We are about to show you a technological innovation that could, one day, change the way every child in every school in America is taught. It’s an online tutor powered by artificial intelligence designed to help teachers be more efficient… and students learn more effectively. It’s called Khanmigo–conmigo means “with me,” in Spanish. And Khan…is its creator…Sal Khan, the well-known founder of Khan Academy — whose lectures and educational software have been used for years by tens of millions of students and teachers in the U.S. and around the world. Khanmigo was built with the help of OpenAI, the creator of ChatGPT. Its potential is staggering, but it’s still very much a work in progress. It’s being piloted in 266 school districts in the U.S. in grades three-12. We went to Hobart High School in Indiana to see how it works.

Melissa Higgason: Good morning, just a normal day in chem, right?

At eight in the morning Melissa Higgason knows it’s not always easy to get 30 high schoolers excited about chemistry.

In 2018, Google DeepMind’s AlphaZero program taught itself the games of chess, shogi, and Go using machine learning and a special algorithm to determine the best moves to win a game within a defined grid. Now, a team of Caltech researchers has developed an analogous algorithm for autonomous robots—a planning and decision-making control system that helps freely moving robots determine the best movements to make as they navigate the real world.

“Our algorithm actually strategizes and then explores all the possible and important motions and chooses the best one through dynamic simulation, like playing many simulated games involving moving robots,” says Soon-Jo Chung, Caltech’s Bren Professor of Control and Dynamical Systems and a senior research scientist at JPL, which Caltech manages for NASA. “The breakthrough innovation here is that we have derived a very efficient way of finding that optimal safe motion that typical optimization-based methods would never find.”

The team describes the technique, which they call Spectral Expansion Tree Search (SETS), in the December cover article of the journal Science Robotics.

What’s the best way to precisely manipulate a material’s properties to the desired state? It may be straining the material’s atomic arrangement, according to a team led by researchers at Penn State. The team discovered that “atomic spray painting” of potassium niobate, a material used in advanced electronics, could tune the resulting thin films with exquisite control.

The finding, published in Advanced Materials (“Colossal Strain Tuning of Ferroelectric Transitions in KNbO 3 Thin Films”), could drive environmentally friendly advancements in consumer electronics, medical devices and quantum computing, the researchers said.

The process, called strain tuning, alters a material’s properties by stretching or compressing its atomic unit cell, which is the repeating motif of atoms that builds up its crystal structure. The researchers use molecular beam epitaxy (MBE), a technique that involves depositing a layer of atoms on a substrate to form a thin film. In this case, they produced a thin film of strain-tuned potassium niobate.

Could human–AI collaborations be the future of interdisciplinary studies?

Its a problem, but im sure ASI by 2035 will solve for a way to use a Crispr type tool with zero unintended alterations. Look for a way to use w/ out alterations in meantime, but worst case ASI will solve it.

Genome editing with various CRISPR-Cas molecule complexes has progressed rapidly in recent years. Hundreds of labs around the world are now working to put these tools to clinical use and are continuously advancing them.

CRISPR-Cas tools allow researchers to modify individual building blocks of genetic material in a precise and targeted manner. Gene therapies based on such gene editing are already being used to treat inherited diseases, fight cancer and create drought-and heat-tolerant crops.

The CRISPR-Cas9 molecular complex, also known as genetic scissors, is the most widely used tool by scientists around the world. It cuts the double-stranded DNA at the exact site where the genetic material needs to be modified. This contrasts with newer gene-editing methods, which do not cut the double strand.

Large language models such as OpenAI’s o1 have electrified the debate over achieving artificial general intelligence, or AGI. But they are unlikely to reach this milestone on their own.

I had wondered if AI could just learn and advance from it s users.

During your first driving class, the instructor probably sat next to you, offering immediate advice on every turn, stop and minor adjustment. If it was a parent, they might have even grabbed the wheel a few times and shouted “Brake!” Over time, those corrections and insights developed experience and intuition, turning you into an independent, capable driver.

Although advancements in artificial intelligence (AI) have made self-driving cars a reality, the teaching methods used to train them remain a far cry from even the most nervous side-seat driver. Rather than nuance and real-time instruction, AI learns primarily through massive datasets and extensive simulations, regardless of the application.

Now, researchers from Duke University and the Army Research Laboratory have developed a platform to help AI learn to perform complex tasks more like humans. Nicknamed GUIDE for short, the AI framework will be showcased at the upcoming Conference on Neural Information Processing Systems (NeurIPS 2024), taking place Dec. 9–5 in Vancouver, Canada. The work is also available on the arXiv preprint server.

Researchers have developed a revolutionary method to produce entangled photon pairs using much thinner materials, drastically reducing the size of quantum computing components.

This breakthrough enables simpler, more compact setups for quantum technologies, potentially transforming fields from climate science to pharmaceuticals.

Breakthrough in Quantum Computing.

From 2022, but an interesting look at Lobsters, and list of animals semi-immortal, tortoises, greenland sharks, jellyfish, etc…

Could the key to lobsters’ longevity slow down our biological clocks?

No one likes the thought of getting old, but it seems to be an inevitable part of life. Most species grow, develop and repair damage to their bodies until a certain point in adulthood. After this, the body becomes less capable of repairing itself and slowly starts to accumulate damage.

But this doesn’t seem to apply to lobsters. They keep growing throughout their extraordinarily long lives – the oldest known lobsters captured have weighed over nine kilograms, with ages estimated between 120 and 140 years.

The CEO also talked about how much AI computing power increased in the past 10 years and Nvidia’s single greatest contribution to AI.