Lifeboat Foundation

Imagine performing a sweep around an object with your smartphone and getting a realistic, fully editable 3D model that you can view from any angle. This is fast becoming reality, thanks to advances in AI.

Researchers at Simon Fraser University (SFU) in Canada have unveiled new AI technology for doing exactly this. Soon, rather than merely taking 2D photos, everyday consumers will be able to take 3D captures of real-life objects and edit their shapes and appearance as they wish, just as easily as they would with regular 2D photos today.

In a new paper appearing on the arXiv preprint server and presented at the 2023 Conference on Neural Information Processing Systems (NeurIPS) in New Orleans, Louisiana, researchers demonstrated a new technique called Proximity Attention Point Rendering (PAPR) that can turn a set of 2D photos of an object into a cloud of 3D points that represents the object’s shape and appearance.

In a recent study published in eBioMedicine, researchers evaluated proteomic signatures in blood plasma and cervicovaginal fluid for endometrial cancer detection.

Study: Detection of endometrial cancer in cervico-vaginal fluid and blood plasma: leveraging proteomics and machine learning for biomarker discovery. Image Credit: mi_viri/Shutterstock.com.

MIT engineers aim to give robots a bit of common sense when faced with situations that push them off their trained path, so they can self-correct after missteps and carry on with their chores. The team’s method connects robot motion data with the common sense knowledge of large language models, or LLMs.

Nvidia’s headquarters is now one of the most sought-after places to work. Spanning more than 1 million square feet combined, Nvidia’s space-ship-like buildings were designed with help from custom software powered by the AI chips that have made the company successful. WSJ gets a look inside. Photo: Nvidia.

Update added to the bottom of the article.

OpenAI’s ChatGPT is down for many people worldwide, with users facing multiple problems, including being unable to access their accounts, having their chat history come up empty, and the chat screens not loading properly.

When accessing ChatGPT, users may see a blank screen with “How can I help you today?” and, in some cases, a missing chat history.

An AI tool called Mia found missed breast cancer symptoms in the scans of 11 women during an NHS test.

AI is driving a dramatic new need for electricity, and while tech execs have long trumpeted their commitment to a green energy future, the urgency of that need presents them with a difficult path forward.

Questions about fueling the AI boom took center stage earlier this month at the CERAWeek by S&P Global, The Wall Street Journal reported. The annual energy conference draws thousands of executives to Houston to discuss topics ranging from geopolitics to the energy transition.

No one knows how much electricity will be needed to power the AI boom. AI requires massive computing power and energy loads and has triggered an explosion of data centers. Microsoft cofounder Bill Gates said at the conference that the amount of power AI is bound to consume is mind-blowing.

Princeton researchers have trained an AI to predict and prevent a common problem arising during nuclear fusion reactions — and they think it might be able to solve other problems, too.

The challenge: If the Spice Girls were physicists, their song “2 Become 1” might have been about nuclear fusion, a reaction that occurs when two atoms merge.

Fusion releases a tremendous amount of energy in the form of heat — it’s what powers the sun and other stars — and if we could harness the reaction here on Earth, we would have a near limitless source of clean energy.

Stanford and McMaster University researchers created an artificial intelligence (AI) model to design molecules that inhibit the growth of Acinetobacter baumannii, a common drug-resistant bacteria. They synthesized and validated six structurally novel molecules that demonstrated antibacterial activity against A. baumannii and other phylogenetically diverse bacterial pathogens. This study represents a significant step toward the practical application of generative AI approaches for antibiotic discovery and drug discovery in general.

The research article, “Generative AI for designing and validating easily synthesizable and structurally novel antibiotics,” was published in Nature Machine Intelligence.

Among the most critical issues in contemporary medicine is the worldwide spread of factors contributing to antibiotic resistance. In 2019, drug-resistant infections were responsible for an estimated 4.95 million deaths. As new antibiotics are being developed slower than the spread of antimicrobial resistance determinants, this figure is expected to reach 10 million annually by 2050.