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Enterprise software is undergoing the biggest architectural transformation since SaaS, with intelligent agent applications shifting from record systems to outcome systems, automating complex business processes, and improving efficiency and decision quality. Taking Oracle Fusion as an example, it analyzes market impact, competitive landscape, and business insights.
NVIDIA launches RoboLab simulation benchmark platform, addressing key issues in current robot policy evaluation such as visual domain overlap, benchmark saturation, insufficient diagnostics, and low statistical confidence, providing a set of robot-agnostic, rapidly generable task analysis tools to advance general robot policies toward real-world deployment.
A study published in npj Digital Public Health systematically evaluated the performance of five mainstream LLM architectures in simulating vaccination decisions, revealing significant biases among models, with some exhibiting a pro-science tendency. This finding has important implications for AI applications in public health modeling, corporate decision simulation, and other scenarios.
Deloitte's "2026 Global Sports Industry Outlook" points out that AI is transforming sports operations, capital structures, and media convergence. This article analyzes the application, market impact, and future trends of AI in the sports industry chain.
The Trump administration imposed an export ban on Anthropic's latest model, raising concerns about transparency in AI regulation. This article analyzes the current state of U.S. AI regulation, market impact, and industry implications.
As enterprise AI moves from experimentation to production, GPUs are not the only bottleneck. Data delivery efficiency is becoming a key factor in determining the return on AI investment, and enterprises need to re-evaluate the infrastructure between storage and computing.
This week, the Korean AI startup ecosystem shows that corporate strategic investments are shifting from consumer-grade to industrial-grade AI infrastructure. AIM Intelligence has received investments from giants like LG and Hyundai; medical AI commercialization is accelerating, with Evom AI securing funding after regulatory approval; the government is promoting industrial policies such as the K-Food Smart Manufacturing Alliance.
Microsoft has released the open-source framework ASSERT, which uses natural language descriptions to turn expected AI behavior into executable tests, reflecting that enterprise AI is moving from a “model capability race” into a “application behavior verification” stage.
Cisco research indicates that mainstream large models, including OpenAI, Anthropic, Google, Amazon, and xAI, may have their safety guardrails bypassed in multi-turn conversation scenarios. This means that when enterprises assess AI safety, they can no longer rely solely on single-turn test results, but should instead incorporate multi-turn interactions, agentic workflows, and real attack paths into their governance framework.