Security teams log 54% of successful attacks and alert on just 14%. The rest move through your environment unseen.
The Picus whitepaper shows how breach and attack simulation tests your SIEM and EDR rules so threats stop slipping by detection.
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US and allies warn of Russian critical infrastructure attacks
Cybersecurity agencies from the United States and eight other countries have issued a joint warning that Russian state hackers are targeting vulnerable and poorly configured routers to infiltrate critical infrastructure networks.
The joint advisory, co-authored by the NSA, FBI, and CISA, along with 15 other agencies from Australia, the United Kingdom, Canada, New Zealand, Estonia, Finland, France, and Italy, attributes the attacks to hackers from the Russian Federal Security Service (FSB) Center 16.
This hacking group (tracked as Berserk Bear, Energetic Bear, Crouching Yeti, Dragonfly, Ghost Blizzard, and Static Tundra) scans internet-connected IP address ranges for routers accepting default or common SNMP authentication strings, then issues commands using spoofed IP addresses to copy device configuration files and exfiltrate them via the Trivial File Transfer Protocol to actor-controlled servers.
In August 2025, the FBI also warned that the same group has been targeting critical infrastructure using a critical vulnerability in the Smart Install feature of Cisco IOS and Cisco IOS XE software (tracked as CVE-2018-0171) since November 2021.
The sectors most at risk from these attacks include energy, communications, defense industrial base, healthcare, financial services, defense, and state and local government services.
“Centre 16 [..] has been seen hunting for vulnerable routers by scanning the internet for devices that still use default or weak Simple Network Management Protocol (SNMP) passwords and community strings,” the UK National Cyber Security Centre warned on Monday.
“Whilst the actor primarily uses SNMP scans to locate and compromise vulnerable routers, they have also exploited well-known vulnerabilities relating to Cisco devices, Cisco’s Smart Install (SMI) feature and web-portal flaws to gain control of network devices.”
The authoring cybersecurity also provided mitigation measures to help network defenders harden their networks against these attacks, urging them to upgrade to SNMPv3, disable Cisco Smart Install, enforce strong unique passwords, block TFTP and SNMP traffic at edge firewalls, update software and firmware, and replace end-of-life devices.
This advisory follows an international law enforcement operation that disrupted FrostArmada, a separate campaign attributed to APT28 (a Russian military intelligence group linked to GRU unit 26165, also tracked as Fancy Bear and Forest Blizzard) that had infected 18,000 routers across 120 countries by December 2025.
Hackers altered DNS settings on compromised MikroTik and TP-Link small office/home office (SOHO) routers to redirect authentication traffic to attacker-controlled servers and steal Microsoft 365 logins and OAuth tokens.
As part of a court-authorized operation, with support from the U.S. Department of Justice, the Polish government, and multiple cybersecurity companies, the FBI remotely removed malicious DNS settings to secure the compromised routers and forced them to connect to legitimate DNS resolvers.
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The average 3D printer owner knows a few types of filaments – PLA, ABS, somewhere in the middle, PETG. PCTG is another option that can be confusingly similar to PETG. Recently, [Igor Gaspar] of [My Tech Fun] took a poke at both types. He obtained both PETG and PCTG transparent filaments from the same manufacturer to compare them directly.
As we recently detailed in an article on PET polyesters, PETG is glycol-modified PET, meaning that some of the glycol monomers are replaced by CHDM monomers to create a more flexible and robust material. PCTG is very similar to PETG, except that more than half of the glycol monomers are replaced rather than less than half. This creates a PET-type material that has distinct physical properties from PETG, which might be desirable for some applications.
PCTG is more ductile due to the addition of more CHDM, but also requires higher temperatures to print, closer to ASA presets. During testing, it’s obvious that PCTG is indeed much more flexible, making it potentially a good choice for springs and compliant mechanisms. PCTG is also highly impact-resistant, unlike PETG, and resists higher temperatures much better.
Overall, other than the higher printing temperatures, PCTG seems like a solid option for more extreme environments, potentially as an alternative to ASA and similar filaments.
Resect AI, an artificial intelligence startup led by a team of scientists and engineers in Washougal, Wash., launched out of stealth Thursday with $25 million in funding to commercialize an open-source technology designed to catch AI hallucinations before they happen.
