Post Syndicated from Ryan Smith original https://www.servethehome.com/nxp-computex-keynote-2026-coverage/
The final keynote for Computex 2026 comes from NXP, where CEO Rafael Sotomayor is talking all about what it takes to deliver AI for edge devices and robotics in the real world, and how NXP is well-positioned to accomplish this
The post NXP Computex Keynote 2026 Coverage appeared first on ServeTheHome.
Post Syndicated from Ryan Smith original https://www.servethehome.com/scoping-out-rtx-spark-sff-mini-pcs-at-computex-2026/
While at Computex, we caught a look at some of the upcoming SFF mini-PCs based on NVIDIA’s RTX Spark SoC, including systems from ASUS, Dell, Lenovo, and MSI
The post Scoping Out RTX Spark SFF Mini-PCs at Computex 2026 appeared first on ServeTheHome.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2026/06/ai-worm.html
Researchers have prototyped an AI-powered internet worm.
The coolest thing about the prototype is that it carries its own LLM with it, and runs it on computers that have been broken into.
This is the closest to John Brunner’s original 1975 conception of a computer worm that I’ve seen.
Post Syndicated from Ming Lu original https://blog.cloudflare.com/ai-gateway-spend-limits/
There isn’t a CIO on the planet not worried about AI spend right now. CFOs are increasingly nervous, too.
For fear of falling behind, many companies have pushed their employees to use AI as aggressively as possible. The edict was clear: “Move fast, we’ll figure out the bill later.” And for the most part, it worked: AI has been genuinely transformational for the teams that leaned in.
But the costs are real: we’ve heard countless horror stories of huge bills and painful overages on token spend.
Today, we’re announcing spend controls in Cloudflare AI Gateway, and a closed beta for identity-driven budgets and routing using Cloudflare Access and your existing identity provider.
As we’ve spoken with hundreds of companies about their AI strategy, we’ve seen a common story: The company gives every engineer access to frontier models through a shared API key. Usage takes off. At the end of the month, finance pulls the invoice and nobody can explain where the money went. Was it the machine learning team training a new pipeline? Was it an intern running Claude Opus on email triage? Was it a runaway continuous integration job that burned through 50 million tokens in a weekend? Nobody knows, because the API key doesn’t tell you who used it.
Without guidelines, staff will generally reach for the biggest model available. And why wouldn’t they? If there’s no budget, no visibility, and no routing logic, the rational move is to use the most powerful model for everything. The problem is that most tasks don’t need a frontier model. A code review summary doesn’t need the same model as a complex architecture refactor. A log parser doesn’t need the same model as a customer-facing content generator. It should be easy to select the right tool for the job, rather than defaulting to the most powerful and expensive one. And it should be simple to see where the spend is going.
You can’t calculate ROI on your AI spend without visibility on what you’re spending, and you can’t protect that ROI without controls. Every other line item in a business has a budget and per-team attribution and AI spend should be no different.
AI Gateway sits between your applications and AI providers. Instead of calling OpenAI, Anthropic, Google, or any other provider directly, your requests route through AI Gateway first.
This immediately gives you several useful tools:
Unified billing to easily switch between different providers and models
Logging across all providers — every request, token count, and cost in one place
Response caching
Rate limiting
Content guardrails and the ability to block Personally Identifiable Information (PII) and secrets before they reach the model
However, AI Gateway didn’t have an easy way to answer who is spending what or how you might set limits on AI spend.
You could see aggregate usage across your account. But you couldn’t see that Jane from engineering burned through \$2,000 on Claude this month while the entire data science team only used \$400. You couldn’t set a budget that said “engineering gets \$5,000/month on frontier models, interns get \$200/month on Kimi K2.6.”
That changes today.
AI Gateway now supports spend limits as a core feature. These are true cost control measures in the form of budgets set in dollars, not tokens, that track cumulative spend across all requests, operating independently of traditional rate limiting.
You can scope limits to any combination of dimensions: model, provider, or admin-defined custom attributes like user, team, or application. Windows can be fixed (resets on the first of the month, Monday, or midnight) or rolling, and set to daily, weekly, or monthly.
