AI and Machine Learning: Smell and Touch Research
To have a broad understanding of how artificial intelligence (AI) and machine learning is used to predict the smell or touch (feel) of a product. An ideal response would be a report or a list if academic research surrounding the sensory analysis and machine learning/AI area.
- In October 2019, Google Brain released a paper on the preprint site Arxiv showing how they trained a set of machine-learning algorithms to predict molecules’ smell based on their structures.
- Google Brain concluded: "Within the realm of machine learning, smell remains the most elusive of the senses, and we’re excited to continue doing a small part to shed light on it through further fundamental research. The possibilities for future research are numerous, and touch on everything from designing new olfactory molecules that are cheaper and more sustainably produced, to digitizing scent, or even one day giving those without a sense of smell access to roses (and, unfortunately, also rotten eggs). We hope to also bring this problem to the attention of more of the machine learning world through the eventual creation and sharing of high-quality, open datasets."
- "There have been previous attempts to use machine learning to detect patterns that make one molecule smell like garlic and another like jasmine. Researchers created a DREAM Olfaction Prediction Challenge in 2015. The project crowdsourced scent descriptions from hundreds of people, and researchers tested different machine-learning algorithms to see if they could train them to predict how the molecules smell."
- "Several other teams applied AI to that data and made successful predictions."
- The problem with how AI understands smell is perception. In other words, it could be two very different things. Two molecules may smell differently, yet even trained noses will label them both as “woody” or “earthy.” “It’s a big caveat,” according to Alex Wiltschko, a researcher with Google Brain.
- "At an AI exhibit at London's Barbican Centre early in 2019, scientists used machine learning to recreate the smell of an extinct flower."
- In Russia, AI is being used to sniff out potentially deadly gas mixtures.
- IBM is experimenting with AI-generated perfumes.
- Some have even toyed with using our sense of smell to reimagine how we design machine learning algorithms.
- A new study, published July 28th, 2020 in Science Daily, reveals that a team of two researchers have used machine learning to understand what a chemical smells like. They call this a research breakthrough with potential applications in the food flavor and fragrance industries.
Summary Of Our Early Findings Relevant To The Goals
- Our initial hour of research returned several examples of how artificial intelligence (AI) and machine learning is being leveraged to predict the smell of a product.
- Despite extensive searching, absolutely nothing was uncovered surrounding how artificial intelligence (AI) and machine learning is being leveraged to predict the touch (we assumed was the feel) of a product. We are not proposing any further research for this.
- Please select one or more of the options provided in the proposed scoping section below.
Proposed next steps:
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