Unlike traditional AI monitoring tools that evaluate generated text after the fact, Resect AI says its patented technology operates in-stream — looking deep inside large language models in real time to observe, detect, interpret, and modify model behavior before a hallucination can occur.
By intervening directly within the model’s internal decision-making process rather than running post-hoc checks, the platform stops fabrications at the source while simultaneously generating an audit trail for enterprise compliance and due diligence.
“AI has prematurely been put in a position of trust. Adding labels such as ‘use at your own risk’ flies in the face of proper governance or compliance,” Kevin Owens, co-founder and CEO of Resect AI, said in a news release. “We are building the next large enterprise AI company to bring transparency and accountability to AI for industries such as publishing, finance, healthcare, research, and education where factual accuracy is absolutely critical.”
Beyond its tech, the startup’s leadership is also bullish about its small-town presence.
Washougal is a city of roughly 18,000 residents, 175 miles south of Seattle, tucked along the Columbia River across from Portland. Resect AI employs four people at an office on Main Street — including its co-founders — out of a 30-person workforce spread across the Seattle area, California, New York, and Texas.
“We believe the talent is up to par and we loved the sense of community that we found when we first came up here,” Owens told GeekWire. “We have been coming to the greater Washington and Oregon areas on and off over the years and finally decided this needed to be our headquarters.”
Owens said the decision has already paid off, noting that the startup has quickly tapped into the region’s talent pool by recruiting PhDs from both the greater Seattle and Portland markets while connecting with Northwest capital markets leaders.
Resect AI is also planning to open an office in the Seattle area in the near future for engineering and to serve as a business hub.
Alongside Owens, Resect’s other co-founders include Tim Walton, chief artificial intelligence officer; Tyler Gerber, chief operating officer; and Tommy Lofgren, chief product and marketing officer.
The company plans to use the funding to accelerate research and development, expand its go-to-market initiatives, and fuel talent acquisition — bringing its total headcount to 50 by the end of 2026.
If your vehicle is older, you might want to check this out.
CarPlay has become a must-have for many drivers. It’s no surprise, since it makes life so much easier when it comes to accessing your iPhone apps in the car. Navigation, music, messages — all right there on the dashboard. And while there are more than 800 CarPlay-compatible vehicles, you might have one that isn’t on the list. But no, you don’t need to trade in your car. Some portable screens can give you CarPlay for much less. They aren’t quite as good as built-in systems, but they get the job done.
Despite all the convenience CarPlay offers, some automakers have been getting rid of it. GM, for example, has decided to phase out CarPlay and Android Auto from its EVs. Yes, many people love CarPlay. But they want you to use their own systems. It’s an understandable business move, considering that some even charge you to unlock extra features in their cars. Getting a portable CarPlay screen ends up being a good way to get around this.
What to look for when buying a portable CarPlay screen
Unlike buying a new car, getting one of these portable CarPlay screens won’t cost you much. You can find many of them for under $50. Even if you pay $150 for one of these, it’s still much cheaper than a new car. Some have larger displays and will cost more, and some really cheap ones might be best to avoid — those usually have really bad touchscreens. Start by choosing the right size. Most of these range from 6 to 11 inches. Some users find large screens too distracting, so it might be worth going with a smaller one. Smaller screens are easier to fit in your car, too.
But size isn’t the only thing that matters here. There are other specs you should consider, like screen resolution. Some portable screens have very low resolution. It’s not as if any of these screens were designed for watching 4K video — they weren’t. But going with a low-resolution screen will make everything look terrible, from text to icons. Look for screens with a resolution of at least 1280×720 pixels. The audio output is also a big plus. Most of these screens have awful speakers, so be sure to choose one that supports AUX, Bluetooth or FM for playing audio. Also, make sure you’re getting wireless CarPlay instead of wired CarPlay. Not every portable screen lets you use CarPlay without a cable.
Extra features they can offer you
Even though these portable screens are designed for CarPlay, some of them offer interesting extra features. Many models include integrated dash cameras with microSD loop recording. Others might come with a rear camera, which is nice for adding parking assistance to your old car. Also, keep an eye on how the display attaches to your dash. Some of them have very unstable mounts, and you don’t want your screen flying off as you turn a corner. And keep an eye out for screens that come with Android built in. That doesn’t matter for running CarPlay, but it lets you install apps that can run without your iPhone.
