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Artificial Intelligence Shaping the Future of Medicine

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We take a look at how the latest advancements in artificial intelligence are impacting modern medicine and theorize about what the future may hold.

00:00 Intro.

Disclaimer: This video is not intended to provide diagnosis, treatment, or medical advice. Content provided in this video is for educational purposes only. Please consult with a physician regarding any health-related diagnosis or treatment.

Scientists discover arginine drives metabolic reprogramming to promote tumor growth in liver cancer

Cancer cells are chameleons. They completely change their metabolism to grow continuously. University of Basel scientists have discovered that high levels of the amino acid arginine drive metabolic reprogramming to promote tumor growth. This study suggests new avenues to improve liver cancer treatment.

The liver is a vital organ with many important functions in the body. It metabolizes nutrients, stores energy, regulates the blood sugar level, and plays a crucial role in detoxifying and removing harmful components and drugs. Liver cancer is one of the world’s most lethal types of cancer. Conditions that cause liver cancer include obesity, and hepatitis C infection. Early diagnosis and appropriate therapeutic strategies are crucial for improving treatments in .

In the past decade, scientists have made much progress in understanding the multiple facets of cancer. Historically, it has long been viewed as a disorder in . However, there is growing evidence that cancer is a .

Crazy Ants Behave like Active Swimmers

Without verbal communication, a group of 100 longhorn crazy ants can simultaneously grab onto an object 10,000 times their weight and collectively walk it to their nest. Scientists understand the ant-behavioral rules behind this feat but have lacked a coarse-grained description of how the group moves. Tabea Heckenthaler of the Weizmann Institute of Science in Israel and her colleagues now provide that description, showing that it fits expectations for a self-propelled particle [1]. The finding offers a simplified route to modeling complex systems.

When a foraging ant happens upon a tasty morsel too big to carry alone, she recruits other ants via a pheromone trail. When enough helpers are gathered, they grab on with their mouths and move the object toward home. Ants at the front pull the load, while those at the back lift to reduce friction. From studies of individual ants, scientists have gleaned other details; for example, after an ant grabs on, she spends around 10 seconds pulling in what she thinks is the direction of the nest—regardless of the group’s actual direction—before aligning her efforts with the other workers. There is also a constant turnover of workers, with ants dropping off and new ants immediately filling gaps.

Instead of accounting for such individual behaviors, Heckenthaler and her colleagues consider the ants and the food item as a single moving system. From experiments performed with a cog-shaped load coated in cat food (to encourage the ants), they find that the ant-load system follows trajectories similar to the directed walks of individual self-propelled particles. Comparing trajectories of cogs carried by different numbers of ants, the researchers then show that they can work out details of the ants’ individual behavior from the group-level measurements.

Narrower-Energy Electron Pulses without Electron Loss

Researchers demonstrate a method to reduce the energy spread of electrons used in electron microscopes, opening the door to time-and energy-resolved studies of quasiparticles such as phonons and plasmons.

Conceived a century ago, electron microscopes are today standard fare in experimental research laboratories. By imaging a material with electrons, scientists can resolve details 1,000 times smaller than is possible with light. These devices can also employ pulsed electron beams to probe transient phenomena, such as the behavior of quasiparticles that a material hosts. Now Michael Yannai of Technion–Israel Institute of Technology and his colleagues demonstrate a way to improve that capability by reducing the energy spread of the electrons in a pulsed imaging beam [1]. Their method leaves the brightness of the beam unchanged, which is important for ultrafast imaging, as the ultrashort pulses used in this method necessarily comprise small numbers of electrons. “Our technique opens the path to many potential time-and energy-resolved explorations that are currently impossible,” says Ido Kaminer, who headed the team behind the research.

Electron energy spread is one of the key factors limiting an electron microscope’s resolution. The smaller this spread—the closer the beam is to being monochromatic—the better the resolution. The conventional method for reducing energy spread is to filter out electrons with energies outside of the desired range. But that process significantly reduces the electron flux, another factor that can limit a microscope’s performance.

Using Artificial Intelligence to Help Students With Down Syndrome Succeed

The Center for Artificial Intelligence at King Khalid University embraces AI-driven innovation by using and creating advanced digital technologies to help fulfill Vision 2030 objectives. With that as the main driver, Nada Saeed Al-Qahtani, student and inventor at the College of Computer Science at King Khalid University, developed a robot called “Eve”. Eve is tailored to students with Down Syndrome, being equipped with machine learning curriculum adaptations that make completing tasks easier.

Technology helps paralysed man to walk

A cyclist who was paralysed in an accident is able to walk again, thanks to a breakthrough in neurosurgery and artificial intelligence in Switzerland.
Al Jazeera’s Andrew Simmons reports.

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Asked if Intel can succeed in developing foundries and chips, AMD exec says, ‘Of course not’

Intel has been in the semiconductor chip manufacturing game for a while. Recently, it’s been looking to expand its foundries and production to the point where it could make cutting-edge chips for other companies, a territory we normally associate with TSMC and Samsung.

Currently, Intel is building and ramping up manufacturing in North America, Mexico, and Germany — and these foundries will be doing a lot more than simply creating chips for the latest generation of Core processors. Earlier this year, Intel and Arm announced a partnership to build mobile SoCs on Intel’s 18A process node, and we’ve even heard from the likes of NVIDIA stating that it’s open to working with Intel to produce its hardware.

All of this makes the recent statement from Darren Grasby, the executive vice president for strategic partnerships and president of AMD EMEA, a little shocking. His words were harsh when asked if Intel would succeed in its ambitious plans to build global foundries and develop and create chips for multiple companies. To say the least!


Some harsh words from an AMD exec who doesn’t think Intel’s global foundry expansion and semiconductor manufacturing will drum up new customers.