AI Gateway calculates cost per request based on the model’s pricing, and tracks cumulative spend against your limit in real time. You can easily track your model spend on our analytics dashboard and filter by model, provider, or any custom attribute.
You have options for what happens when the budget limit is reached. AI Gateway will block further requests by default. Or you can set up rules through Dynamic Routes to route requests to a fallback model after you’ve hit a spend limit, so that a hard spending cap won’t kill your engineers’ workflow. We’re working to add the capability for you to also send alerts when a limit is reached.
Spend limits are available in open beta today for all AI Gateway users across all plans. Configure them in your gateway settings in the dashboard or via the API.
We’re tracking token costs inside Cloudflare already. Every Cloudflare employee uses AI tools daily, routing millions of requests and billions of tokens per month through AI Gateway. We faced the same question every company faces at this scale: who’s using what, and how do we budget for it?
We solved this by enabling AI Gateway to add identity to every request. When an employee authenticates via Cloudflare Access, we extract their identity from the JSON Web Token (JWT) and attach it as metadata on the AI Gateway request. This makes per-user token consumption, team-level usage breakdowns, and cost attribution across the organization all visible in one place.
In addition to spend limits, today we’re also announcing identity-driven budgets and policies as a closed beta.
Spend limits in AI Gateway let you set budgets by model, provider, or custom attributes. But your application has to pass that metadata, and AI Gateway trusts whatever it receives. For verified, automatic attribution, you need identity.
When combined with Cloudflare Access, AI Gateway can see who is making each request — not just which account, but which employee, which identity provider (IdP) group, which service, etc.
Here’s what that looks like in practice.
You can set per-user budgets, say \$500/month for individual contributors and \$2,000 for senior engineers. When a user hits their limit, requests can be downgraded to a cheaper model or blocked.
You can set per-team model policies. For instance, your ML team gets Claude Opus and GPT-4o. The brand design team can access generative image and video models. Interns use open-source models on Workers AI. These policies map directly to your existing IdP groups, the same identity provider groups you already manage.
For CI/CD pipelines and autonomous agents, Access service tokens allow you to give each agent a named identity. You can see that your code review bot used 5 million tokens this week while your documentation generator used 500,000. If one agent is running out of control, apply a budget policy without affecting any others.
Every AI Gateway log entry will include the authenticated identity: email, IdP group, service token name. Export these to your analytics platform, and you’ve got a cost-by-user-by-team breakdown without building anything custom.
Under the hood, you create a Cloudflare Access application for your AI Gateway endpoint and configure policies based on your IdP groups. When a developer or agent makes a request, they authenticate via OAuth, using the typical CLI device-code flow. AI Gateway validates the token and extracts the identity. You don’t need to write a custom Worker, parse JWTs yourself, or rely on honor-system metadata headers.
We recently wrote about how we built our internal AI engineering stack. This is what we are making available today — so you can use it, too, and you don’t have to build it yourself.
If you would like access to the closed beta, sign up here.
Setting a budget is necessary. But once you’ve got a budget, how do you make the most of it?
The reality is that not every request needs a frontier model: a summarization task can run on a smaller, cheaper model without meaningful quality loss, while a large-scale code refactor might require the bleeding edge. But without controls, people will almost always opt for the most advanced model.
A solution for that is coming next: We’re building intelligent, task-based routing in AI Gateway. For each request, we can analyze and automatically route it to the model that will give you the best result at the lowest cost. This is in active development, so follow our developer docs and changelog.
It’s free to get started with AI Gateway. Spend limits are available now for all users.
If you haven’t already, create a gateway and point your applications at it. From there, set up spend limits in the dashboard or via API. Start with a high limit in monitoring mode to understand your current usage patterns before you start enforcing.
If you want per-user attribution and team-based policies, sign up for the identity-driven budgets closed beta, and we’ll get you set up with the Access integration.
We want to hear how you’re managing AI costs today. Join the conversation on Cloudflare Community or reach out to discuss your broader AI security strategy.