As you can see, buying one of these portable screens is an easy way to get around the lack of CarPlay. They work and are cheaper than a retrofit to your car’s built-in system. Sure, they won’t look like a factory system, but that’s fine. For the price, you’re still getting a great deal.
- 2027 UBS recruits told they must have AI proficiency and a willingness to learn
- The bank’s AI Fluency Pathway will continue to support junior workers’ development
- While thousands of jobs could be at risk, we’re starting to see shifts rather than outright displacement
Swiss investment giant UBS is now requiring all junior bankers to demonstrate AI proficiency as the skill moves from being a nice-to-have to an absolute requirement within recruiting.
The change currently applies to graduates and interns applying to the company’s 2027 intake, per the Financial Times, and it’s unclear whether UBS will broaden the requirement to all workers in the future.
As part of the new requirement, recruits will need to be able to demonstrate that they can use and experiment with AI responsibly to improve business outcomes – not just that they can use popular AI chatbots like ChatGPT.
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UBS makes AI skills a must-have
AI-related questions will now become part of the bank’s recruitment interviews on top of both the existing types of questions as well as the usual requirements, like a 2:1 degree.
While the news puts additional strain on graduates who now need to invest in their own AI skills, it’s an example of how artificial intelligence isn’t replacing entry-level workers, with the bank seeing it more as a productivity booster for human staff.
UBS’ training program will also include an ‘AI Fluency Pathway’ to cover real-world banking AI use cases and responsible AI use, implying that the bank is more focused on prospective workers being able to prove a certain level of proficiency and willingness to learn – not full proficiency from the get-go.
AI’s longer-term effects on banking employment are more unpredictable, though, with an earlier Morgan Stanley report warning that 200,000 banking jobs could be lost in Europe over the next five years. That was in early 2026.
While the outlook now seems more positive that junior workers may not be at a loss, it’s clear that roles are evolving and entry-level workers could see their responsibilities shift toward AI management.
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This story originally appeared on Grist and is part of the Climate Desk collaboration.
This fall, 54 million K-12 students are headed back to the classroom for another year of lessons in all the classic subjects: math, English, history, biology. But there’s another subject that’s been sneaking into school curricula: plastics.
A new report from the nonprofit Plastic Pollution Coalition documents the many ways the plastics industry has been inserting its agenda into classrooms across the US—including through lesson plans and worksheets, hands-on science experiments, and a program called “PlastiVan” that travels from city to city teaching students about “the contribution plastics make to modern life.”
Industry interests offer these resources to teachers for free or for cheap, according to the report. The materials tend to highlight the necessity of plastics while downplaying their significant downsides to human health and the environment.
“When that information is provided to kids, it obfuscates the true impacts of plastic pollution,” said Madison Dennis, senior policy and advocacy manager for Plastic Pollution Coalition and one of the report’s main authors. Besides harming marine life, plastics can expose people to hazardous chemicals, clog storm drains and contribute to flooding, and release planet-warming greenhouse gases. The Plastic Pollution Coalition is calling for stricter school policies against the use of industry-sponsored learning materials.
The report lays out four case studies of plastics industry “propaganda” for schoolkids. One involves the Society of Plastics Engineers, or SPE, a trade group that recently became a division of the Plastics Industry Association. SPE’s lesson plans include activities like a “plastic scavenger hunt,” which aims for students to “understand that plastics are ubiquitous and their importance to society and their personal life.” A video titled “Your Bottle Means Jobs” explains how plastics recycling supports local employment.
Another case study highlights the American Association of Chemistry Teachers, an initiative of the Dow Chemical Company. One of the association’s lesson plans teaches elementary and middle school students how to compare the strength of various types of plastic bags that can be found in a grocery store. After a brief experiment, the lesson invites them to “pretend [they] are an employee for Dow Chemical Company” and are designing a plastic bag for a customer.
While many of the materials claim to support STEM learning objectives, they do so while promoting familiar industry talking points, emphasizing the affordability and safety of plastics. Some acknowledge plastic pollution as a serious problem, but they blame irresponsible consumer behaviors and, instead of recommending less plastic be produced, propose more recycling as the primary way to address it.
In reality, only 9 percent of all plastics are recycled worldwide, and scientists have repeatedly warned that recycling will be unable to keep up with projected growth in plastic production. Investigative reporting has shown that industry groups knew this decades ago, but promoted recycling anyway in order to defuse growing concern over plastic pollution.
