A large language model (LLM) is a learning algorithm that can carry out tasks associated with natural language processing. Various studies have been examining how these models can be used to automate research tasks, with some looking into whether they can generate new ideas at a level similar to humans.
Now, a recently posted preprint shows that an idea generator powered by AI produced more original ideas for research than 50 researchers who were working independently. The project was carried out over a one-year period. The objective was to evaluate if LLMs could come up with innovative ideas.
For their study, the researchers recruited more than 100 investigators in natural language processing, which focuses on communication between humans and artificial intelligence. The researchers then tasked 49 participants with developing ideas based on one of seven topics in a 10-day period. To incentivize the participants, they awarded $300 to the participants for each idea. They also gave a $1,000 bonus for the five ideas with the best scores overall.
On the AI side, the researchers built an idea generator using Claude 3.5, then prompted the tool to find papers relevant to the aforementioned topics using a literature search engine powered by artificial intelligence.
The AI and human-generated ideas were assessed by reviewers who weren’t informed who or what had generated each idea. The researchers also standardized the tone and style of writing to make it harder for reviewers to pick out what idea was generated by whom. The reviewers were required to award scores to each idea based on its expected effectiveness, feasibility, excitement, and novelty.
In their reports, the reviewers gave higher marks to concepts generated by artificial intelligence, with some claiming that they were more exciting and original. Suggestions given by AI did receive lower scores on feasibility, however.
When asked, the human participants admitted that the ideas they had submitted were average in comparison to their previous works.
The study had several limitations, among them the fact that it required human participants to originate ideas on the spot, which may have hampered their ability to come up with better concepts. Additionally, the research only centered on one area of study.
The researchers are now planning to compare ideas generated by AI with leading papers to better understand how LLMs compare to human creativity. The study was carried out by Chenglei Si, Tatsunori Hashimoto and Diyi Yang. Its findings were posted on arXiv.
As companies such as D-Wave Quantum Inc. (NYSE: QBTS) continue their focus on AI and quantum computing, these technologies could outperform humans more specialties in the coming years.
NOTE TO INVESTORS: The latest news and updates relating to D-Wave Quantum Inc. (NYSE: QBTS) are available in the company’s newsroom at https://ibn.fm/QBTS
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