New tools use artificial intelligence to assist students with autism and dyslexia and address accessibility for those who are blind or deaf.
Category: robotics/AI – Page 912
Hydrogel locomotion regulated by light and electric fields
Materials scientists aim to develop autonomous materials that function beyond stimulus responsive actuation. In a new report in Science Advances, Yang Yang and a research team in the Center for Bioinspired Energy Science at the Northwestern University, U.S., developed photo-and electro-activated hydrogels to capture and deliver cargo and avoid obstacles on return.
To accomplish this, they used two spiropyran monomers (photoswitchable materials) in the hydrogel for photoregulated charge reversal and autonomous behaviors under a constant electric field. The photo/electro-active materials could autonomously perform tasks based on constant external stimuli to develop intelligent materials at the molecular scale.
Soft materials with life-like functionality have promising applications as intelligent, robotic materials in complex dynamic environments with significance in human-machine interfaces and biomedical devices. Yang and colleagues designed a photo-and electro-activated hydrogel to capture and deliver cargo, avoid obstacles, and return to its point of departure, based on constant stimuli of visible light and applied electricity. These constant conditions provided energy to guide the hydrogel.
A deep learning technique to improve how robots grasp objects
Most adult humans are innately able to pick up objects in their environment and hold them in ways that facilitate their use. For instance, when picking up a cooking utensil, they would normally grab it from the side that will not be placed inside the cooking pot or pan.
Robots, on the other hand, need to be trained on how to best pick up and hold objects while completing different tasks. This is often a tricky process, given that the robot might also come across objects that it never encountered before.
The University of Bonn’s Autonomous Intelligent Systems (AIS) research group recently developed a new learning pipeline to improve a robotic arm’s ability to manipulate objects in ways that better support their practical use. Their approach, introduced in a paper published on the pre-print server arXiv, could contribute to the development of robotic assistants that can tackle manual tasks more effectively.
Scientists employ AI to predict brain cancer outcomes
“Because of the heterogeneity of this disease, scientists haven’t found good ways of tackling it,” said Olivier Gevaert, PhD, associate professor of biomedical informatics and of data science.
Doctors and scientists also struggle with prognosis, as it can be difficult to parse which cancerous cells are driving each patient’s glioblastoma.
But Stanford Medicine scientists and their colleagues recently developed an artificial intelligence model that assesses stained images of glioblastoma tissue to predict the aggressiveness of a patient’s tumor, determine the genetic makeup of the tumor cells and evaluate whether substantial cancerous cells remain after surgery.
AI Can Now Design Proteins That Behave Like Biological ‘Transistors’
Enter AI. Multiple deep learning methods can already accurately predict protein structures— a breakthrough half a century in the making. Subsequent studies using increasingly powerful algorithms have hallucinated protein structures untethered by the forces of evolution.
Yet these AI-generated structures have a downfall: although highly intricate, most are completely static—essentially, a sort of digital protein sculpture frozen in time.
A new study in Science this month broke the mold by adding flexibility to designer proteins. The new structures aren’t contortionists without limits. However, the designer proteins can stabilize into two different forms—think a hinge in either an open or closed configuration—depending on an external biological “lock.” Each state is analogous to a computer’s “0” or “1,” which subsequently controls the cell’s output.
Shape-Shifting Robot Swarms Self-Assemble, Adapt to the Unfamiliar
A new robotic platform developed at the University of Chicago can adapt to its surroundings in real time for applications in unfamiliar environments.
The platform, dubbed the Granulobot, consists of many identical motorized units each a few centimeters in diameter. The units are embedded with a Wi-Fi microcontroller and sensors and use magnets to engage other units.
As its name suggests, the Granulobot is inspired by the physics of granular materials, which are large aggregates of particles that exhibit a range of complex behaviors. After water, these are the most ubiquitous material on the planet.
Proof that AI Understands? 👀 Andrew Ng on LLMs building mental models, Othello GPT, Geoffrey Hinton
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Do Large Language Models really “understand” the world, or just give the appearance of understanding? Evidence (e.g., Othello-GPT) shows LLMs build models of how the world works, which makes me comfortable saying they do understand. More in The Batch: https://t.co/e0JGU2wUbf
— Andrew Ng (@AndrewYNg) August 10, 2023
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https://arxiv.org/abs/2210.
Minecraft AI — SELF-IMPROVING 🤯 autonomous agent:
25 ChatGPTs play a videogame…
https://youtu.be/GwsRu9yLXnw.
GPT-4 leaked! 🔥 All details exposed 🔥 It is over…
Way too Big to FaiL: The Day CapitAI-ism becomes Sentient
Why is everyone so worried about teenagers using AI to write their term papers while no one is talking about AI crashing the financial markets? If high school Pat gets an A they didn’t earn that’s one thing, but Megla Corp using AI to corner the stock market and crash the world economy, well that is quite another. I have no proof that large corporations are in a competition to build the perfect trader, the ultimate hedge fund manager, the killer quant, and the optimal analyst all rolled into one ultra-economist AI, but I know, we all know, in our greedy little capitalist hearts, it’s true. This wanna-be hegemonic corporation will have unleashed an economic weapon that can’t be bargained with, can’t be reasoned with, doesn’t feel pity or remorse or fear, and absolutely will not stop… EVER, until you are broke!
The legendary Hedge fund manager Kyle Reese aside, think about the implications of a trading bot that has even just a 2% advantage and how much money that can mean. Casino empires were built on games that have less advantage than that so you are crazy if you don’t think there is a race to build the ultimate TradeGPT. Everyone is looking for an edge because, in a land where money is king, he or she who owns a money printer owns the crown. Wall Street was an early adopter of computers and networks and they got so far out ahead of the regulators that they crashed the market on Black Monday in 1987 dropping the US market almost 25% in a day that sent reverberations around the world.
South Korean Scientists Unveil AI Pilot, PiBot
DALLAS – As the world continues to adapt to the growing trend of Artificial Intelligence (AI), South Korean scientists have unveiled a humanoid robot capable of piloting an aircraft.
Named Pibot, the life-sized robot, measuring 160 cm tall and weighing in at 65 kg, is capable of gripping the controls, memorizing aircraft manuals, and even responding to emergency situations. It is fitted with multiple cameras capable of monitoring the aircraft’s systems and operational conditions.
Currently under development by the Korea Advanced Institute of Science & Technology (KAIST), researchers utilized AI chatbots such as ChatGPT to create ways for PiBot to learn the pilot manuals for various aircraft. The robot can then be changed onto an alternative airframe by clicking the type. It can also memorize worldwide Jeppesen aeronautical navigation charts, an impossible task for its human equivalent.