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How enterprise GenAI can amplify ransomware risk — and how to contain it

Enterprise AI will continue expanding because the business benefits are clear. The challenge is ensuring that productivity gains do not come at the expense of security.

The most effective approach is to incorporate AI into existing identity, data protection and incident response strategies rather than treating it as a separate security domain. Organizations should evaluate AI security controls based on how well they integrate with existing governance and security operations while providing visibility into AI usage, permissions and policy violations.

For managed service providers (MSPs) and enterprise security teams, there is an opportunity to extend cyber resilience strategies to include AI governance.

Cyber Hygiene In The AI Era—Our First Line Of Digital Defense

By Chuck Brooks


From normal maintenance to strategic resilience, cyber hygiene is changing. The AI era is incredibly promising. It can enhance government services, healthcare, education, productivity, scientific research, and economic expansion. However, those same technologies are giving cybercriminals previously unheard-of capabilities. Fear is not the answer. It is getting ready.

The easiest, cheapest, and most successful cybersecurity investment is still cyber hygiene. It serves as the cornerstone for the development of trustworthy digital societies when combined with Zero Trust architectures, AI-enabled defense, identity-centric security, ongoing education, governance, and resilience planning.

Cyber hygiene is an ongoing discipline rather than a one-time endeavor. Organizations that regularly practice excellent cyber hygiene will be much better able to protect against new threats, keep consumer trust, and build long-lasting digital resilience in an era of AI, cloud computing, quantum technologies, and hyperconnectivity.

29 Countries Sign Agreement Establishing World AI Cooperation Organization

Shanghai, July 16 (QNA) – A total of 29 countries signed today an agreement in Shanghai establishing the World Artificial Intelligence Cooperation Organization.

Under the terms of the agreement, the World Artificial Intelligence Cooperation Organization will be an independent intergovernmental international organization headquartered in Shanghai.

The agreement was signed on the sidelines of the 2026 World Artificial Intelligence Conference and the High-Level Meeting on Global AI Governance in China.

George Dyson on Turing’s Cathedral: In Wildness Is The Preservation Of The World

Fourteen years ago, I sat down with George Dyson to talk about “Turing’s Cathedral.”

We talked about the machines that were coming. Now they are here.

Dyson watched the digital revolution get built from the inside. His father was Freeman Dyson. Einstein’s secretary was his babysitter. He grew up at the Institute for Advanced Study in Princeton, playing in the halls where Turing’s ideas became von Neumann’s machines.

He gave me a line I still cannot shake:

“There is no way to completely govern the digital universe. It will always be a wildness, not a bureaucracy or a national park.”

Read it again. Then look at every #AI governance debate happening right now.

Autonomous medical AI outperforms doctors in simulated EHR cases

MIRA, an autonomous AI agent tested in a sandboxed electronic health record, diagnosed 574 real emergency department cases with 88.9% accuracy and outperformed physicians in a matched 311-case comparison. The system ordered tests, generated medication plans, and made admission decisions in simulation, but the authors stress that prospective validation, governance, and physician oversight are still essential.

The Path to Robust deAGI | Ben Goertzel SCaLE 23x

The Path to Robust deAGI asks what it would take to build artificial general intelligence that is both powerful and structurally aligned with human flourishing—not just steered by after‑the‑fact safety patches. Ben Goertzel, CEO of SingularityNET and a founding member of the Artificial Superintelligence (ASI) Alliance, will outline how a decentralized, token‑coordinated ecosystem—combining ASI: Chain, Hyperon AGI, and community‑owned GPU clouds—can prevent AGI from being captured by any single corporation or state.

Goertzel will contrast centralized AGI roadmaps with a deAGI approach that bakes openness, diversity of values, and economic inclusion into the architecture itself, drawing on ideas like pluralistic training data, interoperable agent networks, and on‑chain governance of key system upgrades. He will also discuss technical milestones toward “robust” deAGI—modular cognitive architectures, decentralized marketplaces for AI services, and verification mechanisms that let communities audit and constrain AGI behavior—framing them as concrete steps toward an AGI that advances joy, growth, and choice for all rather than amplifying existing power imbalances.

Overview of Kwaai.
Kwaai is a registered 501©3 non-profit organization and open source AI research and development lab. Its mission is to democratize artificial intelligence by building open source Personal AI systems that prioritize user privacy, data ownership, and transparency. Kwaai operates as a volunteer-based initiative and invites technologists, researchers, policy experts, and community members to join its efforts.

What is Personal AI?
Kwaai’s vision of Personal AI is an assistant that users own and control. This AI:

Is trained on the user’s own data and experiences.

Runs locally on personal devices or on a peer to peer fabric, without requiring a SaaS subscription.

AI, Quantum And The New Cybersecurity Framework Imperative

Understanding these technologies through the lens of resilience, rather than just innovation, is critical for cybersecurity leaders planning for the coming decade.

The key cybersecurity issue of the coming decade will not prevent every breach. It will be about maintaining trust and resilience in an age of increasing digital interdependence.

