Lollipop-Shaped Device for VR Taste

Researchers at the City University of Hong Kong have developed a new interface to simulate taste in virtual and other extended reality (XR). The lollipop-shaped lickable device can produce nine different flavors: sugar, salt, citric acid, cherry, passion fruit, green tea, milk, durian, and grapefruit. Each flavor is produced by food-grade chemicals embedded in a pocket of agarose gel. When a voltage is applied to the gel, the chemicals are transported to the surface in a liquid that then mixes with saliva on the tongue like a real lollipop. Increase the voltage and get a stronger flavor.

Initially, the researchers tested several methods for simulating taste, including electrostimulating the tongue.  The other methods each came with limitations, such as being too bulky or less safe, so the researchers opted for chemical delivery through a process called iontophoresis, which moves chemicals and ions through hydrogels and has a low electrical-power requirement. With a 2-volt maximum, the device is well within the human safety limit of 30 V, which is considered enough to deliver a substantial shock in some situations.

More information:

https://spectrum.ieee.org/virtual-reality-taste

AI in Agronomy and Crop Protection

Microsoft today announced it is working with the German pharmaceutical-and-agricultural group and other companies on specialized AI models fine-tuned on industry-specific data. The companies can now list and monetize those models on Microsoft’s online model catalog. For Bayer that means an AI model fine-tuned with its data and designed to provide answers on agronomy and crop protection is available to be licensed by its distributors, new AgTech startups, and even potentially competitors.

The model can answer questions about ingredients in an insecticide or whether a product could be applied to cotton, for example. Microsoft expects this new approach, built on its Phi family of small language models and preloaded with industry knowledge, will accelerate enterprise generative AI adoption, a yearslong effort built on the understanding that off-the-shelf AI models often don’t cut it for business needs. Companies now find it critical to augment today’s general models with more industry-specific or business-specific data if they’re going to be useful.

More information:

https://www.wsj.com/articles/bayer-microsoft-generative-ai-90754f54

E-Nose

Researchers built an e-nose that can not only detect odors at the same speed as a mouse’s olfactory system, but also distinguish between odors by the specific patterns they produce over time when interacting with the e-nose’s sensor.

The e-nose uses metal oxide gas sensors with a sensing surface heated and cooled to between 150 °C and 400 °C at up to 20 times per second. Redox reactions take place on the sensing surface when it comes into direct contact with an odorant.

More information:

https://spectrum.ieee.org/electronic-nose