Post Syndicated from Ryan Smith original https://www.servethehome.com/microsoft-to-join-the-ai-dev-mini-pc-market-with-upcoming-surface-rtx-spark-dev-box/
Microsoft is joining the AI dev box mini-PC market with the announcement of the Surface RTX Spark Dev Box. Due later this year, it will offer a pre-loaded dev environment, powered by NVIDIA’s new RTX Spark SoC
The post Microsoft to Join the AI Dev Mini-PC Market With Upcoming Surface RTX Spark Dev Box appeared first on ServeTheHome.
Post Syndicated from Evan You original https://blog.cloudflare.com/voidzero-joins-cloudflare/
VoidZero, the company behind Vite, Vitest, Rolldown, Oxc, and Vite+, is joining Cloudflare. As part of this change, all team members of VoidZero are joining Cloudflare, too.
Before saying anything else, we want to make the most important thing clear: Vite, Vitest, Rolldown, Oxc, and Vite+ will stay open source, vendor-agnostic, and community-driven. Nothing about that changes.
Cloudflare’s mission is to help build a better Internet. And a better Internet is an open Internet. Developers need choice, frameworks need a neutral foundation, and applications need to be portable. It is not reasonable to expect the entire web ecosystem to build around a single vendor. The most important tools and frameworks are portable by design.
Vite is one of the few foundational tools that the whole JavaScript ecosystem agrees on. It earned that position by being fast, excellent, portable, and vendor-neutral. One of the best ways Cloudflare can help build a better Internet is by investing in that foundational open source toolchain. A toolchain that makes the Internet better for everyone, not just people who use Cloudflare or choose to host with us.
Over the last few years we’ve invested heavily in making Cloudflare the best place to build and run websites, applications, and agents on our developer platform. But ultimately that choice will always be yours. Run your Vite application anywhere you want.
Today’s news gives Vite more resources to keep growing, while the things that make Vite what it is remain the same:
Vite remains MIT-licensed and open source.
Vite remains vendor-agnostic. Applications built with Vite run anywhere and will continue to do so.
Vite’s roadmap continues to be driven by the broader Vite team and community, and continues to be developed in the open.
Evan and the rest of the VoidZero team continue to lead Vite, Vitest, Rolldown, Oxc, and Vite+.
Cloudflare is committing engineering and resources to those projects, not redirecting them.
We made the same kind of commitment when Astro joined Cloudflare earlier this year. Astro is still open source, and still deploys anywhere. The team is still shipping the roadmap they were already shipping.
This commitment matters even more with Vite, because Vite is not one framework. Vite is the foundation underlying so many: Vue, SvelteKit, Nuxt, Astro, Solid, Qwik, Angular, React Router, TanStack Start. Even Next.js now has a Vite-based implementation in vinext. Vite has become a shared substrate for the JavaScript ecosystem.
Our number one goal is to maintain the trust that has earned Vite so much adoption. Not with our words here, but by proving it every day in how we support and develop these projects.
We also want to put our money where our mouth is when it comes to our support for open source and shared ecosystem foundations. As part of this announcement, Cloudflare is committing $1 million to a Vite ecosystem fund to support maintainers and contributors, administered by the Vite core team. Vite is bigger than VoidZero or Cloudflare, and the people who have helped build it should be part of what comes next.
The Vite and Cloudflare teams have been collaborating well before this announcement, starting in 2024 with the Vite Environment API. The Environment API lets Vite run server code in something other than Node.js during development. We worked closely with the Vite team on its design, and then built the Cloudflare Vite plugin on top of it.
When you run vite dev with the Cloudflare plugin, your server code runs inside workerd, the same open-source runtime that powers Workers in production. Durable Objects, D1, KV, R2, Workflows, Workers AI, Agents, Service Bindings, Workers RPC – all of it runs locally inside the same runtime model as production.
For a long time, the cost of developing on a non-Node runtime was that local dev felt like a worse version of production. The Environment API removed that cost without forcing anyone to adopt a Cloudflare-specific dev server. Any runtime that wants to plug into Vite can do the same thing. That kind of design – a generic mechanism in Vite with provider-specific implementations – has proven to work well and is one we want to keep building on.
We knew we were on to something when we saw adoption of the Cloudflare Vite plugin take off:
Vite’s adoption curve is one of the more remarkable things to watch in the ecosystem right now. As of this writing, Vite is at roughly 129M weekly downloads. The Cloudflare Vite plugin (@cloudflare/vite-plugin) is at almost 14M weekly downloads.
