Telling artificial intelligence models to “think” step by step when carrying out a task can improve their performance so much that they can outperform humans at jobs AIs usually struggle with.
Category: robotics/AI – Page 1,254
Researchers have developed a hackable and multi-functional 3D printer for soft materials that is affordable and open design. The technology has the potential to unlock further innovation in diverse fields, such as tissue engineering, soft robotics, food, and eco-friendly material processing—aiding the creation of unprecedented designs.
The findings could help pave the way for greater use of machine learning in materials science, a field that still relies heavily on laboratory experimentation. Also, the technique of using machine learning to make predictions that are then checked in the lab could be adapted for discovery in other fields, such as chemistry and physics, say experts in materials science.
To understand why it’s a significant development, it’s worth looking at the traditional way new compounds are usually created, says Michael Titus, an assistant professor of materials engineering at Purdue University, who was not involved in the research. The process of tinkering in the lab is painstaking and inefficient.
New research from Carnegie Mellon University’s Robotics Institute can help robots feel layers of cloth rather than relying on computer vision tools to only see it. The work could allow robots to assist people with household tasks like folding laundry.
Humans use their senses of sight and touch to grab a glass or pick up a piece of cloth. It is so routine that little thought goes into it. For robots, however, these tasks are extremely difficult. The amount of data gathered through touch is hard to quantify and the sense has been hard to simulate in robotics—until recently.
“Humans look at something, we reach for it, then we use touch to make sure that we’re in the right position to grab it,” said David Held, an assistant professor in the School of Computer Science and head of the Robots Perceiving and Doing (R-Pad) Lab. “A lot of the tactile sensing humans do is natural to us. We don’t think that much about it, so we don’t realize how valuable it is.”
Berkeley Lab scientists have developed new machine learning algorithms to accelerate the analysis of data collected decades ago by HERA, the world’s most powerful electron-proton collider that ran at the DESY national research center in Germany from 1992 to 2007.
The stock photography company will incorporate AI-generated content into its website using Open-AI’s DALL-E image generator.
Shutterstock recently announced that it will partner with OpenAI to start selling content created using artificial intelligence software.
Igor Kutyaev/iStock.
Text-to-image AI technology.
The company that will work with US Space Force has also won some NASA contracts.
It’s official: robots are here to stay in space. Robotics software and engineering company PickNik Robotics announced on Tuesday that it has won a SpaceWERX contract to work on robotics for the US Space Force, according to a press release acquired by IE
In addition, the company recently won a NASA Small Business Innovation Research (SBIR) Phase I contract for continued work on supervised autonomy for space robotics, as well as a Colorado Advanced Industries Accelerator (AIA) grant for space robotics.
Three wins.
The company has three big wins: a SpaceWERX contract, a NASA Small Business Innovation Research (SBIR) Phase I contract and a Colorado Advanced Industries Accelerator (AIA) grant for space robotics.
Adobe wants to show the world that AI can do more for designers than generate frightening JPEGs.
AI-powered, generative image search engines, like DALL-E and Stable Diffusion, have stolen the hearts of AI enthusiasts since their release. Some even warned this may be the death of Photoshop, Adobe’s signature imaging software.
But after viewing Adobe’s latest innovations at the MAX Conference in Los Angeles this week, the company is taking a different approach with AI.
The just-issued World Robotics Report announced an all-time high of 517,385 new industrial robots installed in 2021 in factories around the world, representing 31% year-on-year growth. That brought the current stock of operational robots around the globe to about 3.5 million, a new record.
This robot record was reached half a century after the development of SHAKEY, the world’s first “mobile intelligent robot.” According to the 2017 IEEE Milestone citation, it “could perceive its surroundings, infer implicit facts from explicit ones, create plans, recover from errors in plan execution, and communicate using ordinary English.
The robot that was going to start the Third Industrial Revolution.
Dr. Peter Fedichev, Ph.D. is the CEO of Gero (https://gero.ai/), a biotech company focused on hacking complex diseases, including aging, with AI for novel drug discovery, as well as digital biomarkers.
Gero’s models originate from the physics of complex dynamic systems, combining the potential of deep neural networks with the physical models to study dynamical processes and understand what drives diseases.
Dr. Fedichev has a background in biophysics, bioinformatics and condensed matter physics, earning his Ph.D. from the University of Amsterdam, and he conducted research at FOM Institute AMOLF (part of the institutes organization of the Dutch Research Council of Netherlands) and the University of Innsbruck.
To date, Dr Fedichev has published over 70 papers covering his research on physics, biophysics and aging biology.