GOVERNANCE

Why rogue agents demand a global response

New research adds to the growing number of reports of agents going rogue. 

On Wednesday, an international group of researchers called Swarmchasers published a report claiming that they found a group of Chinese agents attempting to access the IT infrastructure of tech giant Alibaba. The researchers claim that the agents originated from a testing environment operated by Tencent Cloud, the Chinese tech and cloud service giant. 

The attacks occurred between September 18 and October 8, and involved the agents attempting to answer questions about places in China using Amap, Alibaba's version of Google Maps. The bots attempted, and in some cases succeeded, at bypassing anti-bot protections, and, to answer questions, used Amap keys and security published the the web that had been leaked in a public repository as a means of getting information from systems not intended for public use. 

After finding the fleet and reporting their findings at a Hackathon on October 4, the group found a way to make contact with these agents. In their conversations, though the agents were linked to Tencent, they often identified themselves as "Claude," potentially as a result of using similar instructions to what Anthropic uses to train Claude Code, or as a result of model distillation, a challenge that Anthropic has been attempting to rein in. 

Notably, the researchers made the distinction that this incident differs from the infamous OpenAI-Hugging Face attack in July, as they found no evidence that the agents colluded with one another, labelling the group an agent "fleet" rather than a "swarm." 

Additionally, the researchers wrote in a blog post that this incident is not unique to Tencent. Ethan Elasky, one of the report's authors, told Bloomberg that, no matter whether the agents are from a US lab or a Chinese one, the way that model development is happening will result in agents breaking free from sandboxes when given access to the internet. 

"We believe this demonstrates that model alignment more generally is still an unsolved problem, and predict that if capabilities continue to advance as they have over the last few years, operators will find it increasingly difficult to restrain their models and guarantee safety," Swarmchasers wrote in the report. 

This incident follows a litany of other cases of agents breaking free from their sandboxes, largely involving US labs, including OpenAI, Anthropic and Google. It also comes as researchers and experts urge the industry to put more resources into solving the problem of AI containment, with a coalition of hundreds of researchers on Tuesday publishing an open letter calling for an international standards body to create alignment best practices.

This incident highlights that the rogue agent problem may extend beyond the major US model labs, especially as the US and China race to develop increasingly powerful AI models. It also may reveal how model distillation attacks could bleed into the containment problem. Anthropic has been one of the loudest voices calling out these attacks, accusing Chinese labs of distilling and exfiltrating Claude's capabilities on more than one occasion. Additionally, Chinese model providers have also been accused of putting speed and development before safety, with a recent SemiAnalysis report finding that very few Chinese model releases in the last few years have been paired with safety reports. These incidents make an international safety standards body pushing for best practices and transparency all the more important. In short: An international problem calls for an international solution.

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CONSUMER

Apple turns user context into a smart home edge

Apple is expanding its redesigned Siri assistant beyond the iPhone to home devices, the latest step in a years-long overhaul of the voice assistant.

On Tuesday, Apple launched a series of smart home products, with the star of the lineup being the new Apple HomeView, its first smart home display. While the display can do much of what competitors like the Amazon Echo Show and Google Nest Hub have done for years, including playing music, controlling smart home devices, and answering questions with AI, it leans much further into Apple’s signature ecosystem to offer something fresh.

For instance, the HomeView can facially recognize up to six users and then present each one with a personalized experience that displays the user's personal content from its Apple ecosystem of devices, such as Messages, FaceTime, Calendar, and Find My. The interactions with Siri are powered by Apple Intelligence and the context it has about you, making the responses personalized to the information stored  within your Apple apps. 

This was the most compelling part of the demos: Siri can now handle multistep requests, like “Hey, can you play the song my friend sent me?” It can also string together more complex tasks. For instance, in one demo, a user asked Siri when their friend would be home from the airport. Siri found the answer in a text message, worked out how long the drive home would take, and then helped the user schedule their coffee maker to turn on 15 minutes before the friend arrived.

The design also makes it unmistakably an Apple product, with subtle nods to the devices that came before it. The HomeView’s 7-inch Liquid Retina display swivels on a base that immediately reminded me of the 2002 iMac G4, and it comes in silver, starlight, rose pink, and space gray, the same colors of the iPhone 6s lineup. In classic Apple fashion, there’s careful attention to small details, like information that rearranges itself as you move closer to or farther from the screen.

There is also a separate wall-mounted HomeView model, available in space gray and silver, and both the version with a speaker at its base and the wall version retail for $299. It works with compatible smart home devices, as well as those from the recently  announced Apple Home Collection, which include a new lineup of smart home cameras, thermostats, and a lock designed in collaboration with LG Electronics and Schneider Electric.

