In July of the previous year, Naver, often dubbed as the “Google of South Korea,” unveiled its new second headquarters, Naver 1784, which pays homage to the Industrial Revolution’s landmark year. What sets this building apart is the presence of 100 autonomous robots known as “Rookies” that seamlessly navigate through the premises, offering services like parcel delivery, coffee dispensing, and lunch delivery to Naver’s employees—all powered by 5G connectivity. These robots even have their dedicated elevator, aptly named Roboport. Naver Labs, the company’s research and development division, is using the headquarters as a testing ground for these robotic marvels and plans to deploy them in its new data center, Gak Sejong, in South Korea this November.

As a multifaceted internet giant, Naver has delved into various domains, including e-commerce, messaging, payments, digital comics, cloud services, and the metaverse. Recently, the company launched generative AI services based on its substantial language model, HyperClova X, joining the race in the generative AI arena. Naver’s exploration into robotics, artificial intelligence, and autonomous driving technology suggests a broader vision for its future growth.

For nearly two decades, the opioid epidemic has confounded researchers, posing a complex challenge as they strive to comprehend the evolving social and systemic factors driving opioid abuse and identify areas susceptible to overdose incidents. This dilemma persists while clinicians work tirelessly to provide effective treatment and support to those grappling with addiction. However, as both researchers and healthcare professionals continue to grapple with the opioid crisis, there’s a growing curiosity: Can Artificial Intelligence (AI) be the moonshot solution that finally brings an end to this devastating epidemic?

The healthcare industry isn’t typically quick to embrace new technology, often lagging behind in the adoption of advanced tools like electronic health records. This reluctance comes at a significant cost, with the industry reportedly losing over $8.3 billion annually due to this delay. Yet, the toll of the opioid epidemic extends far beyond financial losses. Since 1999, over one million lives have been lost to drug-related overdoses. In 2021 alone, America witnessed 106,699 drug overdose deaths, marking one of the highest per capita volumes in the nation’s history. Alarmingly, around 75% of these overdoses were attributed to opioids, including prescription painkillers such as Vicodin and Percocet, along with illicit drugs like heroin.

In a groundbreaking effort to transform patient management and optimize healthcare resource allocation during severe viral outbreaks, a cutting-edge platform harnessing the power of machine learning and metabolomics data has been unveiled. This innovative approach aims to alleviate the strain on local healthcare systems, which often become overwhelmed during epidemics. Metabolomics, a branch of science focused on investigating small molecules associated with cellular metabolism, plays a pivotal role in this endeavor.

According to the senior author of the study, Vasilis Vasiliou, a professor of epidemiology at Yale University School of Public Health, “Being able to predict which patients can be sent home and those possibly needing intensive care unit admission is critical for health officials seeking to optimize patient health outcomes and use hospital resources most efficiently during an outbreak.”

As the urgency of addressing climate change intensifies, fusion energy emerges as a promising clean energy solution. Despite decades of laboratory research on fusion reactions, several crucial questions remain unanswered to make fusion power a reality. In pursuit of carbon neutrality by 2050, the U.S. Department of Energy (DoE) has allocated new funding for a project led by researchers at MIT’s Plasma Science and Fusion Center (PSFC) and four collaborative institutions.

Cristina Rea, a research scientist and group leader at PSFC, assumes the role of primary investigator for this three-year collaboration aimed at integrating fusion data into a format compatible with AI-powered tools. Working in conjunction with scientists from William & Mary, the University of Wisconsin at Madison, Auburn University, and the nonprofit HDF Group, the project’s objective is to create a comprehensive fusion data platform that fosters inclusivity in research and data science. The initiative prioritizes outreach programs led by co-investigators, with four out of five being women, to encourage diverse participation in fusion research.

The debate on whether artificial intelligence (AI) is a boon or a bane for humanity is more divisive than ever. According to a recent survey by Maveron and A/B Consulting, Americans are evenly split, with 37% expressing excitement about AI and 40% harboring fear. The potential impact is similarly divisive, with 39% believing AI will make humans obsolete and 41% rejecting that notion.

As history has shown with previous technological advancements, the truth about AI likely lies somewhere in the middle. The outcome largely depends on how we use this technology and who wields it.

In this crucial moment, we collectively bear the responsibility of shaping AI’s role in transforming business and society. We must be discerning when embracing AI applications and allocate our resources wisely, be they technological, financial, or emotional.