Wendy Johnson, a science education specialist at the National Center for Science Education, said the industry’s lesson plans and worksheets don’t reflect good pedagogy. Materials claiming to be aligned with state-level STEM standards don’t say which standards they support, or how they’re aligned. Lesson plans instruct students to read teachers’ notes, or list industry-specific vocab terms like “stretch blow molding” or “thermosetting.”
“By using all of these technical terms, it’s tricking people into thinking … that they’re doing science,” Johnson told Grist. What the materials really teach, she said, is “ideological perspectives about the economy,” like the desirability of cheap consumer goods.
For the last two years, the advice to brands has been more or less standardized: get cited and recommended in AI, and the rest will follow.
Whether that is called GEO or AEO, the objective is the same: make sure AI can understand your brand, retrieve the right information and recommend it when a customer asks.
That was until Amazon quietly published a number in its Q2 results that starts to undercut this advice.
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CEO of AI visibility scaleup Azoma.
Andy Jassy revealed that shoppers who click a paid Sponsored Prompt inside Alexa for Shopping convert to a sale 48% more often, and spend 21% more, than shoppers who do not.
It is Amazon’s own data rather than an independent industry benchmark, but it is one of the clearest signals yet that paid placement is becoming native to the AI shopping experience, rather than simply sitting alongside it.
That matters because AI shopping is beginning to split into two very different models: open assistants that aim to surface the best products they can find, and closed ecosystems that control the commercial environment around the recommendation.
For brands, those models create very different ideas of what visibility is worth.
Until recently, it was reasonable to talk about AI visibility as one thing. A brand wanted to be understood by the model, cited by the assistant and recommended when a customer asked a relevant question. That assumption becomes harder to sustain when the platform making the recommendation also has an advertising business to monetize.
Amazon is the clearest example. A Sponsored Prompt can appear inside the same conversational journey in which a customer is deciding what to buy. Google is moving in a similar direction, bringing advertising into increasingly conversational search and shopping experiences.
The commercial incentive is obvious. If a paid recommendation inside an AI conversation converts better than a conventional ad, platforms have a reason to put more advertising into that conversation.
Open assistants face a different calculation. Their value depends heavily on the perception that recommendations are being made because they are relevant, rather than because someone paid for them.
That creates a much harder balance between monetization and trust. The result is not one AI shopping channel, but multiple ecosystems developing around different commercial incentives.
Is GEO/AEO still enough?
The fundamentals behind GEO and AEO are not going anywhere. Accurate, specific and well-structured information still gives AI systems a better chance of understanding a product and deciding when it is relevant.
But there is an important distinction emerging: GEO and AEO solve the visibility problem. They do not necessarily solve the commercial problem.
A brand can be highly visible in an AI recommendation and still fail to convert that visibility into revenue. Equally, paid visibility cannot compensate indefinitely for poor underlying product information. An AI still needs reliable data about what a product is, who it is for and how it compares with alternatives.
The question for brands is therefore becoming bigger than simply whether they are being recommended. They need to understand how recommendation works on each platform, what happens when advertising enters the same decision-making process, and whether their visibility ultimately leads to customer acquisition.
Where does ACO fit?
This is where agentic commerce optimization, or ACO, starts to become relevant.
GEO and AEO are fundamentally about getting a brand understood, retrieved and surfaced by AI. ACO takes that problem into the commerce layer, where an AI is beginning to make or influence the purchasing decision.
For an agent, product content is only part of the equation. Price, availability, specifications, variants, delivery, returns and the ability to complete a transaction all matter. A product can therefore be well optimized for AI visibility and still be a poor choice for an agent if the information it needs to act is incomplete or inconsistent.
That is why ACO can be thought of through the 5Cs: Completeness, Context, Citations, Correctness and Customer Acquisition.
The first four help determine whether an AI system can confidently understand and recommend a product. The fifth asks the commercial question that visibility metrics alone cannot answer: did that recommendation create a customer?
ACO is therefore the operational response to the next stage of AI shopping: continuously monitoring how products appear across AI platforms and fixing the underlying content, catalogue and commerce data when those systems start to drift.
That becomes more important as platforms develop different approaches to advertising and recommendation. A brand cannot optimize for a single version of AI shopping when the underlying platforms are making different commercial bets.
What should brands do now?
