Phys.org July 8, 2024 The development of high-throughput methods like massively parallel reporter assays, data-rich microscopy techniques, computational protein structure prediction and design, and the development of whole-cell models are able to generate huge volumes of data. An international team of researchers (UK, USA – University of Washington) presented a community-developed framework for assessing hazards posed by using data-centric methods to engineer biology and demonstrated its application to two synthetic biology case studies. They showed the diversity of considerations that arise in common types of bioengineering projects and provided some guidelines and mitigating steps. According to the researchers understanding potential […]
Tag Archives: AI
Scientists develop new AI method to create material ‘fingerprints’
Phys.org July 16, 2024 Understanding and interpreting dynamics of functional materials in situ is a challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. Although X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited, spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. A team of engineers in the US (Argonne National Laboratory, University of Chicago) developed an unsupervised deep learning (DL) framework for automated classification of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system. They demonstrated how […]
Innovative paper-like, battery-free, AI-enabled sensor for holistic wound monitoring
Nanowerk June 26, 2023 Researchers in Singapore developed a paper-like battery-free in situ AI-enabled multiplexed (PETAL) sensor for holistic wound assessment by leveraging deep learning algorithms. This sensor consisted of a wax-printed paper panel with five colorimetric sensors for temperature, pH, trimethylamine, uric acid, and moisture. Sensor images captured by a mobile phone were analyzed by neural network–based machine learning algorithms to determine healing status. For ex situ detection via exudates collected from rat perturbed wounds and burn wounds, the PETAL sensor could classify healing versus nonhealing status with an accuracy as high as 97%. With the sensor patches attached […]
Six tips for better coding with ChatGPT
Nature (Nature feature article) June 5, 2023 Artificial intelligence chatbots, such as ChatGPT, have impressive abilities. Yet for all their apparent sentience, chatbots are not intelligent — and they must be used with caution. Researchers who have become adept with the tool offer advice for scientists on how to avoid the pitfalls – “treat this AI as a summer intern” — hard-working and eager to please, but also inexperienced and error-prone. In short, ChatGPT and related tools based on large language models (LLMs), which include Microsoft Bing and GitHub Copilot, are incredibly powerful programming aids, but must be used with […]
Major publishers are banning ChatGPT from being listed as an academic author. What’s the big deal?
Phys.org January 31, 2023 Several papers published recently have listed ChatGPT as an author. Last week, both the Science and Nature journals declared their positions on the use of ChatGPT to generate articles. Science is updating its license and editorial policies to “specify that text generated by ChatGPT (or any other AI tools) cannot be used in the work, nor can figures, images, or graphics be the products of such tools”. Similarly, Nature has formulated the following principles: “No LLM (large language model) tool will be accepted as a credited author on a research paper… Researchers using LLM tools should […]
AI may predict the next virus to jump from animals to humans
Science Daily September 28, 2021 Researchers in the UK developed machine learning models that identify candidate zoonoses solely using signatures of host range encoded in viral genomes. Within a dataset of 861 viral species with known zoonotic status, their approach outperformed models based on the phylogenetic relatedness of viruses to known human-infecting viruses distinguishing high-risk viruses within families that contain a minority of human-infecting species. The model predictions suggested the existence of generalizable features of viral genomes that are independent of virus taxonomic relationships and that may preadapt viruses to infect humans. Their model reduced a second set of 645 […]
Harnessing drones, geophysics and artificial intelligence to root out land mines
Phys.org September 20, 2021 Mines are challenging for clearance operations due to their wide area of impact upon deployment, small size, and random minefield orientation. In their previous work a team of researchers in the US (Columbia University, Binghamton University) focused on developing reliable unpiloted aerial systems (UAS) capable of detecting and identifying individual elements of PFM-1 minefields to rapidly assess wide areas for landmine contamination, minefield orientation, and possible minefield overlap. In their most recent proof-of-concept study they designed and deployed a machine learning workflow involving a region-based convolutional neural network (R-CNN) to automate the detection and classification process. […]
‘Edge of chaos’ opens pathway to artificial intelligence discoveries
Phys.org June 29, 2021 An international team of researchers (Australia, Japan) discovered that on the neuromorphic dynamics of nanowire networks (NWNs), a unique brain-inspired system with synapse-like memristive junctions embedded within a recurrent neural network-like structure. Through simulation and experiment they elucidated how collective memristive switching gives rise to long-range transport pathways, drastically altering the network’s global state via a discontinuous phase transition. The spatio-temporal properties of switching dynamics are found to be consistent with avalanches displaying power-law size and life-time distributions, with exponents obeying the crackling noise relationship, thus satisfying criteria for criticality, as observed in cortical neuronal cultures. […]
Rise of the robo-writers
Nature Podcast April 4, 2021 Trained on billions of words from books, articles and websites, GPT-3 was the latest in a series of ‘large language model’ AIs that are used by companies around the world to improve search results, answer questions, or propose computer code. However, these large language models are not without their issues. Their training is based on the statistical relationships between the words and phrases, which can lead them to generate toxic or dangerous outputs. Preventing responses like these is a huge challenge for researchers, who are attempting to do so by addressing biases in training data, […]
AI Predicts Asymptomatic Carriers of COVID-19
IEEE Spectrum February 2, 2021 An international team of researchers (Germany, USA – industry) has developed a machine learning algorithm to determine the likelihood of asymptomatic carriers of the SARS-CoV-2 virus by using interaction-based continuous learning and inference of individual probability (CLIIP) for contagious ranking. It is based on multi-layer bidirectional path tracking and inference searching. The individual directed graph is determined by the appearance timeline and spatial data that can adapt over time, taking into account the incubation period and several features that can represent real-world circumstances, such as the number of asymptomatic carriers present. The model collects the […]