The AI2050 Early Career Fellowship, established by Schmidt Sciences, supports postdoctoral and pre-tenure researchers tackling ambitious, multidisciplinary challenges in artificial intelligence (AI). The 2024 cohort comprises 19 fellows from institutions such as MIT, Oxford, and Stanford. Each fellow receives up to $300,000 over two years, along with access to a global network of experts to advance their research.​

Governor Kathy Hochul announced a $20 million public-private investment aimed at advancing artificial intelligence (AI) research and development in New York State. This initiative involves a collaboration between the University at Albany and IBM to establish the Center for Emerging Artificial Intelligence Systems. The center is designed to promote innovation and attract AI companies to the region, thereby creating jobs and bolstering the state's position as a leader in AI research.

A recent Newsday article titled "Unregulated artificial intelligence: Issue raises concern among NY scientists" discusses the growing concerns among New York scientists about the potential risks associated with unregulated artificial intelligence (AI). The article highlights that hundreds of academics and tech executives have signed a statement warning that AI poses a "risk of extinction," citing dangers such as weaponization and unforeseen consequences.​

The piece also emphasizes the need for regulatory measures to ensure that AI development is conducted responsibly and ethically. Experts argue that without proper oversight, the rapid advancement of AI technologies could lead to unintended and potentially catastrophic outcomes.​

The article underscores the importance of collaboration between scientists, policymakers, and industry leaders to establish frameworks that govern AI development and mitigate associated risks.

A study by Stony Brook University, published in Nature Digital Medicine, demonstrates that artificial intelligence (AI) can assess community mental health by analyzing social media language. The research analyzed over 1 billion tweets from 2019 to 2020 across more than 1,400 U.S. counties, identifying spikes in anxiety and depression during events like the COVID-19 pandemic and the George Floyd protests. The AI's findings closely matched those of traditional surveys, offering a more timely and cost-effective method for monitoring public mental health.