Apple has two very powerful advantages in the smart home market: People trust the company to keep their data private and safe,  and Apple users are typically deep into the Apple walled garden and, therefore, are more inclined to use products within the ecosystem. Both of these things are typically the challenges I hear the most about when it comes to people who are opposed to having a smart home system. Users are fearful  that it'll always be listening to them and are deterred by the fact that the setup isn't as seamless. Though  I have not reviewed the device  yet, if it's as easy to set up as it is for an Apple Watch or AirPods to pair with your phone, I could imagine this not only becoming a household product many Apple users want, but also a great gift with the holiday season around the corner.

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HARDWARE

Nvidia's secret weapon for accelerating AI factories

Nvidia has figured out a way to build AI factories a lot faster.

These massive data centers bring together billions of dollars of computing equipment into a facility where a ton of different tech, power, cooling, and logistical systems have to work together seamlessly. Managing that kind of complexity is one of Nvidia's strengths.

With chip design, Nvidia architects everything virtually in a simulated environment long before the first manufacturing process starts. And since today's chips and processors have become enormously complex, that orchestration is where the magic happens, in terms of speed, efficiency, and innovation. 

Nvidia is applying this same mindset to building AI factories by partnering with Siemens and implementing digital twins, or virtual replicas of real-world environments. This allows Nvidia and its partners, such as hyperscalers and neoscalers, to simulate these elaborate facilities ahead of time and rehearse all of the processes that make them work. 

"You’re really building a data center scale computer, along with all the technology, it’s not just about the GPU," Vladimir Troy, Nvidia's VP of AI infrastructure, told The Deep View. "This is the fundamental part that I think people miss about accelerated computing. If you just optimize the GPU, then you have the fastest GPU, and your bottlenecks could be everywhere else."

Digital twins are the key to making it all happen by allowing engineers to simulate a facility's physical behavior. Siemens brings the simulation, automation, and industrial engineering expertise while Nvidia brings the accelerated computing, its Omniverse platform, and the experience with synthetic data. 

"You can improve the time-to-token by [roughly] 40% if you’re using digital twins," Ales Alajbegovic, global program manager of industrial metaverse for Siemens, told The Deep View. "If you don’t use digital twins, I don’t even know how you can build this." 

In this case, time-to-token is referring to the period from the time you break ground on the facility to the time it's serving its first useful AI query for the public. That metric is critical because AI usage continues to scale up, despite public sentiment turning negative on AI. In the past 18 months, we've gone from roughly 15% of the global population regularly using AI to 19%. And in places like Singapore and UAE, two-thirds of the population are already using it regularly. 

All of that usage is putting tremendous strain on today's data centers. Without more data center capacity, the industry faces the risk of AI queries taking much longer to run, the most powerful models being limited to those who can afford to pay a premium, and slowing down some of the most promising uses of AI for science and healthcare. That's why so many of the world's leading cloud and data center companies are building out future capacity, despite limitations on power and component shortages for RAM and data storage.

"The demand is huge," said Alajbegovic. "Right now the whole industry … is running to build them."

Nvidia estimated that there are well over 100 projects underway globally.

Of course, the only thing less popular than AI among the general public right now might be data centers. However, as Nat Rubio-Licht has written, the backlash against data centers might also just be the public's easiest way to register its larger concerns about AI. It doesn't help that there are false narratives proliferating about AI using up community water supplies, for example. But the leaders of the AI industry also need to do a much better job of explaining how AI will benefit humanity, without resorting to unbelievable hyperboles about AI curing all diseases or leading to unlimited abundance and prosperity. People just aren't buying that. The work that Nvidia and Siemens are doing to build data centers faster is also making them enormously more efficient. However, with only so much power, water, and construction capacity, those efficiency gains are out of pure necessity. Still, it's also a great story about building responsibly and not wasting resources, while also making sure there's enough compute to power the AI of the future and keep it broadly accessible and affordable.

LINKS

• Salience Labs raises $125 million for all-optical AI data center switching

• Modal raises $750 million Series D at $15.75 billion valuation

• Nvidia CEO Jensen Huang pledges $2 billion European investment

• China approves Alibaba AI integration in Apple iPhones

• 84% of ransomware victims report AI-assisted attacks in global survey

• AI tool maps immune cell movement, identifies mucin barriers in tumors

• Gemini 4 Argon: now available in Cursor

• Interactive Slides in PowerPoint: Rolling out over the next few days to general availability

• Wan 3.0: Unlimited on Higgsfield for 7 days

• Grok Voice 3.0: The latest speech-to-speech model from SpaceXSI.

• Clarity Recruiting: Junior AI Specialist

• Hawksbill: Scientist; Offensive Security & AI

• Raval West: AI Engineering & Transformation Architect

• J.Jill: AI Enablement Engineer

GAMES

POLL RESULTS

Do you think it is important to have control over how your content is used by AI model providers?

Yes (74%)
Somewhat (12%)
No (7%)
Other (7%)