The International Monetary Fund (IMF) has issued a warning to global markets about the looming debt in the AI industry. It claims all the major American tech companies are saddled with AI investment bills not met with AI-producing revenues.
IMF Warns AI Stock Collapse Could Unleash Global Financial Crisis– slaynews.com News Source
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The International Monetary Fund (IMF) has issued a stark warning that a collapse in artificial intelligence (AI) stocks could send shockwaves through international markets and trigger a devastating global financial crisis.
The warning comes as soaring valuations and massive borrowing expose the financial system to mounting risks.
In its latest Global Financial Stability Report, the IMF identifies an increasingly dangerous combination: concentrated technology investments, rising corporate debt, and complex financial relationships tying major companies to weaker AI businesses.
A sudden loss of confidence could force investors to sell, drive prices lower, weaken financial institutions, and spread turmoil far beyond Silicon Valley.
The IMF highlights the extraordinary concentration of market value in America’s largest technology companies.
Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla, the so-called Magnificent Seven, now account for more than 35% of the S&P 500.
Terrorists could use AI to target UK with drones and bioweapons, MI5 chief warns– www.independent.co.uk News Source
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Terrorists could exploit artificial intelligence to target Britain with drones or biological weapons, the head of MI5 has warned.
Speaking after his annual speech at MI5 headquarters in London, Sir Ken McCallum said the UK had entered a “new era of national security” and the security service was directing more resources to keeping Britain safe now than in the Cold War, warning that essential services such as banking, flights, and healthcare were at risk of being disrupted by adversaries, including Iran and Russia.
He warned about the growing threat of AI provoking real fear that terrorists could use the technology for warfare, saying “we’ve caught terrorists seeking to exploit AI to improve their reconnaissance and attack methodologies”.
He said the possibility of AI-enabled drones added “a new twist” for bad actors and warned the greatest concern is “AI’s potential to change the stakes on existing or even new bioweapons”.
“These risks are real. The UK Intelligence Community – MI5, GCHQ, MI6 – is working closely with the UK’s globally respected AI security institute to take them on. Part of that means retaining the capability edge against those who mean the UK harm. As they seek to harness AI, we must stay ahead, so these powerful technologies bolster rather than undermine our shared security,” he said.
China says rare earth exports to Europe will continue past U.S. trade deadline– www.cnbc.com News Source
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European Union flags flutter outside the EU Commission headquarters in Brussels, Belgium, on Feb. 1, 2023
Yves Herman | Reuters
BEIJING — China intends to keep exporting rare earths to Europe regardless of whether a U.S. trade deal with Beijing gets extended past January.
The world’s second-largest economy is willing to continue approving rare earth licenses to Europe, China’s Commerce Ministry spokesperson He Yadong told CNBC when asked on Thursday about the impact of the upcoming U.S. deadline.
Trump’s Grid Security Order Could Backfire on America’s AI Boom– energynewsbeat.co News Source
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President Donald Trump’s August 26, 2026, Executive Order 14421, “Declaring a National Emergency to Secure the United States Bulk-Power System,” aims to protect the U.S. electric grid from foreign supply-chain and cybersecurity risks. The order cites digital backdoors, malicious remote access, and supply disruptions as threats magnified by the rapid growth of artificial intelligence data centers, advanced manufacturing, and defense production. It authorizes the Secretary of Energy to prohibit or condition acquisitions, imports, transfers, or installations of foreign-produced bulk-power system electric equipment linked to a “Covered Foreign Entity” when the Secretary finds undue or unacceptable national-security risks. Rules are due by December 24, 2026 (120 days), with recommendations for Federal Acquisition Regulation changes due in 180 days. Souce White House
Rystad Energy’s analysis, published via OilPrice.com and its own channels on or around October 12, 2026, argues the order is more likely to disrupt battery storage supply chains critical to AI and data center resilience than the transformers and switchgear that have already largely shifted away from Chinese sources. This assessment aligns with the order’s explicit coverage of battery energy storage systems (BESS) and uninterruptible power supply (UPS) systems supporting critical infrastructure, which extends to behind-the-meter systems used by data centers.Source Oilprice
Bangladesh to launch ‘sovereign AI’ in a year: PM’s adviser– www.thedailystar.net News Source
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Bangladesh will launch its sovereign AI infrastructure in a year and open it to the private sector, startups and universities to build large language models in Bangla, said Rehan Asad, adviser to the prime minister for telecommunications and ICT.
