The white dwarf that has researchers intrigued is named WD 0816-310, and it’s the remnant of a star barely extra large than our Sun. All that continues to be of that star now’s the white dwarf core, which is about the identical measurement as Earth.
The researchers have been capable of find out about this metallic scar by seeing how metals have been distributed throughout the star’s floor. The metals aren’t evenly unfold however are slightly concentrated specifically areas. They may inform this by seeing how the energy of the sign coming from the metals modified in energy because the planet rotated.
The modifications in detection ranges of the metals have been additionally associated to modifications within the magnetic area of the white dwarf. The outcomes recommend that the metals are clumped across the magnetic pole, which supplies a clue to how they received there: The researchers assume that the magnetic area acted like a funnel for incoming matter from the planetary chunk, pulling it onto the star’s floor and creating the scar.
“Surprisingly, the material was not evenly mixed over the surface of the star, as predicted by theory. Instead, this scar is a concentrated patch of planetary material, held in place by the same magnetic field that has guided the infalling fragments,” stated co-author John Landstreet of Western University, Canada. “Nothing like this has been seen before.”
# Toyota Research Institute Unveils Breakthrough in Teaching Robots New Behaviors
## New Generative AI Technique Brings Researchers One Step Closer to Building a “Large Behavior Model”
**LOS ALTOS, Calif. and CAMBRIDGE, Mass. (Sept. 19, 2023)** – Today, Toyota Research Institute (TRI) announced a breakthrough generative AI approach based on Diffusion Policy to quickly and confidently teach robots new, dexterous skills. This advancement significantly improves robot utility and is a step towards building “Large Behavior Models (LBMs)” for robots, analogous to the Large Language Models (LLMs) that have recently revolutionized conversational AI.
“Our research in robotics is aimed at amplifying people rather than replacing them,” said [Gill Pratt](https://www.tri.global/about-us/dr-gill-pratt), CEO of TRI and Chief Scientist for Toyota Motor Corporation. “This new teaching technique is both very efficient and produces very high performing behaviors, enabling robots to much more effectively amplify people in many ways.”
Previous state-of-the-art techniques to teach robots new behaviors were slow, inconsistent, inefficient, and often limited to narrowly defined tasks performed in highly constrained environments. Roboticists needed to spend many hours writing sophisticated code and/or using numerous trial and error cycles to program behaviors.
TRI has already taught robots more than 60 difficult, dexterous skills using the new approach, including pouring liquids, using tools, and manipulating deformable objects. These achievements were realized without writing a single line of new code; the only change was supplying the robot with new data. Building on this success, TRI has set an ambitious target of teaching hundreds of new skills by the end of the year and 1,000 by the end of 2024.
Today’s news also highlights that robots can be taught to function in new scenarios and perform a wide range of behaviors. These skills are not limited to just “‘pick and place” or simply picking up objects and putting them down in new locations. TRI’s robots can now interact with the world in varied and rich ways – which will one day allow robots to support people in everyday situations and unpredictable, ever-changing environments.
“The tasks that I’m watching these robots perform are simply amazing – even one year ago, I would not have predicted that we were close to this level of diverse dexterity,” remarked [Russ Tedrake](https://www.tri.global/about-us/dr-russ-tedrake), Vice President of Robotics Research at TRI. Dr. Tedrake, who is also the Toyota Professor of Electrical Engineering and Computer Science, Aeronautics and Astronautics, and Mechanical Engineering at MIT, explained, “What is so exciting about this new approach is the rate and reliability with which we can add new skills. Because these skills work directly from camera images and tactile sensing, using only learned representations, they are able to perform well even on tasks that involve deformable objects, cloth, and liquids – all of which have traditionally been extremely difficult for robots.”
**Technical details:**
TRI’s robot behavior model learns from haptic demonstrations from a teacher, combined with a language description of the goal. It then uses an AI-based Diffusion Policy to learn the demonstrated skill. This process allows a new behavior to be deployed autonomously from dozens of demonstrations. Not only does this approach produce consistent, repeatable, and performant results, but it does so with tremendous speed.
Key achievements of TRI’s research for this novel development include:
– **Diffusion Policy:** TRI and our collaborators in [Professor Song](https://shurans.github.io/)’s group at Columbia University developed a new, powerful generative-AI approach to behavior learning. This approach, called [Diffusion Policy](https://arxiv.org/abs/2303.04137), enables easy and rapid behavior teaching from demonstration.
– **Customized Robot Platform:** TRI’s robot platform is custom-built for dexterous dual-arm manipulation tasks with a special focus on enabling haptic feedback and tactile sensing.
– **Pipeline**: TRI robots have learned 60 dexterous skills already, with a target of hundreds by the end of the year and 1,000 by the end of 2024.
– **Drake**: Part of our (not so) secret sauce is [Drake](https://drake.mit.edu/), a model-based design for robotics that provides us with a cutting-edge toolbox and simulation platform. Drake’s high degree of realism allows us to develop in both simulation and in reality at a dramatically increased scale and velocity than would otherwise be possible. Our internal robot stack is built using Drake’s optimization and systems frameworks, and we have made Drake open source to catalyze work across the entire robotics community.
– **Safety:** Safety is core to our robotics efforts at TRI. We have designed our system with strong safeguards, powered by Drake and our custom robot control stack, to ensure our robots respect safety guarantees like not colliding with itself or its environment.
[Diffusion Policy](https://arxiv.org/abs/2303.04137) has been published at the 2023 Robotics Science and Systems conference. Additional technical information can be found on [TRI’s Medium blog](https://toyotaresearch.medium.com/2c30b1a8c573).
