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Category: robotics/AI – Page 43

Tesla’s NEW Model Y L and FSD 14 Rumors

Questions to inspire discussion.

Autonomy and FSD

🤖 Q: What is the biggest valuation upside for Tesla? A: Tesla’s autonomy roadmap is considered the biggest valuation upside, with the company’s robotaxi plans involving 5-passenger vehicles without a driver seat potentially increasing upside option values for investors.

🚘 Q: How has Tesla’s Full Self-Driving (FSD) system improved? A: FSD has made massive improvements with Version 13, and Version 14 may be the breakthrough moment that pushes Tesla past human-level driving and conquers another three nines of safety.

Future Projections.

📈 Q: What is the expected FSD take rate in the coming years? A: The FSD take rate is projected to increase to 20% in the next few years, with cyber cabs having FSD included, while individual owners may need to opt-in for a while before it becomes standard on all new cars.

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US’ secret, unmanned military space plane to embark on new mission

US secret military space plane to embark on new mission with undisclosed goal.

Developed by Boeing, the uncrewed spacecraft is used by the U.S. military to conduct experiments in high and low Earth orbits.

Boeing earlier claimed that the space plane is equipped with state-of-the-art technologies that provide exceptional performance and durability. Its modular design allows for a wide range of experiments and missions, making it a versatile and valuable asset in space exploration.

While it looks like a smaller version of the now-retired space shuttle, the X-37B can’t get into orbit without a boost. For this upcoming mission, it’s hitching a ride on a SpaceX Falcon 9 rocket inside the rocket’s fairing, a protective enclosure made of carbon composite that keeps it safe during the launch until it’s ready to be released into orbit, reported ABC News.

Optimizing how cells self-organize: Computational framework extracts genetic rules

One of the most fundamental processes in all of biology is the spontaneous organization of cells into clusters that divide and eventually turn into shapes—be they organs, wings or limbs.

Scientists have long explored this enormously complex process to make artificial organs or understand cancer growth—but precisely engineering to achieve a desired collective outcome is often a trial-and-error process.

Harvard applied physicists consider the control of cellular organization and morphogenesis to be an that can be solved with powerful new machine learning tools. In new research published in Nature Computational Science, researchers in the John A. Paulson School of Engineering and Applied Sciences (SEAS) have created a computational framework that can extract the rules that cells need to follow as they grow, in order for a collective function to emerge from the whole.

Gone but not forgotten: New research shows the brain’s map of the body remains unchanged after amputation

The brain holds a “map” of the body that remains unchanged even after a limb has been amputated, contrary to the prevailing view that it rearranges itself to compensate for the loss, according to new research from scientists in the UK and US.

The findings, published in Nature Neuroscience, have implications for the treatment of “phantom ” pain, but also suggest that controlling robotic replacement limbs via neural interfaces may be more straightforward than previously thought.

Studies have previously shown that within an area of the brain known as the somatosensory cortex there exists a map of the body, with different regions corresponding to different body parts.

Breaking Barriers in Surface Chemistry: The autoSKZCAM Framework for Ionic Materials

Understanding and predicting chemical reactions on surfaces lies at the heart of modern materials science. From heterogeneous catalysis to energy storage and greenhouse gas sequestration, surface chemistry defines the efficiency and viability of advanced technologies. Yet, computationally modeling these processes with both accuracy and efficiency has been a grand challenge.

A recent study published in Nature Chemistry introduces a breakthrough: the autoSKZCAM framework, an automated and open-source method that applies correlated wavefunction theory (cWFT) to surfaces of ionic materials at costs comparable to density functional theory (DFT). This achievement not only bridges the accuracy gap but also enables routine, large-scale studies of surface processes with chemical accuracy.

Shape-changing soft material for soft robotics, smart textiles and more

Harvard researchers developed liquid crystal elastomers that can switch between multiple shapes — chevrons, flat layers, and coils — in response to heat.

By aligning molecules in different directions, the material can be programmed to morph into domes, saddles, or fin-like motions inspired by stingrays and jellyfish.

The shape-shifting material could advance applications in soft robotics, biomedical devices, and smart textiles.

Liquid crystal elastomers are a class of soft materials that can change shape in response to stimuli such as light or heat — making them promising for applications in soft robotics, wearable and biomedical devices, smart textiles and more. But designing compositionally uniform elastomers that can change into different shapes in response to just one stimulus has been challenging and has limited the application of these potentially powerful materials.

Now, researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a way to program liquid crystal elastomers with the ability to deform in opposite directions just by heating — opening up a range of applications.

The research was published in Science.

(May be a repost from 2024)

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