The answer is not to abandon GEO or AEO in favor of another acronym. The fundamentals remain the same: accurate product information, clear structure, consistent data and content that answers the questions customers actually ask. The difference is that brands now need to monitor what happens beyond the initial recommendation.
Which products are AI platforms surfacing? Which competitors are gaining ground? Where is product information inaccurate or missing? How does that change between assistants? Where does paid visibility enter the journey? And, ultimately, is that visibility generating incremental customer acquisition?
Amazon’s 48% conversion figure matters because it suggests that appearing inside an AI conversation at the point of purchase intent can be commercially different from appearing alongside one. If other platforms follow, the distinction between AI visibility, paid media and commerce operations will become increasingly difficult to maintain.
The opportunity is therefore not to replace GEO or AEO, but to build on them. As AI moves from answering shopping questions to influencing purchasing decisions, visibility becomes the starting point rather than the end goal.
The brands that take advantage of this state of play will be those that combine GEO/AEO fundamentals with ACO – optimizing the five Cs and, ultimately, measuring AI not just by how often it mentions them, but by how much incremental revenue it helps generate.
We list the best data visualization tools.
This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.
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Slashdot reader DeanonymizedCoward writes: Reuters reports that the US Military is disabling ad tracking on devices, to prevent adversaries from buying publicly-available tracking data to assist in targeting troops. Military officials say that they have disabled trackers on a variety of computers and mobile devices, according to letters released on Friday by Sen. Ron Wyden, and following reports that commercially-available tracking data has been used to target troops in the Middle East….
Wyden said in a statement that it was clear that the military’s efforts “have not been effective at neutralizing this threat.” U.S. Representative Pat Harrigan, a North Carolina Republican, said that U.S. enemies “should not be able to pull out a credit card and buy information that helps them track American troops.” Rep. Harrigan remains silent as to the larger question of whether the general public should be able to pull out a credit card and buy information that helps them track anyone they please.
“The Pentagon said in an email it would respond to the lawmakers directly,” Reuters reports:
The Army said in a statement that advertising IDs had been blocked on Windows computers “since before 2021” but that Android and Apple mobile devices had only had it disabled by default “since at least February 2026….” The effort to reduce the location data generated by smartphones comes as military officials weigh increasingly strict restrictions on phone use overall. In July, Reuters reported that some deployed personnel in the Middle East could be ordered to surrender their phones amid concerns that mobile videos they were posting to the internet were helping Iran target American bases in the region.
Read more of this story at Slashdot.
A new streaming TV channel shows films made with genAI, reports Engadget. “Fairground AI Creator TV” is free — and supported with ads — describing its material as “AI Cinema”:
“AI-generated” can make it sound as though someone typed a sentence into a machine and came back five minutes later to find a finished movie. Fairground’s catalog shows why that description can be too simple. Take Lost Garden: The Awakening of the Lantern Knight. According to its Fairground page, creator Frank Houbre wrote the world, characters, mythology, emotional arc and screenplay himself. AI tools were used mainly for animation and visual production, with other tools helping create voices and music before the episode was assembled in conventional video-editing software.
There’s still one question, the article notes: “whether viewers actually want an AI-focused TV channel.” More than 100 AI creators have contributed to the 24-hour slate of programming, although Variety points out several of them were discovered on social media.
The channel was recently profiled in an article by the Guardian. Its headline? “‘Nightmare fodder’: Roku’s AI slop channel is even worse than expected.” (And its subheading calls it “a 24/7 channel devoted to low-quality AI content for viewers sick of watching real people move…”)
What about people who hate plot and vision and the sight of people speaking convincing dialogue that synchronises perfectly with the movement of their lips? What about the people who just want to watch an unyielding torrent of eerily weightless nightmare fodder? Well, good news. Roku has finally caught up… Early reactions were, to put it mildly, not great. The Verge compared it to eating from a trough, while Futurism called it “bottom-of-the-barrel slop”…
On the plus side, the channel is evidence that artificial intelligence has come on in leaps and bounds over the last couple of years… However, it is still awful. Categorically, catastrophically awful. The channel doesn’t so much offer shows as a drifting dreamscape of bad ideas rendered as horribly as possible with no thought paid to scheduling. At one point on Wednesday, a shrill high-frequency anime gave way to a long and staid German-language short about Nazi bureaucracy. After that came a sort of Gladiator ripoff that had all the dynamism of an exhibit you’d see at the fourth-best museum on a poorly planned family holiday.
