Lifeboat Foundation

ChatGPT creator OpenAI on Thursday released a new series of artificial intelligence models designed to spend more time thinking—in hopes that generative AI chatbots provide more accurate and beneficial responses.

The new models, known as OpenAI o1-Preview, are designed to tackle complex tasks and solve more challenging problems in science, coding and mathematics, something that earlier models have been criticized for failing to provide consistently.

Unlike their predecessors, these models have been trained to refine their thinking processes, try different methods and recognize mistakes, before they deploy a final answer.

The ChatGPT maker reveals details of what’s officially known as OpenAI o1, which shows that AI needs more than scale to advance.

Dr. Tim Brown.

Taking…

Axon-mimicking Materials for Computing https://engineering.tamu.edu/news/2024/09/axon-mimicking-mat…uting.html.

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“We’re at the beginning of a new industrial revolution”

- Jensen Huang, NVIDIA

CNBC’s Megan Cassella briefly caught up with Nvidia CEO Jensen Huang outside the White House. Here are the details.

Continue reading “Nvidia CEO Jensen Huang: We are at the beginning of a new industrial revolution” »

A report states that due to abysmal yields of its 2nm GAA process, Samsung has little choice but to withdraw personnel from its Taylor plant.

Latent fingerprints require physicochemical development techniques to enhance their visibility and make them interpretable for forensic purposes. Traditional methods for developing fingerprints include optical, physical, and chemical processes that involve interaction between the developing agent (often a colored or fluorescent reagent) and the fingerprint residue. These methods have limitations in recovering high-quality results in certain conditions.

Recently, new methods using mass spectrometry, spectroscopy, electrochemistry, and nanoparticles have improved the development of latent fingerprints. These techniques offer better contrast, sensitivity, and selectivity, with low toxicity. The ability to adjust nanomaterial properties further enhances the detection of both fresh and aged fingerprints.

Mesoporous silica nanoparticles (MSNs) have attracted significant interest since the discovery of the M41S family of molecular sieves, which encompasses MCM-41, MCM-48, and SBA-15. These nanoparticles are characterized by their controlled particle size, porosity, high specific surface area, chemical stability, and ease of surface functionalization.

BillionToOne, which is headquartered in California, is set to build a new facility in Austin’s EastVillage.

Phase separation, when molecules part like oil and water, works alongside oxygen diffusion to help memristors – electrical components that store information using electrical resistance – retain information even after the power is shut off, according to a University of Michigan led study published in Matter (“Thermodynamic origin of nonvolatility in resistive memory”).

Up to this point, explanations have not fully grasped how memristors retain information without a power source, known as nonvolatile memory, because models and experiments do not match up.

“While experiments have shown devices can retain information for over 10 years, the models used in the community show that information can only be retained for a few hours,” said Jingxian Li, U-M doctoral graduate of materials science and engineering and first author of the study.

Growing immature eggs from old mice in the ovarian structures of young mice can reverse signs of ageing in the eggs¹.

“Think of this as a five-star anti-ageing spa for the old egg,” says Rong Li, a cell biologist at the National University of Singapore (NUS), who co-authored a study describing the results.

When the rejuvenated eggs were fertilized, the resulting embryos were almost four times more likely to give rise to healthy pups than the eggs that matured in the old environment. The results are published in Nature Aging today.