Lifeboat Foundation

In 2024, security teams face new opportunities and obstacles, such as escalating geopolitical tensions, stricter compliance mandates, and the rise of generative AI — which will transform the industry in new and unexpected ways.

In the State of Security 2024: The Race to Harness AI, we identify organizations that are pulling ahead of their peers and share key characteristics and findings.

ChemCrow, an AI developed by researchers at EPFL, integrates multiple expert tools to perform chemical research tasks with unprecedented efficiency.

Chemistry, with its intricate processes and vast potential for innovation, has always been a challenge for automation. Traditional computational tools, despite their advanced capabilities, often remain underutilized due to their complexity and the specialized knowledge required to operate them.

AI Revolution in Chemistry.

A team led by Prof Frank Glorius from the Institute of Organic Chemistry at the University of Münster has developed an evolutionary algorithm that identifies the structures in a molecule that are particularly relevant for a respective question and uses them to encode the properties of the molecules for various machine-learning models.

(TQI) is the leading online resource dedicated exclusively to Quantum Computing.

And it’s not what you think it is.

Here is an interview concerning the current AI and generative AI waves, and their relation to neuroscience. We propose solutions based on new technology from neuroAI – which includes humans ability for reasoning, thought, logic, mathematics, proof etc. – and are therefore poorly modeled by data analysis on its own. Some of our work – also with scholars – has been published, while more is to come in a spin-off setting.

There used to be the concept of a “singularity”. The idea was that computers would become smarter than humans and start to replace them. Even the idea that humanity would be substituted by silicon-based computing machines (robots) was suggested. Against that two years ago we set the concept of “The convergence”. This assumes that biological and silicon-based computation would merge in the sense of better control over biological processes like diseases and longevity. It is essentially a deeply humanistic perspective, in spite of being futuristic, and not taking misuses actively into account.

Summary: Researchers developed a groundbreaking model called Brain Language Model (BrainLM) using generative artificial intelligence to map brain activity and its implications for behavior and disease. BrainLM leverages 80,000 scans from 40,000 subjects to create a foundational model that captures the dynamics of brain activity without the need for specific disease-related data.

This model significantly reduces the cost and scale of data required for traditional brain studies, offering a robust framework that can predict conditions like depression, anxiety, and PTSD more effectively than other tools. The BrainLM demonstrates a potent application in clinical trials, potentially halving the costs by identifying patients most likely to benefit from new treatments.

Explore how AI transforms clinical screening and preventative healthcare. Dive into the impact on efficiency, patient outcomes, and more.