Researchers in China have developed an AI model that can discern species and larval stage of four lepidopteran corn pests with 96 percent accuracy.
Category: robotics/AI – Page 66
Fitzgerald says cyborg search and rescue beetles or cockroaches might be able to help in disaster situations by finding and reporting the location of survivors and delivering lifesaving drugs to them before human rescuers can get there.
But first, the Australian researchers must master the ability to direct the movements of the insects, which could take a while. Fitzgerald says that although the work might seem futuristic now, in a few decades, cyborg insects could be saving lives.
He’s not the only roboticist creating robots from living organisms. Academics at the California Institute of Technology (Caltech), for example, are implanting electronic pacemakers into jellyfish to control their swimming speed. They hope the bionic jellies could help collect data about the ocean far below the surface.
Summary: A new study highlights how brain age models can track healthy infant development and reveal environmental influences. Using MRI data from over 600 term and preterm infants, researchers trained machine learning models to predict brain age and identify gaps between predicted and actual ages.
These brain age gaps can indicate whether an infant’s development is faster or slower than expected, with maternal age emerging as a significant influencing factor. Advanced brain development was linked to better cognitive abilities but poorer emotional regulation, suggesting that following normative developmental trajectories may be ideal.
Chinese researchers have created the BHMbot-B, a 15 mm long microrobot with quick forward and backward movements, which is ideal for navigating small places.
The robot effectively switches between forward and backward movement by aligning the vibratory motions of its magnet, cantilever, and linkages using vibration mode transition control.
The Beihnag University team claims that the device combines a battery, a control circuit for wireless operation, and two electromagnetic actuators for a high load capacity.
New research from the Human Cell Atlas offers insights into cell development, disease mechanisms, and genetic influences, enhancing our understanding of human biology and health.
The Human Cell Atlas (HCA) consortium has made significant progress in its mission to better understand the cells of the human body in health and disease, with a recent publication of a Collection of more than 40 peer-reviewed papers in Nature and other Nature Portfolio journals.
The Collection showcases a range of large-scale datasets, artificial intelligence algorithms, and biomedical discoveries from the HCA that are enhancing our understanding of the human body. The studies reveal insights into how the placenta and skeleton form, changes during brain maturation, new gut and vascular cell states, lung responses to COVID-19, and the effects of genetic variation on disease, among others.
Great article! I really resonate with how Raj Reddy describes his thinking about societal adaptation to technological change.
While some fret about technology’s social impacts, Raj Reddy still believes in the power of artificial intelligence to improve lives.
DeepMind, Google’s AI research org, has unveiled a model that can generate an “endless” variety of playable 3D worlds.
Called Genie 2, the model — the successor to DeepMind’s Genie, which was released earlier this year — can generate an interactive, real-time scene from a single image and text description (e.g. “A cute humanoid robot in the woods”). In this way, it’s similar to models under development by Fei-Fei Li’s company, World Labs, and Israeli startup Decart.
DeepMind claims that Genie 2 can generate a “vast diversity of rich 3D worlds,” including worlds in which users can take actions like jumping and swimming by using a mouse or keyboard. Trained on videos, the model’s able to simulate object interactions, animations, lighting, physics, reflections, and the behavior of “NPCs.”
Games play a key role in AI research.
Generating unlimited diverse training environments for future general agents.
Today we introduce Genie 2, a foundation world model capable of generating an endless variety of action-controllable, playable 3D environments for training and evaluating embodied agents. Based on a single prompt image, it can be played by a human or AI agent using keyboard and mouse inputs.
Games play a key role in the world of artificial intelligence (AI) research. Their engaging nature, unique blend of challenges, and measurable progress make them ideal environments to safely test and advance AI capabilities.
Frontiers: A base on the Moon surface or a mission to Mars are potential destinations for human spaceflight, according to current space agencies’ plans
Posted in biological, chemistry, food, robotics/AI, space, sustainability | Leave a Comment on Frontiers: A base on the Moon surface or a mission to Mars are potential destinations for human spaceflight, according to current space agencies’ plans
These scenarios pose several new challenges, since the environmental and operational conditions of the mission will strongly differ than those on the International Space Station (ISS). One critical parameter will be the increased mission duration and further distance from Earth, requiring a Life Support System (LSS) as independent as possible from Earth’s resources. Current LSS physico-chemical technologies at the ISS can recycle 90% of water and regain 42% of O2 from the astronaut’s exhaled CO2, but they are not able to produce food, which can currently only be achieved using biology. A future LSS will most likely include some of these technologies currently in use, but will also need to include biological components. A potential biological candidate are microalgae, which compared to higher plants, offer a higher harvest index, higher biomass productivity and require less water. Several algal species have already been investigated for space applications in the last decades, being Chlorella vulgaris a promising and widely researched species. C. vulgaris is a spherical single cell organism, with a mean diameter of 6 µm. It can grow in a wide range of pH and temperature levels and CO2 concentrations and it shows a high resistance to cross contamination and to mechanical shear stress, making it an ideal organism for long-term LSS. In order to continuously and efficiently produce the oxygen and food required for the LSS, the microalgae need to grow in a well-controlled and stable environment. Therefore, besides the biological aspects, the design of the cultivation system, the Photobioreactor (PBR), is also crucial. Even if research both on C. vulgaris and in general about PBRs has been carried out for decades, several challenges both in the biological and technological aspects need to be solved, before a PBR can be used as part of the LSS in a Moon base. Those include: radiation effects on algae, operation under partial gravity, selection of the required hardware for cultivation and food processing, system automation and long-term performance and stability.
The International Space Station (ISS) has been continuously inhabited for over twenty years. The Life Support System (LSS) on board the station is in charge of providing the astronauts with oxygen, water and food. For that, Physico-Chemical (PC) technologies are used, recycling 90% of the water and recovering 42% of the oxygen (O2) from the carbon dioxide (CO2) that astronauts produce (Crusan and Gatens, 2017), while food is supplied from Earth.
Space agencies currently plan missions beyond Low Earth Orbit, with a Moon base or a mission to Mars as potential future scenarios (ESA Blog 2016; ISEGC 2018; NASA 2020). The higher distance from Earth of a lunar base, compared to the ISS, might require the production of food in-situ, to reduce the amount of resources required from Earth. PC technologies are not able to produce food, which can only be achieved using biological organisms. Several candidates are currently being investigated, with a main focus on higher plants (Kittang et al., 2014; Hamilton et al., 2020) and microalgae (Detrell et al., 2020b; Poughon et al., 2020).