This AI-powered machine turns photos into smells
Picture a memory from childhood, one that feels real and nostalgic, but somehow just out of grasp: perhaps a family trip to the beach, or a moment mid-swing on the playset, or an afternoon spent hunting for four-leaf clovers. Now, imagine that you could bottle that golden moment into a fragrance.
One scientist at MIT, Cyrus Clarke, is working to do just that. Alongside a team of fellow researchers, Clarke has developed a physical machine called the Anemoia Device, which uses a generative AI model to analyze an archival photograph, describe it in a short sentence, and, following the user’s own inputs, convert that description into a unique fragrance.
The word “anemoia” was coined by author John Koenig and included in his 2021 book, The Dictionary of Obscure Sorrows. It refers to a specific feeling of nostalgia for a time or place that one never actually experienced themselves—and it’s exactly what Clarke’s team hopes to capture with the Anemoia Device.
According to a paper published by the team, the device explores the concept of “extended memory,” or the idea that, in the digital age, memory is increasingly stored and accessed through external media, like digital archives.
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Studies have already shown that memory can be formed vicariously—like when a second-hand account, perhaps from a parent, shapes one’s own memories—but the Anemoia Device is a delightfully physical, interactive experiment into how AI might allow users to experience a memory of a past they never actually lived.
[Photo: Cyrus Clarke/courtesy MIT Media Lab]The Anemoia Device
The Anemoia Device looks like something that one might find in the medical bay of a retro sci-fi spaceship. It’s a slim, metal-and-plastic contraption accented with a singular neon green screen and a simple array of three physical dials. At the bottom, a glass beaker waits to catch the final fragrance.
[Photo: Cyrus Clarke/courtesy MIT Media Lab]To start, a user inserts a photograph into the device. A built-in vision-language model (VLM) analyzes the image and generates an initial caption based on what it finds. For a picture of tourists in China, an example used in the paper, the device might write, “A tourist in black shorts and a child pose in the doorway along the Great Wall of China, with the iconic stone steps and mountainous landscape stretching up toward the sky.”
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