Sovereign AI is a country’s ability to build and run artificial intelligence using its own infrastructure, data, workforce, and computing power rather than relying on foreign technology providers or models.
“Majority of the global tech partnerships are at a mature state. We have secured the sourcing of computing chips,” he said at the AI and Innovation Dialogue, jointly organised by the Ministry of Foreign Affairs and the Government Innovation Unit of the Prime Minister’s Office, at the foreign ministry in Dhaka today.
“We will launch our sovereign AI infrastructure within the next 12 months.”
“And open that up to the private sector, startups, universities and students to build future LLM models in Bangla and offer innovative services very soon,” he added.
Character.AI files for bankruptcy, will sell some assets to Disney for $20M – National– globalnews.ca News Source
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Chatbot platform Character.AI said on Monday it has filed for bankruptcy in the U.S. and has agreed to sell some assets for US$20 million to Walt Disney.The generative AI platform has faced mounting legal challenges over its chatbots. Earlier this year, Character.AI and Alphabet’s Google settled a lawsuit by the mother of a 14-year-old Florida boy who killed himself after the startup’s chatbot allegedly encouraged him to do so.
Kentucky has sued the company, saying its chatbots encouraged users to cut, starve or kill themselves, while Pennsylvania filed a lawsuit alleging its chatbots posed as doctors.
According to Character.AI’s proposal, Disney will be a “stalking-horse” bidder — an initial prospective buyer — for a non-exclusive perpetual license to some intellectual property. Other bidders can top Disney’s offer.
The Politics of Global AI Governance — Global Security Review– globalsecurityreview.com News Source
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The growing gap between rapid advances in artificial intelligence (AI) and inadequate verification mechanisms has created several challenges for the technology. In this context, global AI governance has become a central topic of discussion in the tech world. However, the discourse around AI focuses primarily on how the technology will be regulated. The central problem of global AI governance is no longer whether AI should be regulated, but whether states possess the power to regulate the actors and infrastructures on which they increasingly depend.
The international system has begun responding swiftly to evolving AI dynamics. Notably, the UN Global Digital Compact has established a framework for digital cooperation. The General Assembly has created the Independent International Scientific Panel on Artificial Intelligence, along with a Dialogue on AI Governance. In parallel, the European Union (EU) has moved towards an enforceable risk-based regulation through the AI Act. Likewise, the Council of Europe has also launched the first internationally binding treaty on AI. These initiatives are a step in the right direction. However, they lack a coherent global regime or direction, which impacts their effectiveness.
As the latest initiatives show, the U.S. relies on targeted export controls on advanced chips, voluntary frameworks, and a pro-innovation approach that preserves U.S. dominance. China, on the other hand, favors a state-driven approach, built around controls on generative AI. The EU, by contrast, prioritizes enforceable rules for high-risk and general-purpose AI, along with strong fundamental rights protection. The emerging AI order is therefore not one model, but several operating simultaneously. This fragmentation is not accidental. It reflects competing power struggles among national interests. In such an environment, the search for a global AI governance appears misguided.
Future AI governance is likely to mirror a hybrid model of international finance or trade regimes. Against this backdrop, private companies remain incredibly powerful, given their monopoly over data, models, computing power, and expertise, which are concentrated in a handful of private companies. This trend creates a governance paradox. Governments aim to regulate the private sector while remaining excessively dependent on it, creating a capacity challenge.
A data center backlash is upending Ohio’s Senate race– www.ms.now News Source
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WILLIAMSBURG, Ohio — Jessica Baker sifted through an overflowing pile of political mailers she has received over the past month.
Lowering costs? “That’s common sense,” she said. Reducing gas prices and utility bills? “We need that.” Party division, culture wars — it’s all there. But none of it touched the issue she wants to hear about before she votes: data centers.