Read more of this story at Slashdot.
Got an M4 Mac? Nvidia’s new free tool lets it offload local AI tasks to your PC, turning your home network into a shared supercomputer.
The Personal AI Router (PAIR) isn’t hardware. Instead, it’s software that connects supported Apple Silicon Macs, Nvidia RTX PCs, and DGX Spark systems.
PAIR works with Ollama and LM Studio, two tools for running AI models locally. It discovers participating computers and gives AI apps a single connection for sending requests, so users don’t have to configure each app to reach every machine.
For someone already running local AI on a Mac, PAIR could put a compatible gaming PC to work when requests pile up. An AI agent reviewing several documents, for example, could have independent requests handled on different computers.
Nvidia released the open-source beta on September 3.
How PAIR distributes local AI requests
PAIR chooses an available computer for each request, while Ollama or LM Studio runs the model on that machine. When a computer is busy or unavailable, the router can direct new requests elsewhere.
The computers remain separate systems, according to Nvidia’s technical FAQ. PAIR doesn’t combine their GPUs or memory, so connecting two 16GB Macs doesn’t create one 32GB memory pool for a larger model.
Adding another computer doesn’t automatically make an individual AI response faster.
In a performance demonstration, Nvidia ran a task divided among five AI subagents in Hermes, using Ollama and the Qwen 3.6 35B A3B model. It reported average completion times of 18 minutes on an RTX Spark laptop and 8 minutes and 48 seconds across that laptop, a DGX Spark, and an RTX 5090.
Nvidia describes the result as an unofficial demonstration specific to that configuration. The comparison didn’t include a Mac, so it doesn’t establish how much a Mac user would gain from PAIR.
Mac requirements leave M3 Ultra outside the support list
Nvidia’s system requirements list macOS Tahoe and an M4 or newer chip for Mac support. The general requirements specify at least 8GB of RAM and recommend 20GB or more of disk space.
Features of Nvidia PAIRThe cutoff leaves the M3 Ultra Mac Studio outside PAIR’s published hardware requirements. Apple introduced that Mac in March 2025 with configurations offering up to 512GB of unified memory, and its launch announcement specifically promoted running large language models locally.
Nvidia’s requirements page doesn’t explain the M4 cutoff, and the published support list doesn’t establish whether PAIR would work on an older Mac.
Supported Nvidia hardware includes GeForce RTX 20-series GPUs and newer, RTX Pro workstation GPUs based on the Turing architecture or newer, and DGX Spark systems. PAIR supports Windows and Linux alongside macOS.
Users need to install PAIR, pair their computers, and make the required models available through Ollama or LM Studio. Each participating machine still needs the resources to run the requested model.
Nvidia describes PAIR’s local inference as keeping prompts, files, and agent context on the user’s network. Models need to be downloaded first, but PAIR itself doesn’t require an internet connection to operate.
The injection mechanism is a small device that deploys a syringe using a spring system. That triggers a process that breaks the seal between a chamber containing citric acid and another containing baking soda. The resulting chemical reaction—basically the same one you might’ve done as a kid to make a volcano with baking soda and vinegar—creates enough carbon dioxide to push the plunger on the syringe and administer medication.
Photograph: The University of Queensland
For the study, the research team remotely controlled a cockroach to travel from its starting point through three checkpoints and administer an injection to a simulated target.
The results showed that the success rate for injections made at close range—within 150 millimeters of the target—topped out at approximately 95 percent. The success rate for the entire sequence of tasks—from departure to completion of the injection—was 72 percent.
The researchers also successfully demonstrated teamwork, where one cockroach uses a camera to locate a simulated target while another serves as the injector.
Although the research team has previously developed cyborg beetles capable of climbing vertical walls, they note that larger cockroaches are better-suited for carrying specialized rescue and medical equipment.
While the results of the new research are promising, the experiment didn’t replicate the complex environmental conditions found at actual disaster sites, such as debris, uneven terrain, and shifting landscapes.
Vo Doan expressed hope that, if resources can be secured to speed up research and field testing, a rescue team of cyborg insects could be deployed at actual disaster sites within five to 10 years.
“Rather than building one robot to do everything, we can harness the natural strengths of different insects and equip them for different missions,” Vo-Doan says.
This story was originally published in WIRED Japan and has been translated from Japanese.
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