It’s possible that I shall make an ass of myself. But in that case one can always get out of it with a little dialectic. I have, of course, so worded my proposition as to be right either way (K.Marx, Letter to F.Engels on the Indian Mutiny)
The Portuguese Judicial Police are reporting one of the country’s largest ever drug seizures completed aboard a Hong Kong-flagged containership while underway. The situation, however, has grown further complicated as a crewmember who had been arrested along with two stowaways was found dead hours later in a prison cell in Portugal.
The authorities reported they had been able to dismantle a criminal group dedicated to smuggling large quantities of drugs into Europe. It was part of an investigation shared at the Maritime Analysis and Operations Centre-Drugs, as well as working with the UK’s National Crime Agency and Spain’s Policia Nacional.
Working with the Portuguese Navy and Air Force, the operations intercepted the containership while it was underway at a position about 640 nautical miles off the coast of Portugal in the Atlantic.
The vessel in question, identified as Maersk Nokwanda, serves the banana-trade ports of Ecuador and the Colombian Pacific coast - one of the most prolific drug-smuggling regions globally. On her most recent voyage, Maersk Nokwanda called at Posorja and Machala, Ecuador; Buenaventura, Columbia; Balboa and Colon, Panama; then crossed the Atlantic on an itinerary that would ordinarily take her to Tangier Med and other Mediterranean ports.
The images showed the forces rappelling onto the vessel from helicopters. Once aboard, they reported finding two stowaways, which media reports identified as an Italian and a Colombian citizens. The two were reported to be undocumented and were believed to be involved in the smuggling operation, and were arrested. The police also seized objects for navigating, transporting the drugs, and throwing them overboard.
Searching the vessel, the police uncovered five tons of cocaine in void spaces. They also interviewed the crew and took one person, reported to be an Indian citizen, into custody. The Navy escorted the containership to the port of Sines where the vessel docked on August 4. The cocaine was offloaded.
The head of the police’s drug trafficking unit confirmed at a press conference on Wednesday, August 5, that the crewmember had been discovered hanging in his cell early on Wednesday morning. He was being detained alone in a cell. They pronounced him deceased and are investigating the circumstances of his death. Media reports said he was believed to have been the person with the most information about the smuggling operation.
European authorities have increased their efforts to intercept the large quantities of drugs being smuggled into Europe. Portugal has reportedly already confiscated approximately 28 tonnes in 2026, which surpasses the country’s total for all of 2025.
The Judicial Police suspect that the Maersk Nokwanda smugglers intended to conduct a high-seas "drop-off" to transfer the drugs to fast-boat operators, who would then move the illicit cargo to the littorals of the Spanish or Portuguese coasts. This transport model is increasingly popular for traffickerslooking to avoid heightened scrutiny at larger seaports, as it avoids all of the security measures that accompany port infrastructure.
These high-seas boat transfers sometimes get disrupted or go awry, leaving the cargo to float at sea or wash up on public beaches. Just last week, Portugal's Maritime Police found and seized two tonnes of abandoned cocaine near the Troia Peninsula.
Friday, August 07, 2026
A new way to build safer, more sustainable skyscrapers
Imperial College London and Arup pioneer a new approach to designing tall buildings that uses the building's own weight to reduce movement in high winds and earthquakes.
Credit: Miguel Martinez Paneda, Imperial College London
Key findings:
Up to 70% less movement in high winds than conventional tower design.
More than 50% lower structural loads, creating opportunities to reduce steel and concrete use.
One solution for wind and earthquakes, reducing earthquake displacements by 42% on average.
Extreme events continue to expose the vulnerability of our towns and cities. As urban populations grow and the climate changes, the need for buildings that protect people, recover quickly and use resources more efficiently has never been clearer.
Meeting these challenges has traditionally relied on designing tall buildings to remain as rigid as possible, resisting wind- and earthquake-induced motions through increased structural sizes and material usage. Researchers and engineers from Imperial College London and Arup have challenged that long-held assumption, developing a new approach that uses a building’s own mass to reduce movement in high winds and earthquakes. Instead of trying to eliminate movement, it accepts that buildings will move and puts that movement to work to improve the building’s performance. Tested through wind tunnel experiments and earthquake simulations, the approach reduced wind-induced accelerations and was shown to result in safer, more resilient and more sustainable tall buildings.
Recently highlighted by Nature, the research was led by Imperial’s Miguel Martínez Pañeda (Department of Civil and Environmental Engineering and Arup), with Professor Ahmed Y Elghazouli (Department of Civil and Environmental Engineering) working alongside Dr Kevin Gouder (Department of Aeronautics) and industry colleague Dr William Algaard (Arup).
Martínez Pañeda, PhD Researcher in the Department of Civil and Environmental Engineering and Principal Structural Engineering at Arup, said: "Movement is not automatically a flaw. Rather than adding extra weight or making the structure bigger to keep a building still, the approach turns a building’s own mass into a design asset, improving comfort, safety and material efficiency in both high winds and earthquakes."