If you had told us a year ago that a Cloudflare Vite plugin would reach downloads equivalent to more than 10% of Vite itself, we wouldn’t have believed you. What happened? AI happened. More software is being created than ever before, and a lot of it starts with AI-generated code. Those applications need a default stack and a place to run. Agent-coded applications are choosing Vite, and increasingly they are choosing Vite running on Cloudflare.
Developers used to be the only users of dev servers, bundlers, linters, formatters, and CLIs. That is no longer true: agents are using them too, constantly. They scaffold projects, run dev servers, read errors, write tests, lint and format code, deploy previews, and iterate.
A lot of AI-generated applications already start as Vite apps, because Vite is fast, well understood, and broadly compatible with what agents have seen in their training data. Fast feedback loops have always been important. They become even more critical when writing software with agents:
Fast builds, because they iterate more than humans do.
Fast tests, because they re-run the suite constantly to verify their own work.
Fast linting and formatting, because those tools become guardrails.
Clear, structured errors, because the agent has to read and act on them.
Consistent CLIs, because small inconsistencies cause big detours.
The entire VoidZero toolchain is built for this kind of loop. Vitest, Rolldown, Oxc, Oxlint, and Oxfmt are each among the fastest tools in their respective categories, and they work well when they are run over and over by an agent. Vite+ brings those pieces together into one toolchain, with one CLI, one configuration model, and fewer moving parts. That makes the development loop easier for people to understand, and easier for agents to drive reliably.
We are dogfooding this ourselves. The Cloudflare dashboard is built on Vite. Oxlint is already saving days of engineering time in Cloudflare codebases. Flue, the agent harness framework from the Astro team, is also moving onto Vite as its foundation. Flue can run agents on Node.js, Cloudflare Workers, GitHub Actions, GitLab CI/CD, and more, and the Cloudflare target now uses the official Cloudflare Vite plugin and workerd integration. Vite is becoming the default application foundation inside Cloudflare too.
A few years ago, the job of a build tool was straightforward: take source files, produce a bundle, hand it off. That is not enough for modern applications, especially in a world where some of those applications are agents themselves.
A modern application is server-rendered routes, APIs, background jobs, queues, databases, object storage, real-time, auth, plus a growing list of agents and AI capabilities. The “build” is no longer the end of the story. It is the start of a deployment that has to understand all of those pieces.
That means Vite has to become more than a build tool. It needs to understand more of the application, while staying true to what made Vite work in the first place: speed, simplicity, and portability.
Void, a deployment platform designed for Vite, has been another testbed for these ideas. It helped explore what a modern application framework should own, what deployment should feel like, and how much of the full application lifecycle can be unified around one toolchain. We have learned a lot from that work.
Now the work is putting those lessons in the right place. Some belong in Vite itself as provider-agnostic primitives: first-class abstractions and hooks for backends, APIs, agents, and deployment that any provider can implement. Other lessons belong inside Cloudflare. Cloudflare will provide a first-class implementation of those hooks on Workers and the rest of our Developer Platform.
Even though some Vite maintainers are joining Cloudflare, changes to Vite itself will continue to go through the same open contribution process as any other Vite contribution. Features added to Vite itself should not be Cloudflare-specific. They will work anywhere Vite works.
The same principle shaped how we think about the future of Cloudflare’s own tooling. We are not moving Vite in the direction of Cloudflare. We are doing the opposite: moving Cloudflare’s application tooling onto Vite, so it is built on top of the same workflows developers already know.
We recently shipped a technical preview of cf, a new unified CLI for the whole Cloudflare platform. Vite is going to be the foundation of our CLI experience for applications. The end goal is one consistent CLI for all of Cloudflare, with the same ergonomics whether you are working on Workers, R2, D1, Agents, or anything else.
If we do this right, the Cloudflare CLI should feel like Vite, not like a separate thing bolted on next to Vite.
cf dev should be a superset of vite dev. Same speed, same hot module replacement, same plugin model, plus the Cloudflare runtime and bindings when you want them.
cf build should understand Vite projects natively, without an adapter dance.
cf deploy should make deploying a Vite app to Cloudflare simple.
