Chemists are developing a chemical map of all possible molecules to accelerate the discovery process for drugs and materials, with the help of artificial intelligence to determine the properties and viability of these molecules.
IBM has developed a 14-nanometer analog chip for artificial intelligence (AI) that combines computation and memory, similar to the human brain, leading to faster and more energy-efficient processing, making it a significant step towards sustainable AI.
The book "The Coming Wave: AI, Power and the 21st Century’s Greatest Dilemma" by Mustafa Suleyman explores the potential of artificial intelligence and synthetic biology to transform humanity, while also highlighting the risks and challenges they pose.
Artificial intelligence (AI) techniques, particularly machine learning, are increasingly being used in drug research and development (R&D), with applications expanding beyond small molecules to include large-molecule modalities such as antibodies, gene therapies, and RNA-based therapies. These therapies, which make up a significant portion of the biopharma industry's current and future commercial potential, are expected to represent approximately 50% of the oncology market by revenue in 2030, with the majority coming from antibodies.
Artificial intelligence has the potential to revolutionize the medical industry by quickly discovering new drug candidates and extending human lifespans through therapies that repair damage to cells and tissues, leading to a projected $50 billion AI drug discovery revolution and the possibility of living to 150 years old.
UF Health in Jacksonville is using artificial intelligence to help doctors diagnose prostate cancer, allowing them to evaluate cases more quickly and accurately. The AI technology, provided by Paige Prostate, assists in distinguishing between benign and malignant tissue, enhancing doctors' abilities without replacing them.
Former Google executive Mustafa Suleyman warns that artificial intelligence could be used to create more lethal pandemics by giving humans access to dangerous information and allowing for experimentation with synthetic pathogens. He calls for tighter regulation to prevent the misuse of AI.
Biocomputing, a field that combines artificial intelligence with neuroscience, aims to create machines that use real biological neurons and can reason and create ideas like humans, potentially revolutionizing the capabilities of AI and reducing energy consumption by a significant amount.
Scientists have trained an artificial intelligence (AI) system to create an odor map that visually displays the relationships between different smells and accurately predicts what a new molecule would smell like, with the AI's descriptions outperforming those of human panelists in most cases.
AI is revolutionizing scientific research by accelerating drug discovery, predicting protein structures, improving weather forecasting, controlling nuclear fusion, automating laboratory work, and enhancing data analysis, allowing scientists to explore new frontiers and increase research productivity.
Artificial intelligence (AI) has the potential to revolutionize scientific discovery by accelerating the pace of research through tools such as literature-based discovery and robot scientists, but the main obstacle is the willingness and ability of human scientists to use these tools.
Artificial Intelligence (AI) has the potential to improve healthcare, but the U.S. health sector struggles with implementing innovations like AI; to build trust and accelerate adoption, innovators must change the purpose narrative, carefully implement AI applications, and assure patients and the public that their needs and rights will be protected.
Researchers have used artificial intelligence to diagnose and predict the risk of developing various diseases, including Parkinson's disease and heart failure, by analyzing images of a person's retinas, achieving better results than previous AI models; meanwhile, a "Pandora's box" of new protein shapes has been discovered through the analysis of over 200 million predicted protein structures.
Professor Brad Pentelute and the Pentelute Lab at MIT are using a combination of chemistry, biology, and engineering to develop new techniques and platforms that have the potential to revolutionize therapeutics, including using nature-inspired research to solve protein delivery problems and building an automated protein printing machine. They are also using machine learning and automation to discover new peptides and proteins that can be used in cancer treatment and other applications, with the goal of rapidly designing molecules with new functions and advancing the field of AI-driven molecule design.
The use of generative AI, combined with federated and active learning, can accelerate the development of protein drugs by improving predictions of drug properties and enabling collaboration among biopharmaceutical companies while protecting their competitive interests.
Ginkgo Bioworks has announced a strategic partnership with Alphabet to utilize artificial intelligence (AI) in its biological engineering services, aiming to improve efficiency, but the collaboration alone does not make the stock a buy, as Ginkgo still faces challenges in proving its viability and achieving profitability.
