Google introduces a novel approach with the potential for rapid text-to-image generation on-device…it can run in half a second to generate a 512x512 high-quality image.
OpenAI is developing a blueprint for evaluating the risk that a large language model (LLM) could aid someone in creating a biological threat.
Volkswagen said its new AI lab will serve as a “globally networked competence center and incubator” to produce proofs of concept in the field of the tech surrounding automotive innovations.
Chinese regulators granted approvals to a total of 14 large language models (LLM) for public use last week
There’s a noticeable cultural shift within the industry as companies start to see themselves as data companies driving a transformation that emphasizes the reuse of diverse and historical data to shape predictions and inform decision-making...In an industry where spending over $6.5 billion, failing 95% of the time, and taking an average of 12 years to release a single drug is the norm, the promise of AI is particularly compelling.12 Initial forays into AI-assisted drug development have shown that it’s possible to cut development time by a factor of 15 and to reduce costs by 70% of what they would be without AI.
This week marks a tipping point for treatments of inherited deafness. On Wednesday, a new study reported findings of a clinical trial showing hearing recovery and improvements
https://www.sciencenews.org/article/artificial-intelligence-new-battery
Not all software is perfect—many apps, programs, and websites are released despite bugs… Formal verification involves writing a mathematical proof of your code and is “one of the hardest but also most powerful ways of making sure your code is correct,”… To make formal verification easier, Brun and his colleagues devised a new AI-powered method called Baldur to automatically generate proofs.
As an early user of Variational AI’s technology, the Big Pharma will assess the ability of the platform to generate novel small molecules that match its target product profiles (TPPs).
The identification/development of a machine learning-based classifier that utilizes metabolic profiles of serum samples to accurately identify individuals with ovarian cancer.
According to the developers, FSD Beta v12 replaces over 300,000 lines of explicit C++ code with a single end-to-end neural network trained on millions of video clips.