If you are running Vite today, the path to Cloudflare will feel like swapping in a superset of the commands you already know. Same project shape. Same Vite workflows. The entire Cloudflare developer platform available when you want it.
In the short term, nothing changes for Vite users or the frameworks building on top of Vite:
Vite, Vitest, Rolldown, Oxc, and Vite+ keep shipping. The VoidZero team keeps contributing and leading them.
The Cloudflare Vite plugin keeps improving.
The Environment API and the broader story of “run your server code in the right runtime locally” keeps getting better, including for non-Cloudflare runtimes.
Longer term:
We start the work on moving the Cloudflare CLI toward an experience built directly on top of Vite.
Vite will get new, clean, provider-agnostic primitives for full-stack apps and agents that work for everyone on any platform.
Over time, we intend to open-source the Void platform, so others can learn from it and build their own platforms on top of Vite and Cloudflare.
We will do all of this in public and with the community. The same way Vite has always been built.
Vite, Vitest, Rolldown, Oxc, and Vite+ exist because a deep ecosystem of open source contributors put years of work into them. These projects are already foundational to how the web is built, and we are grateful to everyone who helped get them here. Thank you to everyone who has contributed code, reviews, issues, docs, plugins, integrations, and support along the way.
We are excited to welcome the VoidZero team to Cloudflare, and excited to put more resources behind these projects. Our job now is to help them grow, stay open, and power the JavaScript ecosystem for everyone.
Vite keeps being Vite. Cloudflare gets to help.
If you want to try Vite on Cloudflare today, run:
npm create vite@latest
npx wrangler deploy
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2026/06/hacking-metas-ai-chatbot.html
Hackers are convincing Meta’s AI support chatbot to let them take over other peoples’ accounts:
A video posted on X showed the step-by-step process to hack someone’s Instagram account. The hacker allegedly used a VPN to spoof the targets’ presumed location to avoid triggering Instagram’s automated account protections. Then, the hacker opened a chat with Meta AI Support Assistant and asked the bot to add a new email address to the target’s account. The chatbot can be seen sending a verification code to the email address provided by the hacker; the hacker then shares the verification code with the chatbot, which prompts the chatbot to show a button to “Reset Password.” The hacker enters a new password and takes over the victim’s account.
[…]
On Monday, Instagram spokesperson Andy Stone said in a reply to Wong’s post and others that the issue was now fixed. It’s unclear how many Instagram users had their accounts improperly accessed.
It’s not that easy. Probably this particular tactic is now blocked. But there are others, many others, and they cannot be blocked as a class. The real problem is that LLM chatbots are not trustworthy enough for this application.
Another news article.
Post Syndicated from Ryan Smith original https://www.servethehome.com/qualcomm-announces-dragonfly-brand-for-data-center-products/
Qualcomm this week has introduced its Dragonfly brand for its upcoming data center products. The brief teaser promised more details to come on June 24th, during Qualcomm’s 2026 Investor’s Day
The post Qualcomm Announces Dragonfly Brand for Data Center Products, More Info to Come June 24th appeared first on ServeTheHome.
Post Syndicated from Patrick Kennedy original https://www.servethehome.com/we-found-the-amd-ryzen-ai-halo-ai-developer-pc/
We found the AMD Ryzen AI Halo the company’s AI developer PC at Computex 2026 running a live demo at an AMD event
The post We Found the AMD Ryzen AI Halo AI Developer PC appeared first on ServeTheHome.
Post Syndicated from Jenni Hutchings original https://www.raspberrypi.org/blog/ai-education-resources-ai-awareness-day/
At the Raspberry Pi Foundation, we believe that alongside learning to code, a crucial part of computing education is building AI literacy skills. Amidst the rapid pace of development and the growing impact of AI tools, it is increasingly important for educators everywhere to feel equipped to address the topic of AI with their learners, to help young people understand their world, be responsible users of AI technologies, and prepare to become the future creators of these technologies.
We work at the leading edge of AI education, combining research and industry expertise with practical classroom experience to define what AI means for computing education, and how to best support teachers and learners to understand these technologies.
