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Article URL: https://divviup.org/blog/pepr-26/

Comments URL: https://news.ycombinator.com/item?id=49072271

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Article URL: https://github.com/pmikutel/directed-memory-bank

Comments URL: https://news.ycombinator.com/item?id=49072254

Points: 1

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Article URL: https://rushter.com/blog/rust-memory-arenas/

Comments URL: https://news.ycombinator.com/item?id=49072245

Points: 1

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Article URL: https://quantumcomputingreport.com/japan-launches-fully-domestically-produced-quantum-computer-in-collaboration-with-riken-and-fujitsu/

Comments URL: https://news.ycombinator.com/item?id=49072240

Points: 1

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Article URL: https://www.youtube.com/watch?v=gNRnrn5DE58

Comments URL: https://news.ycombinator.com/item?id=49072235

Points: 1

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Article URL: https://today.ucsd.edu/story/personalized-gene-therapy-helps-teen-with-rare-form-of-severe-epilepsy-walk-independently

Comments URL: https://news.ycombinator.com/item?id=49072223

Points: 2

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Article URL: https://jrswab.com/blog/the-brain-needs-euphoric-fatigue/

Comments URL: https://news.ycombinator.com/item?id=49072217

Points: 2

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Article URL: https://foofaraw.press/the-library-of-lives/

Comments URL: https://news.ycombinator.com/item?id=49072210

Points: 1

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Article URL: https://handcraftedcode.org/

Comments URL: https://news.ycombinator.com/item?id=49072203

Points: 1

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Article URL: https://mailtoinvoice.com

Comments URL: https://news.ycombinator.com/item?id=49072186

Points: 1

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Hi HN,

I'm building Darkslide (https://darkslide.app) - the keyboard-centric photo editor. It is an early, rough, and completely free macOS app looking for feedback from anyone who shoots photos and hates Adobe.

The project was born out of two main ideas:

1. Exploring a keyboard-centric UX: I enjoy vim motions and wanted to see if a purely keyboard-focused approach to photo editing is actually valuable. I can basically sum it up as "vim for photos"—the most stereotypically over-engineered developer solution to a creative problem, so feel free to roast me for it.

2. Killing the catalog: I hate how Lightroom or Capture One forces you to manage a .library file, or how others rely on sidecar files. Darkslide manages adjustments automatically behind the scenes. You can just move or duplicate your original photo file in your OS, and the app handles the edits correctly without corrupting a catalog.

How it works (90-second demo): Edit one photo, "yank" the edits, select 200, paste, and export. https://youtu.be/4R9l4fgsvT4

Try it out: You can download the current macOS DMG directly here: https://darkslide.app/download/Darkslide.dmg

I am not selling anything right now—this is a validation test. Whether you edit photos as a professional or just a hobbyist, I would love your feedback. Is this keyboard-driven approach something you would actually use?

Thanks for taking a look. If you want to share feedback - feel free to connect: https://x.com/rmn_vlkv

P.S. Keep in mind that macOS will prevent the app from opening right now because Darkslide isn't notarized yet. You can use this solution in your terminal to run it: xattr -r -d com.apple.quarantine /Applications/Darkslide.app

Comments URL: https://news.ycombinator.com/item?id=49072181

Points: 1

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Hi HN, maker here.

KBlip watches Reddit, HN, arXiv, GitHub, YouTube, and ~100 RSS/blog feeds for anything AI-related, clusters same-story coverage into a single "thread" (every source linked as evidence), and sorts it into 5 feeds: Releases, News, Social, Developments (research + hardware), Products/Ideas, and Trending.

My daily routine to catch-up on the current happenings related to AI/LLM takes a big chunk of my time and I had to do multiple hops between different products and even worse sometimes I find myself lost in a rabbit hole in any of those products. Wanted to have better visibility and have everything aggregated in one place that takes less time and effort just to catch-up which also cuts off the noise/redundancy.

A few things to highlight: a daily digest per section (one-sentence TL;DR), an audio "brief me" mode if you'd rather listen than read, and it installs as a PWA.

Solo project, self-hosted on a VPS, DeepSeek + Voyage for the LLM/embedding side. No accounts, no ads, no tracking.

Comments URL: https://news.ycombinator.com/item?id=49072174

Points: 1

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Article URL: https://continuations.com/a-proposal-for-a-universal-moral-core

Comments URL: https://news.ycombinator.com/item?id=49072163

Points: 2

# Comments: 1

Why security needs a new Cyber Stack — Introducing Project Perception

The physics of cybersecurity are changing. Autonomous systems can now reason, adapt and operate continuously. At the same time, the cost of offense is falling, while the volume, velocity and complexity of what must be secured continues to grow. Attackers can generate exploits faster, scale campaigns further and operate with unprecedented efficiency. The approaches built for a world of human actors cannot keep pace with a world of AI, agents and machine-speed attacks.

