venturebeat
Microsoft's new AI training method eliminates bloated system prompts without sacrificing model performance

In building LLM applications, enterprises often have to create very long system prompts to adjust the model’s behavior for their applications. These prompts contain company knowledge, preferences, and application-specific instructions. At enterprise scale, these contexts can push inference latency past acceptable thresholds and drive per-query costs up significantly. On-Policy Context Distillation (OPCD), a new training framework proposed by researchers at Microsoft, helps bake the knowledge and preferences of applications directly into a model. OPCD uses the model’s own responses during training, which avoids some of the pitfalls of other training techniques. This improves the abilities of models for bespoke applications while preserving their general capabilities. Why long system p [...]

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venturebeat
Microsoft AI chief says company was “set free” from OpenAI to pursue superintelligence

For three years, Microsoft's artificial intelligence story has been inseparable from OpenAI. The partnership — cemented by a cumulative investment exceeding $13 billion — gave Microsoft early [...]

Match Score: 128.12

venturebeat
Baseten takes on hyperscalers with new AI training platform that lets you own your model weights

Baseten, the AI infrastructure company recently valued at $2.15 billion, is making its most significant product pivot yet: a full-scale push into model training that could reshape how enterprises wean [...]

Match Score: 125.89

venturebeat
Microsoft says ungoverned AI agents could become corporate 'double agents.' Its fix costs $99 a month.

Microsoft today announced the general availability of Agent 365 and Microsoft 365 Enterprise 7, two products designed to bring security and governance to the rapidly growing population of AI agents op [...]

Match Score: 111.14

venturebeat
Microsoft built Phi-4-reasoning-vision-15B to know when to think — and when thinking is a waste of time

Microsoft on Tuesday released Phi-4-reasoning-vision-15B, a compact open-weight multimodal AI model that the company says matches or exceeds the performance of systems many times its size — while co [...]

Match Score: 106.39

venturebeat
How to build custom reasoning agents with a fraction of the compute

Training AI reasoning models demands resources that most enterprise teams do not have. Engineering teams are often forced to choose between distilling knowledge from large, expensive models or relying [...]

Match Score: 100.14

venturebeat
Microsoft launches 3 new AI models in direct shot at OpenAI and Google

Microsoft on Wednesday launched three new foundational AI models it built entirely in-house — a state-of-the-art speech transcription system, a voice generation engine, and an upgraded image creator [...]

Match Score: 97.11

venturebeat
Microsoft takes Agent 365 out of preview as shadow AI becomes an enterprise threat

Microsoft last week took Agent 365, its management platform for AI agents, out of preview and into general availability — a move that signals the software giant believes the governance challenge aro [...]

Match Score: 90.01

venturebeat
Microsoft launches 'Hey Copilot' voice assistant and autonomous agents for all Windows 11 PCs

Microsoft is fundamentally reimagining how people interact with their computers, announcing Thursday a sweeping transformation of Windows 11 that brings voice-activated AI assistants, autonomous softw [...]

Match Score: 89.82

venturebeat
Phi-4 proves that a 'data-first' SFT methodology is the new differentiator

AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology [...]

Match Score: 89.68