--- title: "Scientists Gave AI an “Inner Monologue” and Something Fascinating Happened" description: "Researchers taught an AI to think before it speaks like a human's inner monologue — and found that it made the model smarter." date: "2024-03-20" modified: "2024-03-20" authors: - name: "Noor Al-Sibai" job_title: "Senior Staff Writer" link: "https://futurism.com/authors/nooralsibai" url: "https://futurism.com/the-byte/ai-inner-monologue" categories: - "Artificial Intelligence" tags: - "advanced ai" - "artificial intelligence" - "llms" - "the digest" --- # Scientists Gave AI an “Inner Monologue” and Something Fascinating Happened ![Researchers taught an AI to think before it speaks like a human's inner monologue — and found that it made the model smarter.]() *\Image: Getty / Futurism\* ## Therefore AI Am If you give an AI an inner monologue, it apparently starts teaching itself to be smarter. In a [not-yet-peer-reviewed paper]() researchers from Stanford and a group calling itself "Notbad AI" have teamed up to create an AI model that pauses to "think" before spitting out answers, shows its work, and asks users to tell it which response is most correct. The team behind the Quiet Self-Taught Reasoner, or Quiet-STaR for short, wanted their model to not only be able to teach itself to reason — which they achieved in 2022 with the original [Self-Taught Reasoner algorithm]() — but also to do so "quietly" before providing answers to prompts, thus operating like a human's inner monologue that, ideally, runs before we speak. "Excitingly," as Stanford's Eric Zelikam enthused in an [X-formerly-Twitter thread]() about the new model he helped produce, "self-teaching reasoning on diverse web text automatically improves other reasoning!" ## If You Build It To create this contemplative AI, the research team built Quiet-STaR on Mistral 7B, an open-source large language model (LLM) that is, according to the [Hugging Face AI community](), trained on seven billion parameters and said to be able to outperform the latest version of Meta's Llama model. Quiet-STaR was programmed, essentially, to show its work when giving reasoning for its outputs, and users of the model were then able to select which response was most accurate. This approach, as the paper notes, resulted in the model being accurate 47.2 percent of the time — which isn't particularly impressive, but an improvement from the 36.3 percent it got without the additional reasoning training. While the model still performed abysmally low on math, getting only 10.9 percent of the questions right, the pre-trained Quiet-STaR only got 5.9 percent of the questions right, which means that it doubled its math prowess during its training. None of these results are blowing us away. But they're intriguing because, to date, chatbots like OpenAI's ChatGPT and Google's Gemini have been terrible at common-sense reasoning. Quiet-STaR, the researchers propose in their paper, could lead to leaps that "close the gap between language model and human-like reasoning capabilities." Could that sort of thing be what [OpenAI's sitting on]() with its mysterious and shockingly similarly-sounding Q\* (pronounced "queue star") model? Only time will tell. **More on AI advances:** [*State Department Report Warns of AI Apocalypse, Suggests Limiting Compute Power Allowed for Training*]() ## Author At Futurism, I've often been drawn to unpacking the narratives that underlie technological, scientific and medical progress, with a special interest in areas of conflict and ambiguity that end up setting agendas and steering the fates of both elites and the hoi polloi. I'm a committed generalist, but I often find myself returning to work involving NASA and the private space sector, the effects of AI on media and society, and the mechanics of the pharmaceutical industry, with a specific focus on the spread of GLP-1 drugs like Ozempic and Wegovy. Prior to Futurism, I worked for publications ranging from Media Matters and Truthdig to Raw Story and Bustle. I'm also the author of "Myspace Scene Queens," a 2024 title in Instar Books' acclaimed "Remember the Internet" series. My work at Futurism has been cited by outlets including the New Yorker, Slate, Nieman Lab, the Verge, the MIT Technology Review, the Sunday Times, and the Daily Beast. I grew up in North Carolina, attended the University of North Carolina at Asheville, and now live in Brooklyn, New York. In my free time, I'm an avid reader and music fan; you can probably find me at a local poetry reading, concert, underground rave, or DJ set. I'm the proud parent of an ineffable orange cat named Mee-Mow. ### Author social links [Bluesky]()