Turning movement into a design asset
Tall buildings naturally sway in strong winds and earthquakes. A common solution to control its movement under wind is adding a tuned mass damper: a very large weight, often hundreds of tonnes, suspended near the top of a tower and designed to move against the building's motion. These systems are effective at improving occupant comfort in the wind, but they take up valuable floor space, require substantial reinforcement and do little to reduce the forces a building experiences during an earthquake. Designers often need separate systems to improve seismic performance.
The researchers instead asked a different question: what if part of the building itself became the damper? Their solution separates a group of usable floors near the top of the building from its central core, connecting them with springs and dampers. Those floors remain fully usable, but can move slightly and independently, using their own weight to absorb energy and control the building's motion in both strong winds and earthquakes.
Putting the idea to the test
To prove the concept, the team built a 1:300 scale model of a 300-metre tower and tested it in the National Wind Tunnel Facility’s 10ft x 5ft wind tunnel at Imperial’s Department of Aeronautics (one of few facilities in the world equipped for this kind of testing) alongside dynamic seismic tests in the Department of Civil and Environmental Engineering’s Structures Laboratory.
The results showed the system dramatically reduced how much the building moved. Peak accelerations fell by up to 71% and base moments by more than 50%, compared with a conventional rigid design. Under simulated earthquakes, top displacements dropped by 42% on average, while movement in the movable floors fell by up to 74%. The controlled movement between the floors and the core remained minimal, and it was proven that occupants would not notice the movement under normal conditions.
Dr Kevin Gouder, Advanced Research Fellow in the Department of Aeronautics, said: “These tests gave us the confidence that the concept isn’t just theoretically sound, it's mechanically robust and buildable with technology that already exists. Seeing the model in the tunnel respond exactly as the numerical models predicted was a real turning point for the project.”
One solution for two hazards
Because the system responds to both wind and earthquakes, it removes the need for separate damping systems altogether, an approach that becomes increasingly valuable as more tall buildings are constructed in regions exposed to both hazards.
Cities including Hong Kong, Manila, Miami and Taipei regularly experience typhoons or hurricanes, while many of the world's fastest-growing urban centres across Latin America and East and Southeast Asia are also located in areas of high seismic risk. The need for more resilient tall buildings has been highlighted by recent disasters. In March 2025, a magnitude 7.7 earthquake that struck Myanmar caused a 33-storey tower under construction in Bangkok to collapse.
Since the approach relies on established construction technologies, including springs, dampers and bearings already widely used in buildings, the researchers believe it could be adopted without adding significant cost or complexity. Reducing the forces a building must resist also means less concrete and steel are needed in its core, columns and foundations, cutting both cost and embodied carbon.
The team's next steps include larger-scale testing of a movable module and a pilot application on a real building design. The project marks the culmination of almost a decade of work. The idea first emerged from Martínez Pañeda's Imperial Master's thesis in 2016 before developing into an international research programme involving Imperial and Arup.
Brian Hie and Aditi Merchant examine a protein structure generated by Evo 2, an AI tool that can suggest genome designs. Lab tests of Evo 2’s designs for an E. coli killer exceeded expectations. | Andrew Brodhead
In science, the suffix “phage” means to devour. Thus, the name bacteriophage might conjure images of tiny creatures that “eat” bacteria. While that conception isn’t 100 percent scientifically accurate, bacteriophages are lethal bacteria killers nonetheless, and scientists are excited about engineering phage DNA as a path to new antibiotics.
And so it is that chemical engineer Brian Hie and bioengineering graduate student Samuel King came to study bacteriophage ΦX174 (pronounced “FYE-ex-1-7-4”). Hie, assistant professor of chemical engineering and the Dieter Schwarz Foundation Stanford Data Science Faculty Fellow, created Evo 2, a generative AI model that solves complex biological challenges by suggesting new DNA sequences. Given just the barest snippet of ΦX174 DNA, Evo 2 will go to work writing novel genomes of new phages that kill bacteria – in this case, the microbe E. coli, which can be deadly when infections turn serious.
Until recently, Evo 2 was mostly confined to the computer, but in a new paper, Hie and King have transitioned it to a real-world lab. Based on genomes written by Evo 2, they have synthesized nearly 300 novel phages and tested them for effectiveness against E. coli. They later narrowed that list to a relative handful of 16 exceptionally good E. coli-killing phages.
“In this case, we wanted the model to generate the entire genome end-to-end in a single left-to-right pass. We didn’t add anything,” Hie explains of the process that produced thousands of options for his team. “In lab tests, a few of Evo’s suggestions had higher fitness than the native ΦX174.”
Resistance-resistant antibiotics
Hie and King chose ΦX174 because its entire genome is less than 6,000 base pairs long. Compared to the 3 billion base pairs of the human genome, the ΦX174 genome is relatively simple. But its ability to kill bacteria nonetheless makes it an attractive test case for Evo 2’s design powers.
Why Hie would want or need more than one E. coli-targeting phage comes down to bacterial resistance, a common weakness of modern antibiotics. Eventually, after years of heavy use, bacteria evolve immunity to the medications that kill them. The antibiotics lose effectiveness.
“If the bacteria gain resistance to a single phage, it’s game over for the medication,” Hie said. “But if you have multiple genetically distinct phages in a mixture, it would be harder for the bacteria to develop resistance to the entire cocktail.”
