3 big AI trends to watch in 2024
In his Dec 2023 blog post about AI, Microsoft cofounder Bill Gates said: “We are just at the beginning of this transition right now. This is an exciting and confusing time, and if you haven’t figured out how to make the best use of AI yet, you are not alone.”
“Think back to the beginning of the internet. At first, you probably didn’t know many people who were using it, but it became more common over time. Most people had email addresses, bought things online, and used search engines to answer their questions,” he added.
2023 was a major year for generative AI, as it went from research labs to real life with millions of people using it through popular tools like ChatGPT and Microsoft Copilot. This year, AI is expected to become more accessible, nuanced and integrated in technologies that improve everyday. Here are three important AI trends to keep an eye on in 2024:
Small language models
SLMs are still quite large with several billion parameters — in contrast to hundreds of billions of parameters in LLMs — but they’re small enough to run on a phone offline. Parameters are variables, or adjustable elements, that determine a model’s behavior.
“Small language models can make AI more accessible due to their size and affordability,” says Sebastien Bubeck, who leads the Machine Learning Foundations group at Microsoft Research. “At the same time, we’re discovering new ways to make them as powerful as large language models.”
Microsoft researchers have developed and released two SLMs — Phi and Orca— that perform as well as or better than large language models in certain areas, challenging the notion that scale is required for performance.
Multimodal AI
Most LLMs can process only one data type — text — but multimodal models can understand information from different data types like text, images, audio and video. This capability is making technologies from search tools to creativity apps richer and more accurate and seamless.
Multimodal AI is also powering Microsoft Designer, a graphic design app that can generate images based on a description of what you want. And it enables custom neural voices, or natural-sounding voices useful in text readers and tools for people with vocal disabilities.
AI in science
Experts are anticipating major gains in AI tools designed to speed up scientific discoveries, with much of address climate change, energy crises and diseases. In life sciences, researchers are collaborating on the world’s largest image-based AI model to fight cancer and using advanced AI to find new drugs for infectious diseases and new molecules for breakthrough medicines. The technology is compressing scientific trial and error — work that can take years — into just a few weeks or months.
