In a groundbreaking development reported in Nature Microbiology, a team led by a professor at the University of Michigan has harnessed the power of artificial intelligence (AI) to enable robots to conduct up to 10,000 autonomous scientific experiments per day. This cutting-edge technology, known as BacterAI, holds the potential to accelerate the pace of discovery in fields ranging from medicine and agriculture to environmental science.

The researchers, led by Professor Paul Jensen, aimed to understand the metabolism of two microbes associated with oral health, despite having no initial baseline information. Each bacterial species requires specific nutrients to thrive, but determining the precise combination of amino acids they need can be challenging. With 20 amino acids yielding over a million possible combinations, BacterAI stepped in to uncover the amino acid requirements for the growth of Streptococcus gordonii and Streptococcus sanguinis.

NVIDIA has introduced a groundbreaking AI model called Neuralangelo, capable of generating 3D replicas of objects from 2D videos. Whether the subject is a classical sculpture or a regular truck or building, Neuralangelo utilizes multiple frames from different angles to capture the depth, size, and shape of the object. It then creates an initial 3D representation, refining it to mimic the intricate details of the real-world counterpart.

By leveraging technology from its previous model, Instant NeRF, Neuralangelo achieves remarkable precision in capturing fine details, such as textures, patterns, and color variations. NVIDIA claims that Neuralangelo’s ability to handle challenging textures, like the roughness of roof shingles or the smoothness of marble, “significantly surpasses prior methods.” The model can even generate usable virtual objects from smartphone videos, providing creators with a simple way to produce 3D replicas for their projects. Moreover, NVIDIA Research states that Neuralangelo can generate complete 3D scenes within a remarkably short timeframe of two hours.

Scientists in Singapore, from Duke-NUS Medical School, A*STAR’s Genome Institute of Singapore (GIS), and Singapore General Hospital (SGH), alongside their colleagues, have harnessed the power of artificial intelligence (AI) to expedite the identification of crucial biomarkers that can predict the non-responsiveness of chronic myeloid leukemia (CML) patients to conventional treatments. This early prognosis enables patients to receive potentially life-saving bone marrow transplants during the initial stages of the disease.

CML is a form of blood cancer triggered by a genetic mutation that permanently activates an enzyme called tyrosine kinase. This mutation occurs in a blood stem cell within the bone marrow, causing it to transform into an aggressive leukemic cell that eventually supplants healthy blood production.

The human brain, often referred to as the most complex entity in the universe, has long fascinated scientists seeking to replicate its unparalleled computing capabilities. In a significant breakthrough, researchers at Los Alamos National Laboratory have successfully created a new type of memristive device, demonstrating its potential for constructing artificial synapses in cutting-edge neuromorphic computing.

Memristors, or memristive devices, represent a highly sought-after circuit technology that possesses both memory and programming capabilities. Unlike conventional resistor technology, memristors possess the ability to retain their electrical state even when powered off, resembling the memory retention of the human brain. This unique characteristic opens up a realm of possibilities for computing and device development. Aiping Chen, a scientist at the Center for Integrated Nanotechnologies, explained the significance of data processing in today’s scientific advancements, encompassing fields such as machine learning, artificial intelligence, and artificial neural networks.