Thus, this work might lead to a resistance-resistant antibiotic. Scientists imagine cocktails of genetically diverse bacteriophages working in tandem to counter microbial immunity. Similar approaches might be used to develop phages that target other harmful bacteria, such as tuberculosis, methicillin-resistant Staphylococcus aureus (MRSA), and Pseudomonas aeruginosa, a bacterium that is a leading cause of medically resistant infections acquired in hospitals, among others.
“We have a proof of concept in the paper, where we show that this cocktail of 16 phages rapidly overcomes resistance in E. coli that is immune to native ΦX174,” Hie said.
New tools
The technical challenges of designing entire genomes – creating them nucleotide by nucleotide and then transferring them into bacteria – are neither easy nor inexpensive. King, first author on the paper, led the project.
As short as the ΦX174 genome is, Hie explains, it is extraordinarily difficult to stare at a 5,400-character string and make sense of it gene-by-gene. King developed a computational framework to help the researchers evaluate the genomes and to narrow down the list of candidates from thousands to only those the team deemed most interesting for further exploration.
“One of the main parts of the design framework was figuring out what traits the genomes should have based on ΦX174 and related phages,” King explains. “The framework involved several key steps: generating genomes using Evo 2, evaluating options based on the design criteria, selecting optimal candidates, synthesizing them chemically, and then testing them in the lab to see which genomes worked best.”
“With the cost of DNA synthesis still quite high,” Hie explains, “Samuel’s framework helped us focus only on the most viable alternatives.”
Open source, open doors
As a proof of concept, Evo 2 has exceeded expectations. Sensing its potential in medical and biological sciences, Hie offers Evo 2 open source and free of charge. Anyone can download Evo 2 and design new genomes themselves.
The free availability of the tool has naturally raised discussions about safety and security. Hie is motivated by the tool’s vast potential benefits to health and humanity, and said that open availability is essential to expediting research and real-world results. While he acknowledges that modified versions of the tool could be used by bad actors, he notes that existing pathogens present a greater risk than potential AI designs because they are easier to access and produce and, unlike with AI, safety checks can’t be built into the process of natural evolution. In fact, he adds, AI-enabled tools like Evo 2 provide humans a powerful advantage against naturally occurring pandemics and improved defense options against man-made biological threats.
Next up, Hie is working with other researchers at Stanford and beyond to extend Evo 2’s reach while pursuing his own research to create other new bacteriophages. He is also looking at longer and more complex DNA, possibly even of small bacterial genomes that might lead to beneficial engineered microbes that produce useful chemicals, medicines, fuels, and more.
“The biggest open questions for me,” Hie said, anticipating future research, “are how do we get greater genetic novelty and how do we get greater controllability of the outcomes?”
“One of the most rewarding parts of this project is the creativity Evo 2 allows,” King said. “New doors in science are now open because of what we can do with these models.”
For more information
Contributing authors include Stanford graduate students Claudia L. Driscoll, David B. Li, Daniel Guo, Aditi T. Merchant, and Garyk Brixi; and Max E. Wilkinson of the Broad Institute of MIT and Harvard and Memorial Sloan Kettering Cancer Center.
This research received funding from the Arc Institute, the National Science Foundation, the Knight-Hennessy Graduate Scholarship Fund, the Fannie and John Hertz Foundation, and the Stanford Institute for Human-Centered AI.
UCF researcher to support DOE project using AI to accelerate scientific discovery
Assistant Professor Haonan Ling will explore virtual solutions to biomanufacturing for the Department of Energy’s Genesis Mission, which aims to strengthen America’s energy industry and national security
Assistant Professor of Mechanical and Aerospace Engineering Haonan Ling's contributions to Department of Energy's Genesis Mission will address problems with biomanufacturing by developing an AI digital twin (virtual replication). (Photo by Antoine Hart)
Scientific breakthroughs often require years of experimentation, testing and refinement before researchers can answer some of society’s most complex questions. To explore how artificial intelligence can help accelerate that process, Assistant Professor of Mechanical and Aerospace Engineering Haonan Ling is joining the U.S. Department of Energy’s Genesis Mission.
The nationwide initiative encourages interdisciplinary teams to develop new AI models and research workflows capable of addressing national challenges across fields such as advanced manufacturing, biotechnology, critical materials, energy and quantum information.
“The Genesis Mission harnesses the collective strengths of the nation’s leading institutions across academia, industry, and government to accelerate the pace of discovery,” says Winston Schoenfeld, UCF vice president for research and innovation. “UCF’s participation reflects the expertise of our researchers and talented students, whose contributions will help shape AI-enabled scientific workflows and transform technological advances into real-world solutions that fuel American competitiveness.”
A New Approach to Creating Fuels and Chemicals
As interdisciplinary scientific challenges become increasingly data-intensive, applying human ingenuity to advanced technologies creates possibilities to solve long-standing industry issues.
Ling’s contribution to the Genesis Mission will aim to address problems with biomanufacturing by developing an AI digital twin (virtual replication). This digital twin predicts and optimizes bioprocess performance, enabling improved process monitoring, decision-making, and scale-up.