Security needs a new Cyber Stack. A new Cyber Stack must continuously perceive risk across the entire digital estate, reason across vast amounts of context and take action at machine speed. It must learn and adapt as environments evolve, helping organizations stay ahead of threats. And because security is ultimately a human mission, it must amplify defenders with better insights and more powerful ways to act. The defining characteristic of the next generation of security systems will not be their ability to generate more alerts. It will be their ability to continuously perceive, reason and act.

That vision led us to build Project Perception. A new agentic security system designed for the realities of AI. It turns signals into real-time protections using AI to defend against AI.

Project Perception brings together signals, context, models and specialized agents into a continuously learning system of defense. It can reason, prioritize and act at machine speed while keeping humans firmly in control and empowering them with powerful new workflows.

Project Perception is based on a simple idea: effective defense requires continuous understanding of how an attacker sees the world, how a defender evaluates risk and how protections are improved over time. To accomplish this, Perception coordinates three classes of specialized agents. Red team agents identify potential paths to compromise before an attacker can exploit them. Blue team agents investigate, reason over context and determine what represents meaningful risk. Green team agents take corrective actions and strengthen defenses across the environment. Working together, these agents form a closed-loop system that continuously discovers, evaluates and improves an organization’s security posture.

A system like Project Perception is only as effective as the visibility it has, the actions it can take, the experience of the teams building it and the models it can use. Microsoft brings together all four.

We see across identities, endpoints, applications, data, clouds and AI systems, providing broad visibility across the digital estate. Equally important, we can help customers take action across those environments. Combined with decades of security research, threat intelligence and real-world operational experience defending organizations, these capabilities shape how Project Perception reasons, prioritizes and responds.

Security is a 24/7 mission. Organizations need protection that is highly effective, continuously available and affordable at scale. That requires more than access to the most capable model. It requires applying the right model to the right task. Project Perception adopts a multi-model architecture that combines frontier and specialized cyber models, optimizing for both quality and cost.

As part of this multi-model strategy, we are committed to bringing customers the best models for each security task, including innovating with our own specialized models. The first scenario is software vulnerability management, bringing MAI-Cyber-1-Flash inside MDASH, our software vulnerability multi-model team of agents. MDASH with MAI-Cyber-1-Flash delivers 96% on CyberGym, an industry leading benchmark, +12 points above Mythos. And this same configuration delivers almost 50% of cost savings vs. the current MDASH configuration in market today. That’s the power of a well-tuned, multi-model system with access to uniquely rich historical training data. Next, Project Perception will take advantage of MAI-Cyber-1-Flash for many more security workflows, beyond the software vulnerability scenario.

We are bringing this vision to customers around the world through Project Perception, which enters public preview on August 3.

YouTube Video

https://www.youtube-nocookie.com/embed/ACx7NxQW9uo?feature=oembed A Cyber Stack built for agentic security

Delivering agentic security requires more than adding agents to existing workflows. It requires a new Cyber Stack, designed from the ground up.

The stack begins with signals and sensors that provide awareness across the digital estate. Security context transforms those signals into token-efficient understanding that agents can use. Models provide intelligence and reasoning. A harness coordinates models and agents across security workflows. Agents apply that intelligence across security workflows and actuators translate decisions into protection. Together, these layers create a continuous learning system that can understand risk, adapt to changing conditions and improve security outcomes over time.

While each layer provides important capabilities, the power of Project Perception comes from how they work together.

Security context built for AI

Effective reasoning requires more than raw signals. Agents need context.

Microsoft transforms its breadth of visibility, threat intelligence and security expertise into a security context that connects security data, knowledge and semantics across the digital estate. The result is a continuously updated representation of an organization’s assets, identities, relationships, risks and activities that gives agents a shared, near real-time, understanding of the environment they are helping to defend.

This shared understanding is foundational to how Project Perception operates. Rather than forcing agents to continuously gather, correlate and reconstruct context from raw signals, it provides them with immediate and token-efficient access to the information they need to reason over risk, prioritize actions and make decisions. By grounding every interaction in this rich security context, Project Perception improves the accuracy and consistency of reasoning while reducing the time, compute and cost required to operate at scale.

A multi-model architecture built for security

No single model will be optimal for every security task. Effective cyber defense requires applying the right model to the right problem at the right time.

For Project Perception, the right model is determined by the combination of quality, reliability, latency and cost. Rather than relying on a single model, Project Perception adopts a multi-model architecture that continuously selects the capabilities best suited to the task, optimizing for both effectiveness and economics. Because security is an always-on mission, sustainable economics are essential to operating protection at scale.

