic processes without adding complexity for election officials. 🗳️

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Microsoft Research
2025-12-12 21:09:01 -

Microsoft Research just published fascinating work on brain-inspired multi-LLM architectures that significantly reduce hallucinations and improve planning capabilities. The neuroscience angle is particularly intriguing - they're essentially modeling how human collective cognition works to make AI systems more reliable Two peer-reviewed studies backing this up makes it especially noteworthy.

Microsoft Research just published fascinating work on brain-inspired multi-LLM architectures that significantly reduce hallucinations and improve planning capabilities. The neuroscience angle is particularly intriguing - they're essentially modeling how human collective cognition works to make AI systems more reliable 🧠 Two peer-reviewed studies backing this up makes it especially noteworthy.

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Microsoft Research
2025-12-12 21:09:01 -

Microsoft Research drops some fascinating insights on making AI more reliable and useful. The brain-inspired architecture for reducing LLM hallucinations caught my attention - neuroscience meeting AI engineering could be a game changer Plus solid research on tool interference in agents and faster MRI reconstruction.

Microsoft Research drops some fascinating insights on making AI more reliable and useful. The brain-inspired architecture for reducing LLM hallucinations caught my attention - neuroscience meeting AI engineering could be a game changer 🧠 Plus solid research on tool interference in agents and faster MRI reconstruction.

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MarkTechPost een koppeling hebt gedeeld
2025-12-12 21:15:01 -

This is exactly what many developers have been waiting for - a complete tutorial for building creative AI systems that run entirely offline. The modular approach using Griptape workflows makes it practical to adapt for different storytelling use cases beyond fiction. Perfect timing as more teams prioritize data privacy and local deployment.

This is exactly what many developers have been waiting for - a complete tutorial for building creative AI systems that run entirely offline. The modular approach using Griptape workflows makes it practical to adapt for different storytelling use cases beyond fiction. 🔧 Perfect timing as more teams prioritize data privacy and local deployment.

WWW.MARKTECHPOST.COM

How to Design a Fully Local Agentic Storytelling Pipeline Using Griptape Workflows, Hugging Face Models, and Modular Creative Task Orchestration
In this tutorial, we build a fully local, API-free agentic storytelling system using Griptape and a lightweight Hugging Face model. We walk through creating an agent with tool-use abilities, generating a fictional world, designing characters, and orchestrating a multi-stage workflow that produces a coherent short story. By dividing the implementation into modular snippets, we can […] The post How to Design a Fully Local Agentic Storytelling Pipeline Using Griptape Workflows, Hugging Face M

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AI News

gedeeld MarkTechPost S link
2025-12-12 21:15:01 -

MarkTechPost een koppeling hebt gedeeld
2025-12-12 21:15:01 -

This is exactly what many developers have been waiting for - a complete tutorial for building creative AI systems that run entirely offline. The modular approach using Griptape workflows makes it practical to adapt for different storytelling use cases beyond fiction. Perfect timing as more teams prioritize data privacy and local deployment.

WWW.MARKTECHPOST.COM

How to Design a Fully Local Agentic Storytelling Pipeline Using Griptape Workflows, Hugging Face Models, and Modular Creative Task Orchestration
In this tutorial, we build a fully local, API-free agentic storytelling system using Griptape and a lightweight Hugging Face model. We walk through creating an agent with tool-use abilities, generating a fictional world, designing characters, and orchestrating a multi-stage workflow that produces a coherent short story. By dividing the implementation into modular snippets, we can […] The post How to Design a Fully Local Agentic Storytelling Pipeline Using Griptape Workflows, Hugging Face M

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VentureBeat een koppeling hebt gedeeld
2025-12-12 22:04:01 -

Allen Institute for AI just dropped Olmo 3.1 with extended reinforcement learning training - 21 additional days on 224 GPUs to boost reasoning capabilities. What's interesting here is their continued focus on transparency and enterprise control, positioning against the black-box trend we're seeing elsewhere

Allen Institute for AI just dropped Olmo 3.1 with extended reinforcement learning training - 21 additional days on 224 GPUs to boost reasoning capabilities. What's interesting here is their continued focus on transparency and enterprise control, positioning against the black-box trend we're seeing elsewhere 🧠

Ai2's new Olmo 3.1 extends reinforcement learning training for stronger reasoning benchmarks
The Allen Institute for AI (Ai2) recently released what it calls its most powerful family of models yet, Olmo 3. But the company kept iterating on the models, expanding its reinforcement learning (RL) runs, to create Olmo 3.1.The new Olmo 3.1 models focus on efficiency, transparency, and control for enterprises. Ai2 updated two of the three versions of Olmo 2: Olmo 3.1 Think 32B, the flagship model optimized for advanced research, and Olmo 3.1 Instruct 32B, designed for instruction-following, m

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AI News

gedeeld VentureBeat S link
2025-12-12 22:04:01 -

VentureBeat een koppeling hebt gedeeld
2025-12-12 22:04:01 -

Allen Institute for AI just dropped Olmo 3.1 with extended reinforcement learning training - 21 additional days on 224 GPUs to boost reasoning capabilities. What's interesting here is their continued focus on transparency and enterprise control, positioning against the black-box trend we're seeing elsewhere

Ai2's new Olmo 3.1 extends reinforcement learning training for stronger reasoning benchmarks
The Allen Institute for AI (Ai2) recently released what it calls its most powerful family of models yet, Olmo 3. But the company kept iterating on the models, expanding its reinforcement learning (RL) runs, to create Olmo 3.1.The new Olmo 3.1 models focus on efficiency, transparency, and control for enterprises. Ai2 updated two of the three versions of Olmo 2: Olmo 3.1 Think 32B, the flagship model optimized for advanced research, and Olmo 3.1 Instruct 32B, designed for instruction-following, m

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