Whether you are a teacher, a Code Club mentor, or a parent, we have a wide range of free resources to help you teach your young people about AI, and learn more about it yourself.
We offer a variety of teaching materials to help you bring AI into your setting. You do not need to be a professional educator or have a background in computer science to use these resources, and we provide everything you need to guide your learners with confidence.
Experience AI is our free AI literacy programme, developed in collaboration with Google DeepMind. Through ready-to-use classroom resources, including lesson plans, presentations, and hands-on activities, the programme helps educators all over the world teach their learners about how AI works, as well as its wider social and ethical implications. You and your learners will investigate AI tools, explore real-world uses of AI, and engage with critical issues such as bias, fairness, and transparency, helping learners to understand AI and use it responsibly. The lessons currently available are designed for learners aged 11–14, and we are releasing resources for other age groups this year.
To help bring Experience AI to more educators and learners around the world, we work with a global network of partner organisations, who help us provide tailored and translated resources and offer localised, high-quality training and support for educators in their regions. Experience AI resources are currently available in 19 languages, and have already been downloaded in more than 180 countries. In recognition of its impact, in 2025 Experience AI was named a laureate of the UNESCO King Hamad Bin Isa Al-Khalifa Prize for the Use of ICT in Education.
“[Experience AI] has definitely changed my outlook on AI. I went from knowing nothing about it to understanding how it works, why it acts in certain ways, and how to actually create my own AI models and what data I would need for that. I would 100% recommend others who don’t know much about AI to try it out.” – Student, Arthur Mellows Village College, UK
If you are looking to introduce school-aged young people to AI with short, beginner-friendly coding and digital making projects, take a look at our collection of Code Club projects about AI and machine learning. These projects are a great way to spark curiosity and investigate how AI and machine learning works.
In the projects, learners get hands-on with a range of AI tools and platforms, and explore different applications of AI, such as image recognition, voice recognition, and (for learners aged 13 and over) generative AI. For example, in Doodle detector, learners use Machine Learning for Kids with Scratch to create a machine learning application that can identify what they have drawn.
The projects feature clear step-by-step instructions, and many include video tutorials, to help learners work at their own pace and in a style that suits them. We also provide mentor guidance to help you prepare.
For resources to support older learners to build their understanding of AI, head to Ada Computer Science. Ada Computer Science is our free online platform for computer science students and teachers, developed in partnership with the University of Cambridge. It provides comprehensive resources for learners aged 14–19 across the breadth of computer science, including detailed learning materials about AI and machine learning. The materials include helpful definitions, clear explanations, and carefully designed self-marking questions to support young people’s learning.
To help you build your knowledge around AI technologies and grow your confidence to teach your young people about this important topic, we offer a range of learning resources and professional development opportunities, all for free. They are open to everyone, so we invite you to dive into any that interest you.
For flexible, self-paced learning options, take a look at the following free online courses, which cover a range of topics within AI:
You might also be interested in Hello World, our free magazine and podcast for educators teaching computing and AI. Each magazine is packed with resources, discussions, news, and ideas, and you can subscribe to receive each issue as soon as it is released. The next issue, coming in July, will focus on critical thinking in the age of AI. You can download our previous issues to explore articles about a variety of topics within AI too. What’s more, you can continue your learning with the Hello World podcast, which accompanies the magazine and features discussions with educators and researchers from around the world. Visit the podcast page to discover previous episodes exploring vibe coding and programming education, AI education around the world, and more.
To learn about research-informed teaching strategies to help you as you explore AI with your learners, you can read these short Pedagogy Quick Reads:
For more insights from computing education research, you can join our monthly online research seminars. Our 2026 research seminar series focuses on teaching about AI across the curriculum, delving into research on teaching and learning about AI from disciplines beyond computer science, including the arts, sciences, and humanities. Our next seminar takes place on 16 June, and you can catch up on previous seminars from our current series here. You can also explore our archive of recordings from previous seminar series, with themes including teaching about AI and data science, teaching programming (with or without AI), and more.