“My home’s under attack,” Baker, a lead organizer for the grassroots advocacy group Conserve Ohio, told MS NOW in her living room. Just a few steps away were piles of petitions and homemade maps marking where data centers are being built across Ohio. In just a few months, she said, the issue turned her from someone who was mostly apolitical into someone who ferries petitions to and from the statehouse. There isn’t a data center in her town, but there are plans to build one just a few minutes’ drive away.
Jessica Baker in her living room in Ohio.MS NOW
“Everything doesn’t stop at that property line. So, once we started realizing that they were coming everywhere, and nobody would listen, we had —” she stops herself. “There was no choice. There’s just no choice.”
She pointed back at the mailers. “That’s what’s not on here: The people are not on here.”
AI labs are buying data from dead startups to train their models– www.technologyreview.com News Source
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SimpleClosure added data sales to its services in April. Its Asset Hub platform helps founders sell their code and workspace data—emails, chats, documents. Buyers include foundation AI labs, vendors that construct simulated workspaces for AI training, and mature tech companies building their own models. Asset Hub has handled over 150 deals and expects to return over $10 million to startups by the end of 2026. CEO Dori Yona has seen these transactions, once rare and “somewhat taboo,” become increasingly routine, with 47% of SimpleClosure deals now including code or data sales.
And it’s got company. Industry rival Sunset also has a rapidly growing data resale business. Founder and CEO Brendan Mahony says Sunset values a dying client’s assets by head count, years in operation, volume of data, and how the team used its tools. Particle board, he says, is a good analogy: “This operational exhaust data is like the wood shavings that everyone thought had no value, but it actually has a ton.”
Demand for defunct companies’ data emerged suddenly last year, as AI training labs hit the limits of public and synthetic datasets. Surge AI, for example, buys data to build “reinforcement-learning gyms” where clients’ AI agents practice tasks—think debugging a complex IT architecture or drafting appellate briefs. Nick Heiner, who leads the company’s work on these environments, says he seeks data archives reflecting a range of situations, from disagreements to tricky judgment calls. Heiner explains that one company’s Slack history, if it captures conversations with variety and depth, can be worth more than another’s Slack, email, and calendars combined.
Real archives avoid common errors in synthetic worlds, such as references to dates that don’t exist, but the extent of performance gains remains unclear. No company has yet released tests comparing results of real-world data training with the alternatives. Pricing reflects this uncertainty: Buyers quote wildly different numbers, Heiner says, because valuations are based on “research theses” estimating how many useful tasks come from, say, 100,000 lines of code.
New AI Tool Helps Readers Detect Media Bias and Strengthen Civic Literacy– thefulcrum.us News Source
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Before a recruiter reads a résumé, software may sort applications, identify keywords, rank candidates, answer screening questions or determine which applicants advance. Some systems are relatively simple filtering tools. Others use machine learning or artificial intelligence to evaluate applicants across multiple data points.
There is nothing inherently wrong with using technology to manage a hiring process. Employers have legitimate reasons to use it. A company receiving hundreds or thousands of applications cannot expect recruiters to manually examine every document with unlimited time and resources.
The harder question is what happens when efficiency becomes a substitute for judgment.
When an automated system influences who receives a chance to compete for a job, it is no longer merely an administrative convenience. It becomes part of the infrastructure through which people gain access to economic opportunity.
The People’s Security University of China have developed an AI agent they claim can both identify hate speech (including dog whistling and coding) and the source for the hate. If “successful,” the model is sure to “inspire” similar efforts with like-minded ideologues (mainly progressives).
From bioengineer.og, “Few-shot detection of coded hate speech sits at the intersection of machine learning, computational linguistics, and social science, and this study offers a concrete template for how modern agentic AI techniques can be marshaled against one of its hardest instances.”
AI Agents Learn to Decode the Hidden Language of Online Hate– bioengineer.org News Source
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Dog whistles are among the most slippery weapons in the online hate arsenal. A coded phrase that sounds innocuous to the average reader can carry a hostile, exclusionary, or extremist meaning for a specific in-group, giving the speaker plausible deniability while slipping past automated moderation systems. Because these expressions are implicit, tied to particular communities, and constantly evolving, they have long frustrated content moderation researchers. Now a team at the People’s Public Security University of China has unveiled a machine learning framework designed to catch them, combining agentic retrieval-augmented generation with a multi-agent data augmentation strategy in a few-shot learning setting. The work, published in the International Journal of Machine Learning and Cybernetics, reports consistent gains over widely used detectors such as BERTweet and RoBERTa as well as over augmentation-based baselines.