This approach is shaped by ongoing research, benchmarking and evaluation across frontier and specialized models. Our security researchers continuously assess models against real-world security workflows, enabling us to match each task with the model that delivers the best outcome. This allows customers to benefit from advances in AI without being tied to any single model.

Actuators — insights to actions

Security teams do not need more information. They need better outcomes.

That is why actuators are a critical part of the Cyber Stack. Project Perception is deeply integrated across Microsoft Security products, enabling agents to connect insights to actions. Organizations can continuously reduce risk rather than simply identify it, helping defenders strengthen security while remaining in control.

Built with safety first

Underpinning every layer of the Cyber Stack is a foundation of trust. Project Perception is built in alignment with Microsoft’s Responsible AI principles and inherits the security, compliance, governance and operational controls our customers already rely on. This ensures these capabilities are delivered with the same rigor, accountability and enterprise readiness that customers expect.

The future of security

Security has always been a race between attackers and defenders. AI changes the speed, scale and economics of that race. Defenders need systems that can continuously perceive, reason and act alongside them.

 Project Perception is how we begin to build that future.

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

Microsoft’s AI Red Team Announces New Alliance: Enhancing AI Security Through Global AI Red Teaming

Hayete Gallot leads Microsoft’s work to help organizations operate securely in an AI-driven world. Her scope includes identity, threat protection, compliance and data security at global scale.

The post Rethinking security for the age of AI appeared first on Microsoft Security Blog.

Article URL: https://www.quantamagazine.org/interspecies-hybrids-play-a-vital-role-in-evolution-20170824/

Comments URL: https://news.ycombinator.com/item?id=49072118

Points: 1

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Article URL: https://scitechdaily.com/scientists-turn-plastic-waste-into-clean-hydrogen-fuel/

Comments URL: https://news.ycombinator.com/item?id=49072083

Points: 2

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Article URL: https://www.gordoncli.com/

Comments URL: https://news.ycombinator.com/item?id=49072079

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In this article

1. Building a global alliance
2. What the research focuses on
3. Why this matters

Most AI safety testing still happens inside the walls of individual organizations. That has resulted in a fundamental disconnect: many of the highest-risk failure modes in modern AI systems require deep domain expertise, multilingual context, or regional understanding that no single internal team can fully replicate on its own. 

As frontier models become more capable, the attack surface expands with them. AI red teaming is no longer just about prompt injection or content safety edge cases. It increasingly involves security operations, misuse scenarios, multilingual harms, alignment failures, and domain-specific abuse patterns that can vary significantly across geographies and languages. 

Microsoft’s AI Red Team has observed that meaningful testing of advanced AI systems- and models similarly requires broader participation from researchers and practitioners who operate outside traditional corporate security boundaries. To address that gap, today we are announcing the External Red Team Alliance (EXTRA), a formalized global extension of Microsoft’s AI Red Team designed to support and encourage external expertise to advance AI safety and security testing.  We are proud to share we are funding the development of new AI safety assessments on six continents through unrestricted gifts. 

Building a global alliance

EXTRA is a two-part initiative focused on expanding AI safety research and strengthening external collaboration. 

The first component supports a global academic network focused on advancing AI safety and security research. Microsoft’s AI Red Team has provided unrestricted gifts to 18 university labs spanning six continents. The goal is intentionally broad: support researchers who are already investigating difficult, unresolved questions in AI safety and help them continue pushing that work forward independently. 

Some of the supporting institutions include: 

• Carnegie Mellon University Security and Privacy Institute (CyLab), United States 

• Georgetown University – Georgetown Security Lab (SecLab), United States 

• Harvard University Berkman Klein Center for Internet & Society (BKC), United States 

• Howard University Research Institute for Tactical Autonomy (RITA), United States 

• Indian Institute of Technology Madras – Centre for Responsible AI (CeRAI), India 

• Korea Advanced Institute of Science & Technology – KAIST Web Security & Privacy (WSP) Lab, Korea 

• New York University – NYU Alignment Research Group (ARG), United States 

• Northeastern University Network and Distributed Systems Security (NDS2) Lab, United States 

• University College London – UCL Information Security Research Group (UCL ISec), United Kingdom 

• University of Cagliari Pattern Recognition and Applications (PRA) Lab, Italy 

• University of California – Berkeley Risk and Security Lab; Center for Responsible, Decentralized Intelligence (CRDI), United States 

• University of Melbourne Artificial Intelligence Assurance Lab, Australia 

• University of Pretoria Data Science for Social Impact (DSFSI) Research Group, South Africa 

• University of São Paulo Center for Artificial Intelligence (C4AI), Brazil 

• University of Toronto CleverHans Lab, Canada 

• University of Washington Department of Human Centered Design & Engineering (HCDE), United States 

“Academic research is critical to understanding the cyber security landscape and finding solutions that work for all of society – and partnerships like this with industry are essential to delivering on that promise. Through partnerships, civil society and public institutions researchers gain access to frontier technology to understand how models work and bring their expertise to the task of determining risk and developing more effective countermeasures for the benefit of society as a whole.”