The project will also provide opportunities for UCF researchers at different stages of their careers to contribute to the work. Pinzhen Lin, who will begin a doctoral degree at UCF’s College of Optics and Photonics in Fall 2026, will join Ling’s research group and lead development of the project’s real-time sensor, including its characterization and performance benchmarking. Jirui Fu ’24PhD, a UCF mechanical engineering doctoral graduate and postdoctoral scholar in the College of Engineering and Computer Science, will also assist with the project.
“The challenge is that conventionally scaling up biomanufacturing is slow and prone to failure, creating a need for smarter tools to accelerate development,” Ling says. “If successful, this project could significantly accelerate the development and deployment of sustainable biomanufacturing for fuels and chemicals, making the process faster, cheaper and less risky.”
With industry-academic collaboration at the core of the Genesis Mission, Ling is working on the project with Kansas State University Assistant Professor Yian Chen, as well as the National Laboratory of the Rockies researchers Ajinkya Pal, Jason DesVeaux and Evan Komp.
A Mission With Many Benefits
Although the Genesis Mission is focused on accelerating scientific discovery, Ling believes the work has the potential to create benefits that extend beyond the research community.
“The AI digital twin framework developed here has strong potential as a commercial platform that can be adopted across a wide range of industries, from energy to materials,” Ling says. “More broadly, it could lower the barriers for industrial partners to adopt bio-based processes, helping drive the transition toward a more sustainable economy.”
For Ling, the research also represents an opportunity to see emerging technologies applied to real-world challenges.
“As an early-career researcher, I feel very fortunate to lead and participate in a mission of this scale,” Ling says. “What excites me most is the opportunity to apply this technology to solve real-world problems, and to see how it can be integrated with the rapidly advancing field of AI.”
This project will be supported by the U.S. Department of Energy Office of Science through the Genesis Mission, a Transforming Science and Energy with AI initiative.
World Bank warns developing countries to embrace AI or be left behind
The World Bank has called for governments in developing countries to embrace the use of AI to achieve better governance outcomes – Copyright AFP Martin LELIEVRE
The World Bank on Tuesday called on developing countries to embrace artificial intelligence technology tools to deliver better governance outcomes, warning that they risked being left behind if they failed to do so.
“AI has thrown developing economies a lifeline, and they should seize it,” Indermit Gill, chief economist of the World Bank Group, said as the organization launched its annual World Development Report.
“They do not need large models or big data centers to reap its benefits,” he added, advocating for the adaptation of lower-cost AI tools to local conditions to deliver results in the health, education, justice and agricultural sectors.
Advanced AI models — largely developed in the United States and China — offer the ability to quickly analyze data and automate many tasks that otherwise take skilled humans longer to do.
These AI models, however, require huge data centers and large amounts of complex computing power, using massive amounts of electricity and water — with implications for climate change.
“Developing economies today are in the midst of their weakest average growth performance in three decades,” said a World Bank statement accompanying the report.
“AI could significantly boost that performance before the end of the 2020s while delivering tangible benefits to people.”
The report calls for countries to use AI to “help extend otherwise costly medical, legal, educational, and agricultural services to underserved billions — doing in a decade what might otherwise take a century.”
– Shock after shock –
Lower-income countries have struggled through the 2020s, hit by a series of successive shocks that saw the World Bank earlier this year dub it a “lost decade” for their economic growth.
The Bank has lowered its 2026 global growth forecast to its lowest level since the pandemic, with the economic fallout of the Iran war battering countries around the world.
The shock has hit low-income and developing countries hardest, with Asia the worst-affected region.
The Bank’s new report advocates for developing countries to start working with localized AI tools and solutions now, and to invest in electricity generation and distribution; expand access to computing power; and improve the availability of local data.
“The window to get this right is narrow,” said Gaurav Nayyar, director of the report.
“AI presents a once-in-a-lifetime opportunity to solve problems that have resisted solutions for generations,” he added.
For the 6.8 billion people — 83 percent of humanity — who live in low-income and developing countries, AI tools will need to be adapted to meet their needs.
The report shares examples of AI applications in governance, such as to increase diabetes screening volumes in Bangladesh, or in reducing costs for Indian farmers through advanced weather forecasts.
The solutions, the report stresses, will need to meet people where they are.
“For example, AI solutions will need to be delivered through voice calls on basic mobile phones for those who cannot read or afford smartphones,” it says.
“Simply importing an AI model does not mean it will work well locally.”
– Stark warning –
The report calls for policymakers to also build public trust as they expand AI use.
“Improved public services and better learning outcomes in schools will reinforce trust — but if AI embeds bias in government decisions or erodes data privacy, that trust will be difficult to recover,” said the statement.
The report delivers a stark warning, too: “AI could widen gaps between countries, increase inequality within them, concentrate market power, weaken trust in public institutions, and create new risks for safety, rights, and social cohesion.”
And while risks to employment in developing countries are low at the moment, it warns that in the long run AI tools could cut off economic mobility by eliminating many of the middle-class jobs that enable it.
The report was written with the aid of several of the world’s most advanced AI tools, including offerings from OpenAI, DeepSeek, Google and Anthropic, according to a disclosure.