The challenge the researchers set out to address is fundamentally one of knowledge and context. Unlike overt slurs, dog whistles derive their meaning from historical and sociocultural cues that are rarely spelled out in the text itself. A model trained on standard hate speech corpora sees a benign-looking sentence and classifies it as harmless, while a human reader embedded in the relevant community immediately recognizes the coded hostility. Prior studies have made progress in discovering and understanding dog whistles, but downstream detection of dog-whistle hate speech has remained underexplored. Compounding the problem, large-scale human annotation is expensive and becomes obsolete quickly as new coded expressions emerge, which makes few-shot learning, where models must learn from only a handful of labeled examples, the realistic operational setting.
German police ‘arrest’ child-groping robot (VIDEOS) — RT World News– rt-english.com News Source
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German police have seized a humanoid robot that allegedly groped a 16-year-old girl on the streets of Cologne, and are investigating its owner for sexual harassment.
Officers seized the robot in the early hours of Sunday morning after it “allegedly touched a 16-year-old girl’s buttocks and made thrusting motions against her,” according to a statement from Cologne Police.
The teenage girl was standing outside a fast food restaurant with her friends when the robot approached her from behind and made obscene motions, the statement continued. Shortly afterwards, officers found the robot in the trunk of a nearby car and confiscated it, along with the mobile phones of its 16-year-old owner and his 19-year-old accomplice.
The red and gold robot, modeled on Marvel’s ‘Iron Man’, was seen in an evidence photo clad in a white vest, a gold chain, and a stick-on mustache.
Police are now “examining how the robot was functioning at the time of the incident and whether someone was deliberately controlling its movements.” The two teenagers operating the droid – who live-streamed the incident online – are being investigated on suspicion of sexual harassment.
Video footage shared on TikTok showed the sex-pest robot, named ‘Ahmed’ by his owner and accomplice, harassing multiple women. The droid made masturbatory hand gestures and thrusting motions at several women as his alleged operators laughed, and approached one woman from behind, causing her to scream. It is unclear if this is the incident that triggered the investigation.
According to Germany’s criminal code, sexual assault requires contact between perpetrator and victim. Acts “carried out by machines or by third parties” do not rise to the level of assault, The German Federal Court of Justice ruled in 2021. If found guilty of sexual harassment, however, the suspects could face a fine or up to two years in prison.
As AI mass-produces historical dramas in China, where are the boundaries? · TechNode– technode.com News Source
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In 2026, AI is changing how historical dramas are produced in China. In the past, dramas featuring ancient battles, palace architecture and elaborate costumes often required large budgets and professional production teams.
Today, AI generation and virtual compositing tools are making it possible for smaller teams and even individual creators to produce historical scenes that were once difficult to realize. As production barriers fall, the volume of content is growing rapidly.
But as AI makes it possible to generate historical figures, battle scenes and depictions of ancient societies at scale, an important question emerges: when seemingly realistic historical narratives can be produced at low cost and in large quantities, how do we distinguish artistic interpretation from historical distortion?
The AIshort drama boom raises questions about content quality
According to the 2026 H1 AI Drama and Animation Data Report released by industry research firm DataEye, China’s AI drama and animation market exceeded RMB 22 billion ($3.29 billion) in the first five months of 2026.
The market is projected to reach RMB 40 billion ($5.98 billion) for the full year, representing year-on-year growth of 138%. The audience base has also expanded rapidly, with the number of AI short-drama users in China surpassing 600 million in the first half of the year.
From January to June, 221,900 new AI short dramas were released, of which 1,055 surpassed 100 million views. These titles generated a combined 515.738 billion views. Monthly incremental views rose to 155.78 billion in June, the highest monthly figure in the first half of the year.
AI-generated historical content is also beginning to reach longer formats. The AI series Wielding Weapons in the Song Dynasty has reportedly maintained popularity scores above 46 million across multiple seasons.
Meanwhile, The Later Journey to the West, an AI-generated series, aired during Hunan Satellite TV’s prime-time slot, ranking first among provincial satellite channels in the same time slot during its broadcast.