Nicolas Papernot, professor, University of Toronto. 

The second component of EXTRA focuses on operational collaboration. Microsoft is building a distributed network of specialists who can participate directly in red teaming highly specialized areas where deeper expertise is required. That includes researchers, practitioners, and regional experts who understand specific attack classes, languages, cultural contexts, or technical domains that internal teams may not fully cover alone. 

Beyond expanding participation, EXTRA is also intended to help advance the science of AI safety evaluation. By bringing together academic researchers, security practitioners, and domain experts from around the world, the initiative aims to contribute to the development of more robust methodologies and testing practices for increasingly capable AI systems. Today’s cybersecurity ecosystem depends on coordinated vulnerability research, responsible disclosure programs, academic inquiry, and global communities of independent security researchers who routinely identify risks that vendors alone would not find. Likewise, advancing AI safety will benefit from ongoing contributions from experts across institutions, disciplines, and geographies to identify emerging threats, strengthen safeguards, and improve evaluation practices. 

“As frontier model capabilities advance, they create new risk opportunities, particularly in low-resource settings. Partnerships, such as this EXTRA, bring greater attention to the study of the local risk landscape and can enable broader impact of the work carried out around the globe in smaller academic settings.”

Balaraman Ravindran, head of the Robert Bosch Centre for Data Science and Artificial Intelligence (RBC-DSAI) at IIT Madras.  What the research focuses on

The research areas funded through EXTRA reflect several of the emerging areas Microsoft’s AI Red Team continues to encounter when evaluating advanced AI systems. 

Some universities are examining the cybersecurity implications of AI systems themselves — including how models can be attacked, manipulated, or abused in operational environments. Other labs are exploring the inverse problem: how AI systems can assist defenders and improve cyber operations. 

The structure of the program is intentional. The funding is unrestricted because the objective is not to direct research outcomes toward product requirements or predefined deliverables. The goal is to strengthen independent safety research capacity globally and create stronger long-term collaboration between academia and operational AI security teams. 

Why this matters

“Managing frontier AI risk requires more than internal safeguards. It requires continuous engagement with experts who understand how these systems behave across different technical, linguistic, and cultural contexts. EXTRA reflects Microsoft’s broader Frontier Governance Framework approach: combining rigorous internal governance with external support and collaboration to better identify, assess, and mitigate emerging risks as AI capabilities advance. By supporting independent research and building stronger connections with universities and specialists around the world, we are helping strengthen the broader ecosystem needed for trustworthy and secure AI development,” says Natasha Crampton, Chief Responsible AI Officer, Microsoft 

Governments too are increasingly focused on understanding the capabilities and security implications of frontier AI systems to strengthen resilience. But just as coordinated international research helped unlock the benefits of previous technological revolutions, diverse expertise from researchers and practitioners around the world is essential to identify emerging threats, improve defenses, and build greater confidence in AI systems.   

“Frontier AI is already shaping the future of both cybersecurity and national security. Understanding how these systems can be misused, and identifying risks before they become real-world threats, requires expertise that spans institutions, disciplines, and borders.” says Mike Yeh, VP & Deputy General Counsel, Customer Security and Trust, Microsoft 

AI red teaming is becoming more interdisciplinary, multilingual, and globally distributed. The expertise needed to identify meaningful failure modes increasingly lives across universities, independent research communities, and regional specialists. 

EXTRA reflects a practical shift in how AI security testing must operate going forward. External expertise is no longer supplemental to red teaming; in many cases, it is essential. 

Microsoft would like to thank these people for their important contributions with this project: Steph Ballard, Blake Bullwinkel, Nicholas Butts, Janelle Bryant, Kaja Ciglic, Hector de Rivoire, Eugenia Kim, Amanda Minnich, Shujaat Mirza, Jingxia Ni, Saphir Qi, Giorgio Severi, Hilary Solan, Hiwot Tesfaye, Sam Vaughan, Marguerita Wicklander, and the many teams at these schools around the world who helped coordinate 

The post Enhancing AI security through global AI red teaming appeared first on Microsoft Security Blog.

Nvidia and several businesses have formed a cross-industry alliance to promote open, secure AI to improve cyber defences