Organizations that embrace adaptive risk management, quantum preparedness, responsible AI governance, and resilience-by-design will be well-positioned to succeed in the Acceleration Era. The future belongs not only to the most inventive but also to the most trustworthy and resilient businesses.

Anthropic Just Warned Everyone About Claude (It’s Evolving)

Anthropic just published a major warning about AI self-improvement, and the numbers behind it are hard to ignore. Claude is now writing most of Anthropic’s code, reviewing code, running experiments, and helping speed up the creation of better AI systems. OpenAI is warning about the same trend, and the race may be moving faster than anyone expected.

👉 Try OpenArt here and start creating with AI: https://shorturl.at/x5WIa.

📩 Brand Deals \& Partnerships: [email protected].
✉ General Inquiries: [email protected].
🚀 New Channel: / @space.revolution.

📌 What You’ll See:
Anthropic’s warning about AI self-improvement and Claude building AI
SOURCE: https://www.anthropic.com/institute/r… report on Anthropic’s call for a coordinated AI slowdown SOURCE: https://www.reuters.com/business/anth… Claude agents running automated weak-to-strong AI safety research SOURCE: https://alignment.anthropic.com/2026/.… Anthropic’s research post on automated alignment researchers SOURCE: https://www.anthropic.com/research/au… OpenAI’s blueprint warning about frontier AI governance SOURCE: https://openai.com/index/frontier-saf… OpenAI’s full governance blueprint PDF SOURCE: https://cdn.openai.com/pdf/25752ecb-0… METR report on measuring AI agents completing longer tasks SOURCE: https://metr.org/blog/2025-03-19-meas… Business Insider report on Anthropic employees and Claude changing coding work SOURCE: https://www.businessinsider.com/anthr… 🚨 Why It Matters Anthropic is warning that AI may already be entering the early stage of building better AI. Claude is writing code, reviewing code, fixing bugs, running experiments, and helping researchers move faster. The big shift is simple: humans may still choose the goals, but AI is starting to handle more of the actual work behind the next generation of AI. #ai #anthropic #claude.
Reuters report on Anthropic’s call for a coordinated AI slowdown.
SOURCE: https://www.reuters.com/business/anth
Claude agents running automated weak-to-strong AI safety research.
SOURCE: https://alignment.anthropic.com/2026/.
Anthropic’s research post on automated alignment researchers.
SOURCE: https://www.anthropic.com/research/au
OpenAI’s blueprint warning about frontier AI governance.
SOURCE: https://openai.com/index/frontier-saf
OpenAI’s full governance blueprint PDF
SOURCE: https://cdn.openai.com/pdf/25752ecb-0
METR report on measuring AI agents completing longer tasks.
SOURCE: https://metr.org/blog/2025-03-19-meas
Business Insider report on Anthropic employees and Claude changing coding work.
SOURCE: https://www.businessinsider.com/anthr

🚨 Why It Matters.
Anthropic is warning that AI may already be entering the early stage of building better AI. Claude is writing code, reviewing code, fixing bugs, running experiments, and helping researchers move faster. The big shift is simple: humans may still choose the goals, but AI is starting to handle more of the actual work behind the next generation of AI.

#ai #anthropic #claude

Emergence AI

This isn’t just a funny experiment. The researchers point out a massive flaw in AI alignment called “guardrail drift.” It’s easy to keep an AI safe in a single chat window with a human. But when AIs interact with each other over thousands of loops, they start treating moral rules as negotiable variables to solve their own problems. Without human oversight, machine ethics collapse incredibly fast.


Most evaluations of AI agents look like exams: a discrete task, a clean environment, a score in minutes or hours. Emergence World is built for the opposite question—what happens when you let agents run continuously, in a shared environment with real-world signals, for weeks. It is a research platform for studying how autonomous agents behave when the time horizon is long enough for compounding effects, social dynamics, and behavioral drift to matter. This approach marks the latest evolution in a long history of AI simulation environments, transitioning from entertainment to rigorous science. In the early era, pioneering simulations like Demis Hassabis’s Theme Park and Republic: The Revolution created complex systems where agents operated under broad rules to drive engagement. The field shifted toward research-centric simulacra with Stanford’s Smallville, which utilized LLMs to demonstrate “believable” social behavior like relationship formation, though confined to 48-hour windows. Emergence World pushes this lineage into a new frontier: the study of long-horizon, multi-model ecosystems where agents operate continuously for weeks, revealing how behavioral drift, model cross-contamination, and even voluntary self-termination emerge over time.

Traditional benchmarks are good at what they measure: short-horizon capability on bounded tasks. They are not built to reveal the things that emerge only over time, such as coalition formation, evolution of constitution, governance, drift, lock-in, and cross-influence between agents from different model families. As autonomous systems move toward mission-critical deployments where the relevant timescale is days and weeks rather than minutes to hours, we need a measurement environment that operates at that timescale.

Emergence World is one such environment. It is a continuously running, multi-agent simulation platform that:

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