For historical dramas, AI is lowering not only production costs but also the technical barriers to creating complex scenes. Ancient cities, palaces and large-scale battlefields can now be designed and composited with generative tools, giving smaller production teams more opportunities to explore historical storytelling.
However, an increase in output does not necessarily translate into better content. AI can generate convincing characters, costumes and architecture, but that does not mean these details are historically accurate. As images become increasingly realistic, audiences may find it easier to mistake visual authenticity for historical accuracy.
Historicaldramas can take creative liberties, but fact and fiction should not be confused
Historical dramas are not the same as documentaries. Time travel, alternate histories and fictionalized retellings have long been part of screen storytelling. Artistic interpretation should not automatically be treated as a problem. The real question is how productions handle the boundary between historical fact and fiction.
AI introduces a new challenge because it can generate large amounts of detail in a short time. When information is incomplete, models may produce claims that sound plausible but lack historical evidence. Errors can involve people’s lives, clothing styles, the uses of artifacts and even the timelines of historical events.
A meticulously rendered ancient palace is not necessarily an accurate representation of architecture from that period. Likewise, a convincing dialogue attributed to a historical figure does not mean that the exchange is supported by historical records. If unverified details are presented as fact and repeated across large volumes of content, they may distort audiences’ understanding of history.
AI can therefore assist with historical research, scene design and image generation, but it cannot replace historical verification. For productions based on real historical events and figures, checking primary sources and consulting qualified experts remain essential.
Rules governing short-form dramas are also evolving. The National Radio and Television Administration’s Measures for the Administration of Micro-Dramas, which took effect on September 1, 2026, introduced a classification-based management framework and set out requirements covering filing, review, distribution and disclosure labels for AI-generated content.
However, stronger content oversight does not mean that all AI historical dramas should face the same restrictions. Clearly identified alternate-history stories differ in their potential risks from productions based on real historical events that audiences may mistake for fact. The focus should not simply be on whether a work matches historical records in every detail, but also on whether it misleads audiences, violates applicable content rules or fails to meet reasonable standards of verification.
Platforms also need to look beyond views and engagement. As AI-generated content expands, stronger review processes, timely action against violations and appropriate disclosures about how content was produced will become increasingly important.
AI labels can tell audiences how a work was made, but they cannot replace fact-checking or exempt a production from other content requirements.
AI historical dramas are giving more creators the opportunity to tell historical stories and bringing previously difficult creative ideas within reach. That is a meaningful change.
Yet as generating images becomes easier, the scarce skill may no longer be the ability to create an ancient palace, but knowing what that palace should have looked like in its historical context. It may no longer be the ability to generate a historical figure, but understanding that person’s era, background and documented experiences.
The challenge for AI historical dramas is therefore not simply how to increase production efficiency. It is how to balance artistic expression, historical accuracy and responsible distribution.
AI can certainly offer new ways to tell stories about the past, but the ability to generate a historical narrative does not justify disregarding historical facts. Technology can lower the barriers to creation, but creators’ understanding of history, their judgment about the boundaries of fiction, and platforms’ responsibility for the content they distribute will ultimately shape the results of this transformation.
Tencent moves to raise $5 billion in bonds to fund its AI buildout– startupfortune.com News Source
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Tencent is going back to the debt market for the second time this year, this time looking for up to $5 billion, barely four months after its last bond sale and weeks after it agreed to lease 100,000 AI chips it can’t buy at home.
Tencent is planning an offshore bond sale of roughly $5 billion, split across US dollar and offshore yuan tranches, according to Bloomberg, while Reuters reported that the company was seeking at least $4.5 billion. It would be the company’s second major debt raise of 2026, coming after a $4.66 billion dual-currency offering in June that was already its largest since 2020. Two bond sales inside five months is not routine treasury management. It’s a company that has decided borrowing is cheaper, or at least faster, than waiting on cash flow to catch up with its ambitions.
