  AI and generative AI tools, including chatbots like ChatGPT that rely on
large language models (LLMs), have burst onto the scene this year, creating
incredible opportunities to increase work productivity and improve our lives.
Statisticians and data scientists have begun experiencing the benefits from the
availability of these tools in numerous ways, such as the generation of
programming code from text prompts to analyze data or fit statistical models.
One area that these tools can make a substantial impact is in research
discovery and summarization. Standalone tools and plugins to chatbots are being
developed that allow researchers to more quickly find relevant literature than
pre-2023 search tools. Furthermore, generative AI tools have improved to the
point where they can summarize and extract the key points from research
articles in succinct language. Finally, chatbots based on highly parameterized
LLMs can be used to simulate abductive reasoning, which provides researchers
the ability to make connections among related technical topics, which can also
be used for research discovery. We review the developments in AI and generative
AI for research discovery and summarization, and propose directions where these
types of tools are likely to head in the future that may be of interest to
statistician and data scientists.
