Recent AI Developments Special Librarians Should Know About

I write extensively about artificial intelligence, and keeping up with the field is a constant challenge. In this post, I would like to highlight two significant recent developments in AI that deserve attention: Test-time compute and OpenAI’s Deep Research. Both of these developments are setting the stage for faster, smarter, and more efficient workflows.

Test-time Compute

According to ChatGPT, test-time compute “refers to the computational resources and time required to make predictions (or inferences) using a trained machine learning model. It is a critical factor in real-world applications where models need to perform efficiently under constraints such as latency, power consumption, and hardware limitations.”

In other words, if the question posed to the AI is difficult, it allocates more resources to answering the question. If the question posed to the AI is easy, it allocates fewer resources to answering the question and the answer will come quicker.

If you’d like to learn more about how GenAI tools use test-time compute, here are a few resources to explore:

• Computers Are Now Thinking Hard: Next-Level AI and Test-Time Scaling (Forbes)
• Google DeepMind researchers think they found a solution to AI’s ‘peak data’ problem (BusinessInsider)

OpenAI’s Deep Research

Deep Research from OpenAI will likely change the research landscape even more. It is described as “An agent that uses reasoning to synthesize large amounts of online information and complete multi-step research tasks for you.” The description continues by stating, “… you give it a prompt, and ChatGPT will find, analyze, and synthesize hundreds of online sources to create a comprehensive report at the level of a research analyst.”

In a recent podcast episode, Ezra Klein, NYTimes Opinion Columnist, said what Deep Research “produced in a matter of minutes was at least the median of what any of the teams I’ve worked with on this could produce within days.”

Deep Research is currently limited to Pro subscribers, though it will eventually be accessible to users on other tiers. This tool will likely transform how both individuals and information professionals conduct their research. The AI technology landscape is evolving at a remarkable pace. While earlier iterations raised significant concerns about factual inaccuracies and fabricated information, advanced research tools are addressing these reliability issues. These solutions are seeing rapid improvements, offering increasingly efficient and precise resource discovery and evaluation capabilities.

Keeping Up with the Latest in AI

With tools such as Deep Research and the growth of AI capabilities regarding time and resource allocation, it will be important for special librarians and other information professionals to determine how best to incorporate these tools into their own work and how to help others use these tools as well.