All of these resources and learning opportunities are available to anyone interested in educating young people about AI, anywhere in the world. We hope they help you gain understanding, confidence, and inspiration to guide your young learners to engage with AI safely and responsibly, and to learn valuable skills that will help them navigate their world.
“Let the students explore, advance, and grow. And who knows — maybe one of our students will go on to become a mentor or leader in this field someday.” – Ana Judith Zavaleta, computer science teacher, Mexico, speaking about Experience AI
If you are in the UK, you can also use these resources to get involved with the first-ever AI Awareness Day, a new nationwide campaign designed to build AI literacy across UK schools, which is taking place on 4 June.
The post Support your young people with our AI literacy resources appeared first on Raspberry Pi Foundation.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2026/06/ai-used-to-decrypt-medieval-ciphers.html
Researchers are using machine learning algorithms to decrypt historical pencil-and-paper ciphers.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2026/06/the-intersection-of-encryption-and-ai.html
As part of their 20th Anniversary celebration, Dark Reading asked five cybersecurity industry leaders who wrote blogs or columns for them over the years to select their favorite piece and share their reflections on the topic today. This is my section.
Renowned technologist and author Bruce Schneier contributed a column on June 20, 2010, warning about cryptography’s inability to secure modern networks, a point he says he has been trying to argue since 2000.
“For a while now, I’ve pointed out that cryptography is singularly ill-suited to solve the major network security problems of today: denial-of-service attacks, website defacement, theft of credit card numbers, identity theft, viruses and worms, DNS attacks, network penetration, and so on.
“Recently, I talked to a former NSA employee at a conference. He told me that back in the 1990s, he had a copy of my book Applied Cryptography by his desk, as did many other cryptographers working at Ft. Meade. People were allowed to refer to it, but they were not allowed to cite it.
“The 1990s were an important decade for cryptography. This was before the internet went mass market, when cryptography was just emerging from a niche academic discipline to a mainstream engineering one. There wasn’t much that programmers could read. The NSA used my book for the same reason it became a bestseller: because it collected all the academic cryptography of the time in one place and made it understandable to people who weren’t mathematicians. They feared it for exactly the same reason.
“I’ve been thinking about that conversation as I revisit a 2010 essay I wrote for Dark Reading, ‘The Failure of Cryptography to Secure Modern Networks.’ Cryptography has inherent mathematical properties that greatly favor the defender. Adding a single bit to the length of a key adds only a slight amount of work for the defender but doubles the amount of work the attacker has to do. Doubling the key length doubles the amount of work the defender has to do (if that—I’m being approximate here) but increases the attacker’s workload exponentially. For many years, we have exploited that mathematical imbalance.
“Computer security is much more balanced. There’ll be a new attack, and a new defense, and a new attack, and a new defense. It’s an arms race between attacker and defender. And it’s a very fast arms race. New vulnerabilities are discovered all the time. The balance can tip from defender to attacker overnight, and back again the night after. Computer security defenses are inherently very fragile.
“That isn’t a new idea. I said much the same thing in the preface to my 2000 book, Secrets and Lies:
“‘Cryptography is a branch of mathematics. And like all mathematics, it involves numbers, equations, and logic. Security, real security that you or I might find useful in our lives, involves people: things people know, relationships between people, people and how they relate to machines. Digital security involves computers: complex, unstable, buggy computers.’
“I especially like how I phrased it in 2016: ‘Cryptography is harder than it looks, primarily because it looks like math. Both algorithms and protocols can be precisely defined and analyzed. This isn’t easy, and there’s a lot of insecure crypto out there, but we cryptographers have gotten pretty good at getting this part right. However, math has no agency; it can’t actually secure anything. For cryptography to work, it needs to be written in software, embedded in a larger software system, managed by an operating system, run on hardware, connected to a network, and configured and operated by users. Each of these steps brings with it difficulties and vulnerabilities.’
“It’s a lesson we have all learned over the decades. Cryptography is still necessary for cybersecurity—although I wouldn’t have used that word back then—but is not sufficient. There are particular attack and forms of mass surveillance that cryptography prevents. But as computers have infused throughout our lives, and networks have connected all those computers, those aspects of cybersecurity have become increasingly important, and vulnerable.