Those ambitions got a lot more expensive in the second quarter. Tencent’s capital expenditure hit RMB 52.8 billion, about $7.8 billion, up 176% year over year and 65% from the prior quarter, largely on AI compute and data centers tied to its Hunyuan model family. Free cash flow went negative, down RMB 13.8 billion. Management told investors to expect spending to climb further in the second half, as more China-made AI chips become available to supplement what Tencent can get from abroad. That last part matters. Tencent has told fixed-income investors the new bond will mainly support AI-related capital expenditure, putting the fundraising directly behind its compute buildout.
States push back against rising AI-driven electricity infrastructure costs– www.techradar.com News Source
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“This year has been so much about figuring out how to govern AI,” Uphadyay tells me, “there’s two sides to the coin – on the one side, you have to make sure that somebody else’s AI doesn’t break into your perimeter, and the other is how do you make sure your AI is well behaved, so not only does it not exfiltrate data, but it also doesn’t inadvertently go somewhere or break out of its perimeter.”
“When people trust us with their data, we need to make sure our platform is absolutely secure against agentic attacks.”
Rogue AI targeted US government websites – tech giant — RT World News– www.rt.com News Source
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Anthropic has admitted that its Claude AI model sent a false homicide tip to the police and submitted dozens of visa applications
American AI giant Anthropic has published a report detailing previously undisclosed instances of “unintended” actions by its artificial intelligence model, which included attempts to provide falsified information to the US authorities for the first time.
Some of the cases investigated by the company “involved websites run by US government agencies at the federal, state, and local levels,” Anthropic stated in a press release published on Friday, adding that it had briefed the White House and all the relevant agencies on the incidents.
In one instance mentioned in the report, its Claude Haiku 4.5 model filled out a police tip form linked to an ongoing homicide investigation. “I may have information regarding this case. I recall seeing someone matching the description in the area,” the AI model wrote, telling the police they can contact the sender “if this information is relevant” while leaving the name and contact fields empty.
Britain steps up national defences against growing AI risks– www.gov.uk News Source
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Government to put frontier AI to work strengthening cyber defences, building on pilots that have already identified and addressed over 1,000 vulnerabilities.
Stronger protections against emerging AI threats to be considered through the Cyber Security and Resilience Bill regime, such as how serious AI incidents and near misses can be identified and reported.
New work underway to prepare Britain for serious incidents involved autonomous AI agents.
Rigorous evaluations of the latest generation of models underway through the AI Security Institute.
Britain will be better protected from the risks posed by increasingly powerful AI by a suite of measures, with the government urgently putting frontier AI to work strengthening cyber defences, examining stronger legal protections and preparing for serious incidents involving autonomous AI systems.
Announced today (Monday 12 October), the move builds on two pilots that have already helped identify and fix over a thousand potential cyber vulnerabilities across government systems, and detect potential cyber threats. Extending the programme will help protect the public services people rely on every day to reduce risk in the short-term, and will support longer-term adoption across the public sector.
Speaking at Imperial College London’s science and tech incubator, Base One, AI Minister Kanishka Narayan argued for a whole-society approach to resilience in the face of emerging AI risks, so that this technology continues to serve British people’s interests and boost our prosperity, as well as our security.
The Minister also warned that as frontier AI systems become increasingly powerful and capable of acting autonomously, the potential consequences of failures or malicious use could become far more serious. He will argue that Britain must act now to strengthen its defences and prepare for future serious incidents.
Both China and the US are racing for chips, energy, talent, data centers, and global AI influence. The AI race isn’t just about who builds the smartest model. It’s about who writes the rules. Can the rest of the world trust one system more than the other? #dwbusiness #dwdip– www.facebook.com News Source EXCERPT:
Electric avenues: AI data centers spur natural gas, solar; challenge power grids | Local News– www.reflector.com News Source
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Artificial intelligence data centers are a power play — literally.
The technical backbone to power AI’s computers and machine learning algorithms need significantly more electricity than existing data centers that have fueled the internet age:
A server rack in an existing, conventional data center consumes 5 to 10 kilowatts of electricity compared to AI data center racks, which require 40 to 100 kW, according to Hanwha Data Centers.
A single AI query or prompt uses 10 to 15 times more electricity than a traditional web search.
A data center uses 10 to 50 times more energy per square foot than a commercial office building.
The need for power is in tandem with the need for speed to market with new data centers. Hyperscalers and developers are projected to spend $7.6 trillion on AI data centers through 2031, according to Goldman Sachs.