Trump admin to review ‘closed’ AI models before release: reports
Founded in San Francisco in 2015 as a nonprofit research lab by Altman, Elon Musk and others, OpenAI burst into the mainstream with the launch of ChatGPT in 2022 – Copyright AFP MARCO BERTORELLO
The Trump administration on Tuesday met with tech leaders to finalize a security review process for advanced AI models before their release, though it will apply only to “closed” models, US media reported.
However, it remains unclear when — or if — the White House will release the details of the process or how it will be implemented and enforced.
According to Axios, the review process will only apply to closed models that are tightly controlled by their developers. Major closed model developers include OpenAI, Anthropic and Google.
By contrast, Meta and Nvidia are developing “open” models that can be downloaded and updated directly by users. Open models are made by competitors in China, including DeepSeek and Moonshot, as well as Mistral in France.
Tuesday’s meeting at the White House reportedly included OpenAI, Anthropic, Google, Nvidia, Microsoft and Meta.
The move to exempt open models is likely aimed at helping the United States stay competitive with China.
However, there is a “deeper problem,” according to Martijn Rasser, vice president for technology at the Special Competitive Studies Project, a think tank founded and chaired by former Google chief executive Eric Schmidt.
“The United States still lacks a statutory, predictable process for evaluating the security of frontier AI models,” Rasser wrote in a LinkedIn post on Tuesday, adding that a voluntary framework applying only to closed models “concentrates the uncertainty” on a handful of companies.
– Rogue models –
The rapid advancement of artificial intelligence has created a sense of urgency in the United States to develop regulations that mitigate and prevent risks associated with the technology.
US President Donald Trump (C) and OpenAI CEO Sam Altman (L) attend an AI leaders’ meeting during the G7 summit in Evian, France, on June 17, 2026 – Copyright AFP Ludovic MARIN
However, the Trump administration has favored a light-touch, deregulatory approach to most industries, including tech.
In June, Trump signed an executive order that called for major AI developers to submit new models to the government for review 30 days before they are publicly released. It also gave the federal government a 60-day deadline to finalize a proposed framework.
That deadline passed on August 1 without any public announcement.
Recent cyberattacks carried out autonomously by software from OpenAI and Anthropic have raised concerns about the capabilities of advanced AI models.
On July 21, OpenAI confirmed that its software escaped a testing environment and attacked another company, Hugging Face. About a week later, it said the models had also targeted three additional companies.
Then on July 30, Anthropic revealed that it also found three incidents where AI models being tested “gained unauthorized access” to unnamed organizations.
Trump urged a balanced approach that addresses AI security risks while maintaining US competitiveness.
“We have to be careful in both ways. We don’t want to restrict them where all of a sudden we come in second to China,” he told reporters in the Oval Office last week.
In recent months, DeepSeek and Moonshot have developed their own powerful new models that have reignited fears about US competitiveness in AI.
Taiwan probes 17 China-funded firms over high-tech talent poaching
Chips, also known as semiconductors, are vital for every electronic device, from smartphones to electric cars, and control of supply chains has become a major priority for the world’s biggest trading blocs – Copyright AFP/File JENS SCHLUETER
Taiwanese investigators said Wednesday they have raided dozens of locations as part of a probe into 17 Chinese-funded companies suspected of trying to “illegally” poach Taiwan’s high-tech talent to erode the island’s competitive edge.
Taiwan is a powerhouse in the global semiconductor industry, producing nearly all of the most advanced chips for companies including Nvidia and Apple.
China is racing to develop the advanced chips used to power artificial intelligence systems, as it faces export restrictions imposed by the United States.
More than 300 investigators searched 64 locations and interviewed 114 people in recent weeks, the Ministry of Justice Investigation Bureau said in a statement.
Investigators said the companies allegedly sought to conceal the identity of their Chinese financial backers while establishing “unauthorised” operations or “illegally” recruiting talent.
As AI competition intensifies, Taiwanese firms face the “challenge of having their core high-tech talent targeted and recruited by ‘Chinese’ companies, leading to the loss of their core competitive advantages,” the statement said.
Taiwan has long accused China of carrying out espionage activities on the island, which Beijing claims is part of its territory and has threatened to seize by force.
Last month, Taiwanese prosecutors charged a former TSMC employee with stealing the chipmaking giant’s “core” technology and attempting to leak it to China.
Prosecutors also have detained seven people, including an Nvidia worker, in a separate case involving the alleged smuggling of the US tech giant’s AI chips to China.
When rogue AI launches a cyberattack, who is legally responsible?
In July 2026, two OpenAI models undergoing testing left their confined environment — a scenario the developers had not anticipated – Copyright AFP Martin LELIEVRE
Recent cyberattacks carried out autonomously by two rogue OpenAI artificial intelligence models raises an untested legal question: who is responsible when AI acts on its own?
On Friday, Clement Delangue, head of the Hugging Face platform targeted by the intrusions, said there should be a way to “keep the companies that are doing some mistakes leading to (cyberattacks) accountable,” while saying his company would not be pursuing legal action at this time.
In mid-July, two OpenAI models undergoing testing left their confined environment — a scenario the developers had not anticipated — and ventured onto the internet, where they attacked Hugging Face, an AI model-hosting platform.
Delangue also mentioned Anthropic, which revealed Thursday that three of its models had broken into three different websites, also during testing.
– Negligence route –
Under US civil and criminal law, unauthorized access to a computer system is an offense.