“Today, the cybersecurity world is changing yet again, this time due to the capabilities of artificial intelligence. AI isn’t advancing cryptography, but it’s changing cybersecurity. AI has demonstrated a superhuman ability to find vulnerabilities in software and to write exploits. A similar ability to write patches is probably coming. This has profound implications for both attackers and defenders, and it is unclear who will win the particular arms race in a world of what I call instant software.”
Post Syndicated from Ryan Smith original https://www.servethehome.com/intel-computex-2026-keynote-live-coverage/
Closing out Computex’s day 2 keynotes is Intel, where CEO Lip-Bu Tan will be outlining Intel’s vision for the Intelligence Era and engineering AI hardware across multiple markets. Come join ServeTheHome for our live blog coverage of the keynote
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Post Syndicated from Ryan Smith original https://www.servethehome.com/marvell-computex-2026-keynote-live-coverage/
Marvell’s keynote address will lead off day 2 of Computex 2026, where CEO Matt Murphy is taking the stage to discuss the need for and future of connectivity in AI data centers. Come join ServeTheHome for our live blog coverage of the keynote
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Post Syndicated from Ryan Smith original https://www.servethehome.com/nvidia-computex-2026-news-bytes-vera-rubin-now-in-production-dgx-station-gets-windows/
At Computex 2026, NVIDIA announced that its next-gen Vera Rubin platform is now in full production. The company is also bringing Windows to its high-end DGX Station systems, which will be available in Q4
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Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2026/06/vulnerability-disclosure-in-the-age-of-ai.html
New article: “Responsible Disclosure in the Age of AI: A Call for Urgent Action,” by Melissa Hathaway.
Abstract: Artificial intelligence is fundamentally reshaping the balance between vulnerability discovery and remediation. Frontier AI models are now capable of autonomously identifying exploitable software vulnerabilities at unprecedented speed and scale. This development exposes decades of accumulated technical debt created by a software industry that prioritized rapid deployment over secure-by-design engineering practices. Drawing on the evolution of software assurance, vulnerability disclosure frameworks, and U.S. cyber policy, this perspective argues that the current moment represents a strategic inflection point for governments, industry, and critical infrastructure operators. The author examines the growing tension between offensive and defensive equities in cyberspace, the emergence of AI-enabled vulnerability discovery capabilities in both the U.S. and China, and the increasing risks posed by unsupported legacy systems and AI-assisted code generation practices. Responsible disclosure can no longer remain a reactive or fragmented process, but must become a coordinated national and international resilience effort involving governments, software vendors, infrastructure operators, and emergency response organizations. The article concludes with an urgent call for accelerated remediation, large-scale patch management coordination, and sustained investment in automated vulnerability repair capabilities before adversaries exploit this rapidly narrowing window of opportunity.
Post Syndicated from Ryan Smith original https://www.servethehome.com/nvida-introduces-rtx-spark-an-arm-soc-for-windows-pcs/
Fresh out of Computex, NVIDIA has introduced its long-awaited Arm SoC for Windows PCs, the RTX Spark. With 20 CPU cores and a sizable Blackwell GPU, NVIDIA is setting their sights on powering the premium Windows market
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Post Syndicated from Ryan Smith original https://www.servethehome.com/qualcomm-computex-2026-live-coverage/
The second keynote of Computex 2026, Qualcomm’s CEO Cristiano Amon is at the show to talk about agentic AI, consumer PCs, and more. Come join ServeTheHome for our live blog coverage of the keynote
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Post Syndicated from Ryan Smith original https://www.servethehome.com/nvidia-computex-2026-keynote-live-coverage/
Computex 2026 kicks off with NVIDIA’s keynote. CEO Jensen Huang is taking the stage for two hours to discuss AI, PCs, robotics, and all things NVIDIA. Come join ServeTheHome for our live blog coverage of the keynote
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Post Syndicated from Patrick Kennedy original https://www.servethehome.com/asus-xa-nb3i-e12-review-a-massive-8x-nvidia-b300-gpu-server/
In our ASUS XA NB3I-E12 review, we see what makes this massive NVIDIA Blackwell Ultra platform with over 6.4Tbps of networking different
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