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US safety regulators contact Tesla over erratic robotaxis

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The U.S. National Highway Traffic Safety Administration (NHTSA) has contacted Tesla after footage shared on social media appeared to show its newly-launched driverless cars breaking traffic laws.

The firm’s long-awaited robotaxis – which boss Elon Musk says are central to Tesla’s future – were tried out on public roads for the first time in Austin, Texas, on Sunday.

Videos posted online seem to show instances where the vehicles, which had a safety driver in the passenger seat, drive erratically.

In a statement, the NHTSA said it was “aware of the referenced incidents and is in contact with the manufacturer to gather additional information.”

The BBC has contacted Tesla for comment.

Despite the importance Musk places on his robotaxi project, Sunday’s launch was low key.

A small group of invited analysts, influencers and shareholders participated in paid rides.

Musk congratulated Tesla’s artificial intelligence and chip design teams on the launch in a post on X, writing that it was “culmination of a decade of hard work”.

However, social media footage seems to show the vehicles struggled with real world driving scenarios.

One video seems to show a robotaxi stopping abruptly as it passes a parked police car.

Tech news outlet TechCrunch said cars were also seen speeding and swerving into the wrong lane.

The rollout is limited to 12 taxis and Tesla says they won’t operate in bad weather, attempt difficult intersections or carry customers below the age of 18.

Analysts had already said the small-scale launch showed how far Tesla has to go to catch up with rivals.

Waymo, owned by Google parent Alphabet, along with Amazon’s Zoox, already offer self-driving taxi rides in Austin, as well as in San Francisco, California, and Phoenix, Arizona.

Fully driverless cars have done millions of miles on public roads in other countries too, including China, UAE and Singapore, but whether they are more or less safe than human-driven ones is still being investigated.

Tesla is using a different technology to its rivals, relying on in-car cameras rather than the radar and sensors employed by the current market leaders.

It is betting that its approach will be cheaper and therefore ultimately more attractive to consumers.

However, questions have been asked about its safety.

The NHTSA has highlighted that under the law it “does not pre-approve new technologies or vehicle systems – rather, manufacturers certify that each vehicle meets NHTSA’s rigorous safety standards, and the agency investigates incidents involving potential safety defects.”



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Frontiers broadens AI‑driven integrity checks with dual integration

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Image: Shutterstock.com/EtiAmmos

Frontiers has announced that external fraud‑screening tools – Cactus Communications’ Paperpal Preflight, and Clear Skies’ Papermill Alarm and Oversight – have been integrated into its own Artificial Intelligence Review Assistant (AIRA) submission-screening system.

The expansion delivers what the companies describe as “an unprecedented, multilayered defence against organised research fraud, strengthening the reliability and integrity of every manuscript submitted to Frontiers”.

AIRA was launched in 2018, making Frontiers one of the early adopters of AI in submission checking. In 2022, Frontiers added its own papermill check to its comprehensive catalogue of AIRA checks, with the aim of tackling the industry-wide problem of manufactured manuscripts. The latest version, released in 2025, uses more than 15 data points and signals of potential manufactured manuscripts to be investigated and validated by a human expert.

Dr Elena Vicario, Head of Research Integrity at Frontiers, said: “Maintaining trust in the scholarly record demands constant innovation. By combining the unique strengths of Clear Skies and Cactus with our own AI capabilities, we are raising the bar for integrity screening and giving editors and reviewers the confidence that every submission has been rigorously vetted.”

Commenting on the importance of the partnership, Nikesh Gosalia, President, Global Academic and Publisher Relations at Cactus Communications, said: “This partnership with Frontiers reflects the confidence leading publishers have in our AI-driven solutions. Paperpal Preflight is a vital tool that supports editorial teams and existing homegrown solutions in identifying and addressing potential issues early in the publishing workflow.

“As one of the world’s largest and most impactful research publishers, Frontiers is taking an important step in strengthening research integrity, and we are proud to collaborate with them in this mission of safeguarding research.”

Adam Day, Founder and CEO of Clear Skies, added: “Clear Skies is thrilled to be working with the innovative team at Frontiers to integrate AIRA with Oversight. This integration makes our multi-award-winning services, including the Papermill Alarm, available across the Frontiers portfolio.

“Oversight is the first index of research integrity and recipient of the inaugural EPIC Award for integrity tools from the Society for Scholarly Publishing (SSP). As well as providing strategic Oversight to publishers, our detailed article reports support human Oversight of research integrity investigations on publications as well as journal submissions.”



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Australia’s China AI quandary is a dealmaker’s opportunity

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It is not surprising that reactions to Chinese ambassador Xiao Qian’s suggestion that Australia and China cooperate more on artificial intelligence as part of an expanded Free Trade Agreement have been hawkish. However, it highlights the need for Australian organisations to broaden their view on the AI world.

It would take a dramatic shift in policy position for Australia to suddenly start collaborating with China on AI infrastructure such as data centres and the equipment that runs them. But it would be wrong to assume that advances in capability will always come from America first.

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Joint UT, Yale research develops AI tool for heart analysis – The Daily Texan

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A study published on June 23 in collaboration with UT and Yale researchers developed an artificial intelligence tool capable of performing and analyzing the heart using echocardiography. 

The app, PanEcho, can analyze echocardiograms, or pictures of the heart, using ultrasounds. The tool was developed and trained on nearly one million echocardiographic videos. It can perform 39 echocardiographic tasks and accurately detect conditions such as systolic dysfunction and severe aortic stenosis.

“Our teammates helped identify a total of 39 key measurements and labels that are part of a complete echocardiographic report — basically what a cardiologist would be expected to report on when they’re interpreting an exam,” said Gregory Holste, an author of the study and a doctoral candidate in the Department of Electrical and Computer Engineering. “We train the model to predict those 39 labels. Once that model is trained, you need to evaluate how it performs across those 39 tasks, and we do that through this robust multi site validation.” 

Holste said out of the functions PanEcho has, one of the most impressive is its ability to measure left ventricular ejection fraction, or the proportion of blood the left ventricle of the heart pumps out, far more accurately than human experts. Additionally, Holste said PanEcho can analyze the heart as a whole, while humans are limited to looking at the heart from one view at a time. 

“What is most unique about PanEcho is that it can do this by synthesizing information across all available views, not just curated single ones,” Holste said. “PanEcho integrates information from the entire exam — from multiple views of the heart to make a more informed, holistic decision about measurements like ejection fraction.” 

PanEcho is available for open-source use to allow researchers to use and experiment with the tool for future studies. Holste said the team has already received emails from people trying to “fine-tune” the application for different uses. 

“We know that other researchers are working on adapting PanEcho to work on pediatric scans, and this is not something that PanEcho was trained to do out of the box,” Holste said. “But, because it has seen so much data, it can fine-tune and adapt to that domain very quickly. (There are) very exciting possibilities for future research.”



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