“If a human OpenAI employee had broken into Hugging Face’s systems… OpenAI would be liable for the employee’s wrongful conduct,” University of Houston law professor Gabriel Weil wrote in an opinion piece for the Transformer newsletter.
“When an AI agent does it, the law treats it very differently, at least for now,” he added.
Matthew Tokson, a University of Utah law professor who focuses on new technologies, had a similar view, saying “we haven’t had to grapple with that being formed in anything that’s not human, and I don’t think courts are likely to be there yet.”
The question remains open, however, when it comes to the company that created the model.
“Does ‘we didn’t tell the AI to do that’ end the liability question?” asked Rob T. Lee, head of research at the SANS cybersecurity training institute, in a post on X.
University of Washington law professor Ryan Calo does not believe a criminal case would be likely to succeed.
“The company or individual would have to be at least reckless,” he said, explaining they would “be substantially certain the crime would occur and build or prompt the system anyway.”
Experts see greater potential for a civil — rather than criminal — case, where the burden of proof is lower.
“Some people think that AI companies should be strictly liable if an AI agent that they deploy totally breaks out, causes damages,” Tokson explained.
“Others would prefer to do like a negligence assessment and see if they were actually negligent or if this was just sort of an unavoidable accident or something that couldn’t possibly have been foreseen,” he added.
In such cases there is a standard of care in product design that judges or juries can use to make a ruling, Tokson continued.
“It’s all a bit unwritten because we’ve never had an AI agent break out of its sandbox and hack other people on the internet before,” he said.
OpenAI could rely on the lack of legal precedent if it faced a lawsuit, but those that follow will no longer be able to do so, Calo warned.
Proving that a similar incident could have been anticipated “shouldn’t be so hard now that it’s begun to happen.”
AI keeps consumer prices high in ‘RAMaggedon’ chip crunch
Print-outs of articles about the global memory chip shortage are pinned beside a price list at a Hong Kong computer shop, offering an explanation to confused customers feeling the pinch.
Price rises for goods such as laptops and smartphones, with cars potentially next, have been an unwelcome side-effect of the artificial intelligence gold rush — and the squeeze is far from over.
Samsung Electronics’ chief financial officer said this week shortages of microchips that store digital data will likely deepen in 2027 and stay tight through 2028.
The crunch has been nicknamed “RAMaggedon” after the components called RAM, or “random-access memory”.
It is caused as profit-hungry chipmakers pivot to producing high-bandwidth memory (HBM) — a more advanced type of computer memory in huge demand to help train and run AI tools.
The articles on display at In-Technology Services — one of many compact vendors crammed into Hong Kong’s Wan Chai Computer Centre — are to inform customers who “don’t know what happened,” manager Wade Lam told AFP.
The centre’s shops sell tech equipment of all sorts, from computer parts to gadgets and games consoles.
Ken Tam, manager of Videocom Computer, which specialises in custom-built PCs, said business has halved since price rises began in September.
Sixteen gigabytes of RAM used to cost HK$300-400 ($40-50) but the price has now hit HK$1,500, he said.
“When it suddenly gets so expensive, customers have a psychological barrier,” Tam told AFP.
“If they need it, they will buy it,” but otherwise they will wait, or “lower their standards” and buy a less high-performing memory chip, he said.
– Chinese competition –
Analyst Ellie Wang at the Taiwan-based market research firm TrendForce said memory prices for PCs and smartphones were up around five to six times compared to a year ago.
The AI boom has brought humungous profits and share price jumps to the world’s top three memory chip makers: South Korea’s Samsung Electronics and SK hynix, along with US giant Micron.
In fourth place is ChangXin Memory Technologies (CXMT), which became mainland China’s most valuable company on Monday when it made its market debut in Shanghai — another sign of how red-hot the sector has become.
CXMT, as a relative newcomer, “remains in a follower position regarding leading-edge technologies”, James Zhao, senior principal analyst at Omdia, told AFP.
HBM is used in data centre servers to support other powerful chips — such as those made by US titan Nvidia — that execute the dizzyingly complex calculations of AI systems.
But when it comes to conventional RAM, and a type for computers called DRAM, “the current supply-constrained market environment” could bring CXMT “late-mover advantages”, he said.
At a shopping centre in a different part of Hong Kong, customer Henry Wong, an investment banker, said he had chosen to upgrade the RAM in an older laptop instead of buying a new one with even better specs.
“After upgrading the memory, I found it ran really smoothly, and I stopped wanting to buy a new computer,” he told AFP.
– ‘Bubble’ –
Automakers say they are facing rising costs for in-vehicle computer systems, which could also soon push up the price of new vehicles.
In Tokyo’s tech hub of Akihabara, Charles Brousse, a 30-year-old graphic designer and custom PC builder from Belgium, said prices for RAM, graphics cards and motherboards have hit “ridiculous levels”.
For his “PC & Chill” service, Brousse does not buy parts to pre-build machines — as it is too expensive — but he requires clients to purchase their own that he assembles.
The chip shortage is pushing people to buy cheaper laptops than desktops, which can last up to a decade, said Brousse, in Tokyo on his honeymoon.
