The remarkable progress in artificial intelligence (AI) over recent years can largely be attributed to one factor: scale. Around the beginning of this decade, researchers noticed that as they increased the size of their algorithms and fed them more data, the capabilities of AI models skyrocketed. The latest AI models, boasting hundreds of billions to over a trillion network connections, are learning to write, code, and process information by ingesting vast amounts of data—essentially a large fraction of the internet.

This scaling, however, demands enormous computing power. According to nonprofit AI research organization Epoch AI, the computing power dedicated to AI training has been quadrupling every year. Should this trend continue, by 2030, AI models could be trained with up to 10,000 times more compute than today’s cutting-edge models, such as OpenAI’s GPT-4. This would represent a leap as significant as the difference between GPT-2’s rudimentary text generation in 2019 and GPT-4’s advanced problem-solving abilities in 2023.

After the 2014 failure of Google Glass, smart glasses seemed doomed to obscurity. However, a resurgence may be on the horizon, as companies like Meta and Google invest heavily in a new generation of smart glasses that blend fashion, functionality, and generative AI, according to Gene Munster, managing partner at Deepwater Asset Management.

Writing on the firm’s website, Munster explained the renewed optimism in smart glasses, stating that consumers are drawn to easy-to-use technology, and the advancements in generative AI are transforming these devices into a more attractive option. “Gen AI is paving the way toward complex wearable ambient computing,” he noted. This next iteration of smart glasses aims to look and feel like “normal glasses,” while incorporating generative AI, voice activation, cameras, and sensors for a seamless user experience.

In a groundbreaking advancement in artificial intelligence, Google is leveraging audio signals to detect the early symptoms of illness. Using 300 million audio samples—ranging from coughs to labored breathing—Google has trained its AI foundation model to recognize signs of diseases like tuberculosis. In collaboration with Salcit Technologies, an AI startup in India focused on respiratory healthcare, Google is working to integrate this technology into smartphones. This innovation has the potential to transform healthcare in high-risk, underserved communities by offering more accessible diagnostic tools.

Google has a history of digitizing human senses, and its venture into bioacoustics is an extension of that. Bioacoustics, which merges biology and acoustics, uses AI to interpret sounds made by humans and animals to gain medical insights. In this field, Google’s new AI model, HeAR (Health Acoustic Representations), stands at the forefront. This model utilizes sound signals to detect early signs of illness, offering a promising tool for early diagnosis.