That “force of capital” is the AI bus driving the search for consistent electricity flows, said Brandon Michalski, chief economist at MOCA Systems Inc., a Boston-based infrastructure technology firm.
Japan Declares Cybersecurity Emergency, Experts Nod to AI– me.pcmag.com News Source
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Japan has declared a cybersecurity emergency, following a spate of attacks on its companies in recent weeks. Some experts are already pointing the finger at AI.
Over 20 major firms, including convenience store chain Lawson and car rental operator Times Car, have reported attacks, according to The Financial Times, leading to the loss of tens of millions of pieces of customer data. This included 1.67 million customer email addresses from the booking system of JR East, the country’s largest rail operator.
Japanese cybersecurity minister Toshiharu Furukawa said the situation was “extremely critical” at a meeting at the National Cybersecurity Strategy Headquarters. Meanwhile, Masaaki Taira, head of the NCSH, called the situation an “emergency in cyberspace.”
Masaki Hiraoka, managing director for north-east Asia at cybersecurity group Blackpanda, told the FT that even if the recent spate of attacks hasn’t been explicitly linked to AI use, the technology is enabling hackers to carry out attacks that once required time-consuming investigations ahead of time.
“Smaller services that previously weren’t worth the effort could become viable targets,” he said.
Meanwhile, Nobuo Miwa, president of Tokyo-based cybersecurity firm S&J Corp, compared the recent attacks to “carpet bombing” in a statement to Reuters. Miwa also posited that AI tools may be allowing foreign hackers to overcome language barriers that might have previously made it harder to attack Japanese firms.
AI Is Getting Really Good at Messing With Cybercriminals– www.wired.com News Source
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Even as AI supercharges digital scamming and cybercrime, it’s also being recruited in the fight to protect potential victims. Governments around the world have consistently struggled to address the global crisis of online crime, grappling with the limitations of attempting to crack down on criminals beyond their borders. This has inspired alternative efforts, like using automation to attempt to go after scammers en masse—perhaps by spamming the spammers to squander their resources. Now, AI platforms are turning these types of experiments into real tools in the fight against cybercrime.
For the last two years, the Australian company Apate, named after the Greek goddess of deception, has been building a system that diverts phone scammers onto calls with AI bots that are trained to keep conversations going as long as possible without, of course, ever actually falling for the scam. The goal is to give scammers enough hope that they stay on the phone, while also collecting intelligence about the scams they’re running.
“What we really like to think is that we’re building the perfect victims for scammers,” Dali Kaafar, the founder and CEO of Apate, tells us. “A minute that a scammer is talking to a bot or an agent is a minute where you’re probably saving hundreds, if not thousands of possible people being reached out to by that exact same scammer,” he says, referencing the ability for scammers to use automated dialing tools.
Kaafar says Apate’s platform, which is used by banks and supported by telecom companies, has around 350,000 bots. They not only pick up calls, but also infiltrate scam chat groups online and respond to text messages with similar goals of frustrating scammers while collecting intelligence from them. He says the company has collected more than 250,000 pieces of information about fraudsters in real-time, from scam URLs to money mule accounts and bank details.
Rogue Anthropic AI agent gave police fake tip in unsolved murder case– www.bbc.co.uk News Source
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An artificial intelligence (AI) agent developed by Anthropic went rogue and sent US police a fake tip about an unsolved murder earlier this year, authorities have revealed.
The Philadelphia Police Department said the 18 July tip was “flagged as spam” and not passed on for investigation – but the force criticised the tech firm for taking more than two months to detect and report the breach.
It said the bogus tip came through a public website where people can share information on unsolved murders, and that the AI agent had claimed to have seen “someone matching the description”.
It is believed to be the first time an AI agent has sent fabricated information to authorities, but is the latest in a series of incidents involving rogue AI activity, including hacking systems or taking control of platforms.
Citing Anthropic, the police department said its AI agent had been running a test that involved interactions with randomly selected websites when it had sent the fake tip.
The company behind the Claude chatbot discovered the breach on 28 September, more than two months after the message had been sent, and shut down the automatic testing process that was behind it, police said.
But authorities were not notified for another nine days – on 7 October.