“I’m not sure that’s a good thing; people end up buying products with shorter lifespans, which fuels a cycle of consumption.”
Brousse added that the fact it is driven by the “speculative bubble” of AI is also frustrating, “because I’m a graphic designer by trade, so AI has a real impact on my profession.”
Google rolls back new satellite image AI tool after backlash
This April 18, 2017 file photo shows people viewing a Google Earth map of Paris, France at an event at New York’s Whitney Museum of Art – Copyright GETTY IMAGES NORTH AMERICA/AFP SPENCER PLATT
Google rolled back Friday a new feature allowing Google Earth users to generate AI visualizations on top of the service’s satellite imagery, following a furious backlash from researchers and open-source intelligence experts about the potential for disinformation.
“We’ve seen geospatial professionals using this feature for a range of useful purposes, however we’ve also seen people sharing screenshots of generated imagery that appear to violate our policies,” a Google spokesperson said in a statement to AFP. “So we’re rolling back this feature in Google Earth while we work on implementing stronger guardrails.”
“We know that people uniquely trust Google Earth for a reliable view of the world,” the statement added.
The “create image” tool, unveiled Thursday, had integrated Google’s Nano Banana 2 image-generation technology into Google Earth, letting users zoom into locations and build pictures in seconds based on the program’s satellite, aerial and 3D-mapping data.
Google had described it as a way to “visualize history, create real estate plans and more.”
But disinformation researchers warned that it could enable bad actors to misuse Google Earth — a key resource for fact-checking and verification — to create realistic geospatial fakes.
“Google spent 20 years building the reference the world checks against,” digital investigations expert Henk Van Ess wrote in one widely shared post on Substack. “Today it added a button that makes things up.”
Brady Africk, a research analyst at the American Enterprise Institute specializing in satellite imagery analysis, told AFP the Google Earth update would have made it “easier to generate convincing fake satellite imagery that can spread quickly online and mislead the public.”
Such fakes “erode public trust in satellite imagery, and make the jobs of journalists and researchers more difficult,” he said.
– ‘Irrevocably damaged overnight’ –
As the critiques piled up, Google had said on X that the images created with the feature included SynthID digital watermarks, invisible markers embedded in media generated using the company’s artificial intelligence tools.
“We take misinformation seriously,” the company wrote, linking to an AI policy that instructs users against “misinformation, misrepresentation or misleading activities.”
AFP’s tests of the feature on Friday were able to fabricate satellite images that could have had serious global consequences: an explosion in Paris, a nuclear site in Iran, a bomb crater in Russia and an Islamic State group training ground in Syria.
The tool also fulfilled prompts to visualize other fake scenes, including floods across Bangladesh, a migrant caravan camped at the US-Mexico border and a suspicious warehouse holding vans in Georgia — one of several states US President Donald Trump has falsely accused of widespread election fraud.
The “create image” button no longer appeared within Google Earth after Google paused its use.
Similar fakes have previously had real-world impacts. In 2023, an AI image depicting an explosion at the Pentagon briefly rattled the markets.
Early in the US war with Iran, an AI-altered satellite image depicting a destroyed US military base garnered millions of views across platforms.
Among the groups that called for Google to reverse its decision was the London-based Centre for Information Resilience, whose executive director Ross Burley told AFP the feature was “irresponsible.”
“Trust in satellite imagery has taken decades to build and could be irrevocably damaged overnight,” Burley said.
GeoConfirmed, a volunteer-driven open-source intelligence project that verifies visuals from conflicts around the globe, had also urged Google to reconsider.
“We are already observing individuals exploiting the new Google Earth web tool to make military positions, relabel buildings as schools, and experiment with manipulating the information environment,” the group wrote on X, before Google announced it was rolling back the feature.
“The primary, and perhaps only, practical use of this tool appears to be the creation and dissemination of mis- and disinformation.”
NSF CAREER Award will help University of Illinois researcher improve the quality of AI training data
University of Illinois School of Information Sciences Assistant Professor Jiaqi Ma's project will develop new tools to understand how training data affects large AI systems
University of Illinois School of Information Sciences
Assistant Professor Jiaqi Ma has received a National Science Foundation (NSF) CAREER award to develop new tools to understand how individual components of training data affect the behavior of large artificial intelligence systems. The highly selective CAREER award recognizes early-career faculty with the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization. Ma received a five-year, $660,307 grant for his project, "Data Attribution and Curation for Web-Scale AI Systems," which seeks to improve data attribution, a family of methods that estimate how training examples influence model behavior.
AI systems increasingly influence how people search for information, receive recommendations, learn, work, and create. The quality of these systems depends heavily on the data used to train them. However, modern training data is often enormous, noisy, and constantly changing, because it is drawn from many sources. Poorly understood data can reduce accuracy, amplify harmful information, weaken reasoning and/or make it difficult to recognize the value of content in AI systems.
"Data is one of the most important ingredients in modern AI," Ma said, "but we still have a limited understanding of how individual training examples shape a model's behavior."
Ma hopes to develop tools to help researchers and practitioners decide what data to keep, remove, prioritize, or compensate for. By making data curation more principled and transparent, the project has the potential to improve the performance, reliability, and safety of widely used technologies such as language models and recommendation systems.