Please join our LinkedIn Live Q&A session on October 4th from 1 pm – 1:30 pm ET / 10 am – 10:30 am PT, for an opportunity to learn more and hear directly from the TRI robotics research team. Sign up for the event on [TRI’s LinkedIn page](https://www.linkedin.com/events/trilinkedinlive7108154211422408704/theater/).
## About Toyota Research Institute
Toyota Research Institute (TRI) conducts research to amplify human ability, focusing on making our lives safer and more sustainable. Led by Dr. Gill Pratt, TRI’s team of researchers develops technologies to advance energy and materials, human-centered artificial intelligence, human interactive driving, machine learning, and robotics. Established in 2015, TRI has offices in Los Altos, California, and Cambridge, Massachusetts. For more information about TRI, please visit [http://tri.global](http://tri.global).
A new exploit, known as BLASTPASS, has been discovered by Citizen Lab, involving the use of iMessage accounts to send malicious image files. In response, Apple has released an iPhone update, iOS 16.6.1, to address this vulnerability. To safeguard your device, follow these steps: Go to Settings → General → Software Update and run the software update as soon as possible.
For added protection, Apple has also released updates for iPad, Mac, and Apple Watch. It is recommended to install these updates urgently.
Apple has acknowledged the severity of the exploit, stating that the processing of a manipulated image could result in arbitrary code execution. They are aware of reports of active exploitation. In response, Apple has addressed the buffer overflow issue in ImageIO with improved memory handling. Additionally, a similar issue in Wallet has been resolved with enhanced logic.
While the majority of users are unlikely to be targeted by NSO Group clients, it is advisable to take precautions. Citizen Lab suggests activating the iPhone’s “Lockdown Mode,” which offers resistance against Pegasus-style mercenary malware attacks. To enable this feature, follow these steps: Go to Settings → Privacy & Security → Security → Lockdown Mode → Turn On Lockdown Mode → Turn On Lockdown Mode (again) → Turn On & Restart. After entering your device passcode, the mode will be activated.
The concentration of ammonia in different layers of Saturn’s atmosphere has provided scientists with valuable insights. It was observed that there is a higher amount of ammonia closer to the planet, indicating a system that moves ammonia through these layers. Imke de Pater, co-author from UC Berkeley, explained that radio observations help understand various processes such as heat transport, cloud formation, and convection in the atmospheres of giant planets on different scales.
The researchers discovered a correlation between ammonia levels and massive storms that have occurred on Saturn in the past. It is believed that ammonia moves through the atmosphere via evaporation and precipitation, similar to the water cycle on Earth. These storms can have long-lasting effects, with evidence of recent storms from 2010 as well as older storms that left detectable signatures in the atmosphere, dating back hundreds of years.
One fascinating finding is that despite both Saturn and Jupiter being gas giants primarily composed of hydrogen, the dynamics of their atmospheres are quite distinct. This highlights the vast amount of knowledge we still need to uncover about these magnificent planets.
Scientists are using NASA’s AVIRIS-NG instrument to detect signs of GLRaV-3, a grapevine disease. AVIRIS-NG is typically used for ecological research, such as studying wildfires and air pollution. However, in this case, it was used to observe how grape plants interact with sunlight. By analyzing the composition of light absorbed by the plants, researchers were able to identify infected plants with up to 87% accuracy even before they exhibited symptoms. The study, published in the journal “Phytopathology,” utilized machine learning and data from 11,000 acres of vineyards. This technology has the potential to assist grape farmers and could be extended to monitor crop diseases globally.
The researchers have achieved a significant technological breakthrough by designing the world’s first CPU using artificial intelligence (AI). Their work is outlined in a paper titled “Pushing the Limits of Machine Design: Automated CPU Design with AI.” Instead of manually coding the CPU, the researchers trained their AI model by providing input and output examples, along with a Boolean function to establish a frame of reference. To simplify the process, they used a Binary Speculation Diagram, which effectively instructed the computer on what to do and how to do it.
Designing CPUs is an intricate task that requires careful attention to detail, involving a multitude of sophisticated components. However, machines have proven to be much faster and more efficient than humans in many tasks, and this project reaffirms that fact once again.
The resulting CPU, called RISC-V, would typically take a skilled human team approximately 5,000 hours to produce. In contrast, the AI-designed CPU was created in just five hours. This groundbreaking achievement demonstrates the immense potential of AI in pushing the boundaries of technological innovation.
An Australian company called Vaxxas is on the verge of introducing an alternative to traditional needle-based vaccinations. The company’s vaccine patch technology, which was developed in 2011 by researchers from the University of Queensland, is based on the concept of dry-delivery microneedles. Unlike regular injections, each individual needle in the patch is coated with the vaccine solution.
The patch consists of thousands of tiny needles that are placed on the inside of a small patch. These needles are so small that they cannot be seen or felt, but they are capable of piercing the upper layers of the skin. When the patch is applied to a patient’s arm and tapped, the vaccine is delivered to the immune cells through the needles. The entire process takes only a few seconds and is virtually painless for the patient. Additionally, since the needles are small, only a fraction of the vaccine solution required for a traditional injection is needed to create a single patch.
To fast-track the development and global deployment of vaccine patches, the Queensland state government has pledged its full support to Vaxxas. The patches have been included in the government’s Biomedical 10-Year Roadmap and Action Plan, recognizing their potential contribution to pandemic preparedness.
According to Queensland deputy premier Steven Miles, this technology has the potential to be an essential tool in responding to pandemics. By enabling quick and easy deployment of vaccines to communities, vaccine patches can play a crucial role in preparing for and managing outbreaks.
Vaxxas has already conducted successful tests of its vaccine patch system on more than 500 human subjects. If all goes according to plan, commercial distribution of vaccine patches could begin within the next three to five years.
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