Plus, AI Professors: Scoring Straight A’s in Teaching College Students
AI is used to create more sophisticated and convincing scams. Fraudsters are using AI to generate fake websites, emails, and social media posts that look like they come from legitimate companies. They are also using AI to automate tasks such as customer service and support, making it more difficult for victims to identify them.
Insilico Medicine, a biotech startup in Hong Kong, has developed the first fully AI-generated drug, INS018_055, which is being tested in clinical trials for the treatment of idiopathic pulmonary fibrosis (IPF). IPF is a chronic condition that causes scarring in the lungs and can be fatal if left untreated. The drug was created through a discovery process that began in 2020 with the aim of overcoming the limitations of current treatments for IPF. The drug is unique in that it not only targets a novel site but also has a design generated by AI. Insilico Medicine has two other drugs partially generated by AI in clinical stages, including a Covid-19 drug in phase one trial and a cancer drug recently approved by the FDA for clinical trials. The current trials for the IPF drug are taking place in China, with plans to expand to the US and China. If successful, the drug could reach the market in the next few years.
Microsoft released the first public preview of Windows 11’s Copilot, an AI-powered assistant that can help users with tasks. Copilot is designed to work in the background, providing suggestions and completing tasks as users type. It can be used for various tasks, including writing code, creating documents, and editing spreadsheets.
A group of AI researchers and experts have written an open letter to the European Commission, warning that the draft EU artificial intelligence (AI) rules could hurt Europe’s AI industry. The letter argues that the rules are too restrictive and will make it difficult for European companies to compete with those from other countries.
A new study suggests that machine learning can help people with depression by reducing rumination. Rumination is the tendency to dwell on negative thoughts and feelings, and it is a common symptom of depression. The study found that people who used a machine learning-based app to track their thoughts and feelings reported reduced rumination and improved mood.
In a recent essay for Vanity Fair, author Ted Chiang discusses how we should think about AI. Chiang argues that we should not view AI as a threat but as a tool that can be used for good or evil. He also cautions against anthropomorphizing AI, which can lead to unrealistic expectations.
A new study suggests that AI-powered talk therapy could be used to detect the earliest symptoms of dementia. The study found that AI could identify people with dementia by analyzing their speech patterns. The AI was able to detect dementia with 80% accuracy, even in people who had no other symptoms.
Harvard University will be rolling out AI professors in its flagship coding class for the fall semester. The AI professors will help students learn the basics of coding and provide feedback on their work. The program is still in its early stages, but it has the potential to revolutionize how coding is taught.
The widespread adoption of AI by companies will take a while, according to a new report from The Economist. The report found that only a small percentage of companies currently use AI at scale. The report also found that companies face many challenges in adopting AI, such as a lack of skilled workers and the high cost of AI technology.
Experts warn that AI-powered coding tools could harm people’s jobs. The experts argue that these tools are becoming increasingly sophisticated and could eventually automate many of the tasks that human coders currently do. They are calling on governments and businesses to take steps to mitigate the potential negative impact of AI on jobs.
AI is facing a new challenge: digital dark matter. Digital dark matter is the vast amount of data that is not easily accessible or searchable. This data includes everything from user activity on social media to the contents of encrypted files. AI researchers are working on ways to make sense of digital dark matter, but it is challenging for AI because it is difficult to collect and process. This data is often hidden or encrypted, making it difficult for AI systems to access. Additionally, digital dark matter constantly changes, making it difficult for AI systems to keep up.