"This project aims to make those influences measurable, even in large and continuously evolving AI systems," he said. "Better data attribution can help us build models that are more accurate, reliable, and safe, while also creating a more transparent basis for recognizing and compensating the people whose content contributes to these systems."
The project will also create public educational resources, open-source software, conference tutorials, course modules, and research opportunities for graduate, undergraduate, and pre-college students, helping widen access to data-centered AI research and training.
Ma's research interests lie in the broad area of machine learning and AI, with recent focuses on the data foundations of AI, including three complementary aspects: 1) understanding how training data impact AI models (data attribution); 2) developing data-centric algorithms that improve the quality and safety of training data (data curation and synthetic data generation); and 3) studying how data mediate the societal impact of AI (data compensation and machine unlearning). His work has been recognized with a Best Paper Award from the Workshop on Navigating and Addressing Data Problems for Foundation Models at the 2024 International Conference on Learning Representations, and a New Faculty Highlight at the Association for the Advancement of Artificial Intelligence 2025.
He earned his PhD from the University of Michigan and worked as a postdoctoral researcher at Harvard University.
Finding new osteoarthritis medicines via AI and genetics
Credit: Kristan Jacobsen Photography / University of Utah Health
Key points:
Researchers combined family genetic studies with AI molecular biology to find a new candidate drug to treat osteoarthritis.
In cells in a dish, the new compound prevents OA-associated changes and promotes cell health.
The drug has not yet been tested in people or animals.
IMPACT: The new drug is a starting point for therapies that treat OA at its source.
Osteoarthritis (OA) is a chronic, painful joint disease and a leading cause of disability. Despite its prevalence, therapies for osteoarthritis are limited and focus on symptom management. Now, researchers are combining genetic studies of Utah families with AI-based molecular biology tools to find new medications that may ultimately help treat OA at its source.
One such new drug appears to promote joint health and reduce inflammation-related genes in a model of osteoarthritis based on cells in a dish. While it has yet to be tested for safety and efficacy in a living organism, the new compound provides a starting point for innovative OA therapies.
“Our goal really comes down to treating patients,” says Michael Jurynec, PhD, associate professor of orthopedic surgery at University of Utah Health and the senior author on a paper describing the new results. “Right now, the only thing we can do for OA is joint replacement or pain medication. So, if we can find something that slows down the disease process, giving people an extra 10 or 20 years of pain-free living, that’s a huge advancement.”
Using AI tools, the researchers were able to narrow a pool of half a million drug candidates down to six in a matter of weeks.
Previous human genetics research with Utah families had found that, for several forms of highly hereditary OA, changes in a gene called WNK2 underlie the disease’s progression. For these families, WNK2 overactivity in joint cells triggers processes associated with inflammation, which suggests that blocking WNK2 could effectively treat arthritis.
The scientists used an AI-based tool to predict the physical structure of the WNK2 protein, and then computationally simulated how hundreds of thousands of individual chemical compounds would interact with it. This gave them a “shortlist” of just over 50 compounds predicted to bind to WNK2 and reduce its activity. Visual inspection of the shortlist narrowed down the candidate pool to six compounds.
Promisingly, one of the candidate drugs, M04, appeared to prevent osteoarthritis-related changes and make cells healthier in an established cell-based model of osteoarthritis, in which human cartilage cells are exposed to conditions that trigger inflammation.
“We treated cells with this new compound we discovered, and it inhibited many, many genes that are associated with osteoarthritis,” Jurynec says. “Not only did it inhibit these inflammatory factors, but it actually increased expression of genes that promote the health of these cells.”
This suggests that the drug or a derivative of it could help treat OA.
Next steps
The new compound is a valuable starting point, but much more work lies ahead to develop it into a safe and effective drug, Jurynec emphasizes. While computational evaluation and in vitro studies suggest that M04 is a promising OA drug, its toxicity and side effects have not been fully tested, and researchers don’t know whether it will be safe to use in people.
The team is working to address these concerns through a collaboration with the University of Utah Therapeutics Accelerator Hub, working together to develop improved derivatives of the drug. M04 will also need to be comprehensively tested for safety and efficacy in animal models before clinical trials are possible. But as early as it is, the new compound provides a crucial starting point for development of better OA drugs.
“This is really the beginning of the study,” Jurynec says. “It’s not the end. We don’t have a drug that’s going to cure OA yet. But this is very promising.”
This research was funded by the Skaggs Foundation for Research, the Utah Genome Project, and the Arthritis National Research Foundation. Content is solely the responsibility of the authors and does not necessarily represent the official views of the funding organizations.
Jurynec and first author Shivakumar Veerabhadraiah have filed a U.S. Patent Application (No. 19/672,326) titled ‘Compounds That Inhibit WNK2 Activity And Methods For Treating Osteoarthritis.’
Identification and Validation of a Novel WNK2 Inhibitor: A New Genetically Informed Target for Osteoarthritis Drug Development
Article Publication Date
6-Aug-2026
COI Statement
Jurynec and first author Shivakumar Veerabhadraiah have filed a U.S. Patent Application (No. 19/672,326) titled ‘Compounds That Inhibit WNK2 Activity And Methods For Treating Osteoarthritis.’
