Discover the latest MAI models, designed for real-world intelligence Create stunning, de...
模型更新Hacker News 热门（buzzing.cc 中文翻译）
今日 AI 情报摘要
Discover the latest MAI models, designed for real-world intelligence Create stunning, design-ready
images from any text or photo prompt, with best-in-class Arena ELO scores at a lower price. Delivers expressive, low-latency speech that holds up across long generations.
中文正文 · AI 翻译
发现最新的 MAI 模型，专为现实世界的智能设计
从任意文本或照片提示创建惊艳、设计就绪的图像，以更低的价格获得一流的 Arena ELO 分数。
提供富有表现力、低延迟的语音，即使在长时间生成中也能保持表现。
为最重要的复杂问题而构建，具备竞争力的推理能力，并在中等成本下获得顶级 SWE-Bench Pro 成绩。
帮助你的工程团队更快地编写更高质量的代码，内置轻量级、具有代理能力的模型于 GitHub Copilot 和 VS Code 中。
微软能够端到端地看到这个循环：通过微软安全响应中心（Microsoft Security Response Center, https://www.microsoft.com/en-us/msrc）掌握漏洞；跨身份、终端、云、数据、浏览器和应用程序的攻击与防御；每天超过100万亿条安全信号；以及来自160万客户的运营洞察。因为我们可以将行动与结果关联起来；什么是可利用的，什么被遏制，什么被阻止，以及什么真正有效；我们拥有的不仅仅是数据。
我们的 MAI 强化学习循环为打造持续改进并成为专家级网络防御者的网络模型奠定了基础。这将是我们未来多年对客户的承诺。
Discover the latest MAI models, designed for real-world intelligence
Create stunning, design-ready images from any text or photo prompt, with best-in-class Arena ELO scores at a lower price.
Delivers expressive, low-latency speech that holds up across long generations.
Built for the complex problems that matter most, with competitive reasoning and top SWE-Bench Pro results at a mid-weight price.
Helps your engineering team write better code faster, with a lightweight, agentic model built into GitHub Copilot and VS Code.
Turn noisy audio into precise, domain-specific transcripts, with leading FLEURS and Artificial Analysis accuracy scores.
The latest breakthroughs and updates from within our team
Today we’re announcing MAI-Cyber-1-Flash inside of MDASH, our multi-agent vulnerability identification and remediation harness. Together they deliver world-class performance at 50% of the cost of leading models.
Progress in AI has been startling and so has the new generation of cyber threats it’s unleashing. Attackers now wield increasingly powerful capabilities, probing an ever-growing mountain of code for just a single weakness that lets them in.
As the cost of finding a flaw collapses, the old model of security, where you scan occasionally and patch eventually, is now obsolete. If we’re to unlock the true benefits of AI, we must first build outstanding cyber models that help all of us harden the software the world runs on.
That’s the motivation behind MAI-Cyber-1-Flash, which has been built to find challenging vulnerabilities in complex codebases. It’s been deeply integrated into MDASH, honed by the best cybersecurity experts in the industry and hardened across the largest security estate on the planet.
This combined expertise delivers exceptional security protection, beating Mythos, Gemini and GPT on CyberGym, the gold standard benchmark for evaluating how systems reason over large codebases to find real vulnerabilities in the code.
Picking the right model for the task
Security is an always-on mission, and given the enormous volume of inbound attacks, token cost is now the real constraint for defenders. MAI-Cyber-1-Flash was designed to efficiently handle up to 90% of all tasks, enabling MDASH to use the larger and most costly models in our fleet (in this case GPT-5.4) for the 10% of exceptionally hard tasks that truly need them.
The result is that the unified system of MDASH with MAI-Cyber-1-Flash delivers 96% on CyberGym (+12 pt above Mythos) .
This combination delivers a 50% cost saving when compared against our best offering in MDASH today (GPT 5.4 + 5.4 mini + 5.3 codex). That’s the power of a well-tuned, multi-model system with access to uniquely rich historical training data. It ensures you always have the best model at the best price for every task.
In this new environment, being able to go from identifying a new vulnerability to addressing it in real-time is critical. And while AI remediation of software vulnerabilities is now a key security workflow, there are many jobs to be done by Security practitioners themselves.
That’s why today we’re also launching Perception：http://aka.ms/agenticsecurityblog, our agentic security systems, that provides teams of agents for a variety of security workflows in MDASH, to continuously monitor, patch, and close new threat vectors. Perception will also soon use MAI-Cyber-1-Flash for many more security workflows, beyond the software vulnerability work.
Three things matter today: Model. Data. Harness.
We have jointly optimized our world-class models, our unmatched historic data, and our expert-tuned harness to ensure that our customers have a uniquely powerful security offering.
Model. MAI-Cyber-1-Flash is a compact, code-heavy security model derived from the MAI-Thinking-1 lineage, which was built from scratch, in-house, on the highest quality data. Details in our technical report：https://microsoft.ai/pdf/mai-thinking-1.pdf.
Data. Our deepest advantage. Decades of building world-class security systems now give us trillions of daily signals across identity, endpoint, cloud, and network, and an unmatched record of real exploits and remediations. No one can manufacture this history.
Harness. MDASH：https://www.microsoft.com/en-us/security/blog/2026/05/12/defense-at-ai-speed-microsofts-new-multi-model-agentic-security-system-tops-leading-industry-benchmark/?msockid=07e1b320223d63fa1e34a47d23db623b, our multi-agent vulnerability identification and remediation harness, is tuned by the best security experts in the industry, who have created 100+ agents using multiple leading models to find, validate, and remediate vulnerabilities. Agentic code scanning is a critical function in the Security Operating Center and feeds Project Perception, our new agentic security system.
Because MAI-Cyber-1-Flash is Microsoft’s first cyber model, we built trust into every layer of the system, from model training to customer deployment. The model was developed with a security-first calibration, rigorously evaluated by Microsoft’s AI Red Team, tested through automated and expert-led adversarial exercises, and independently assessed by a third party.
Trust extends beyond the model itself. Through MDASH, customers get enterprise-grade controls including Role-Based Controls, tenant isolation, encryption, auditability, and sandboxed execution environments with no internet access. The result is a cyber model that delivers powerful capabilities to defenders while maintaining the governance, security, and control enterprises expect from Microsoft.
Cybersecurity is not just a data-rich domain; it is a live reinforcement learning loop. Every day, defenders investigate threats, triage alerts, hunt adversaries, remediate vulnerabilities, deploy protections, and learn from the outcome.
Microsoft sees that loop end to end: vulnerabilities through Microsoft Security Response Center：https://www.microsoft.com/en-us/msrc; attacks and defenses across identity, endpoint, cloud, data, browser, and applications; more than 100 trillion security signals every day ; and operational insight from 1.6 million customers. Because we can connect actions to outcomes; what was exploitable, what was contained, what was blocked, and what actually worked; we have more than data.
Our MAI reinforcement learning loop gives us the foundation to build cyber models that improve continuously and become expert cyber defenders. That’ll remain our commitment to our customers for years to come.
We’re a lean, talent-dense team of explorers, researchers, and full-stack engineers. We move fast, sweat the details, and operate at frontier scale with a roadmap to build the world’s most powerful AI models. Most importantly, we’re united by the belief that doing this right is the only way to do it at all. If our mission resonates with you, we’d love to talk.
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