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Engineers develop bio-machine nose that can “sniff” and classify odors
Engineers from Brown University in Rhode Island have invented a small, low-cost sensor device which is able to classify odors using input from a mimicked “sniffing” action. It’s called TruffleBot, and it’s here to raise the bar on electronic “noses”. It also works with Raspberry Pi, an inexpensive mini-computer popular with electronics hobbyists, students, and others in the “maker” crowd.
Generally, an electronic nose is a device comprising several chemical sensors whose results are fed through a pattern-recognition system to identify odors. In traditional devices, the chemical responses alone are used for classification. The engineers behind this invention, however, decided to incorporate non-chemical data to account for the mechanics of the smell process used in nature for a better result. Their experiment proved successful with an approximate 95-98% rate of accuracy in identification compared to about 80-90% accuracy with the chemical sensors alone.
According to the inventors’ published paper, the guiding knowledge that made TruffleBot so useful in odor detection was this: Different smells have different impacts on the air around them, and measuring the variations enables more accurate identification. Did you know that beer odor decreases air pressure and increases temperature? The changes are slight, but TruffleBot can sense them.
This is where the “sniffing” comes in. The device uses air pumped through four obstructed pathways before sending it through chemical and non-chemical sensors. Odors impact the air surrounding them, and the movement of the air through obstacles (“sniffing”) enables the odors’ impact to be more accurately measured.
A chart detailing how TruffleBot processes odors. | Credit: Brown University
So, where exactly would one need an electronic nose? Everywhere. Devices with the chemical sensing ability are being used in agriculture, military, and commercial applications to identify all sorts environmental data. Essentially, electronic noses are useful in any industrial application that has odor involved.
Nasal Marketing
Did you know that it’s possible to trademark a smell in the United States? It’s not easy to accomplish given the somewhat difficult requirements to meet, but a few such things exist. The fact that Play-Doh, a product whose smell is probably one of its most distinct features, was granted a trademark for the scent only this year is testament to the difficulty of obtaining such a mark. However, the fact that some companies have found enough incentive to make sure only their company can give your nose a particular chemical experience tells a lot about that sense’s importance from a marketing perspective.
On one hand, utilizing smell in marketing might seem a little manipulative. After all, creating an air freshener that reminds someone of a beloved, deceased relative on purpose might not seem like a particularly ethical way to target their money. On the other hand (or bigger picture), however, the motivation for marketers to use scent as a tool involves a sort of “chicken or the egg” question.
To summarize part of an article in the journal Sensors on the role scent plays in society and commerce, the aroma of products has a direct impact on their appeal to customers and thus, the success of the product. In fact, a change in a product’s formula that impacts its smell can, and often has had, devastating sales results. In other words, it’s not enough for a company to create a good product; it has to be a good smelling product.
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Hacking the Human Nose
It’s probably no surprise that the commercial industry has categorized consumer preferences when it comes to smells. As the first sense fully developed after birth, our noses link us to things like memories, emotions, and chemical communication (think pheromones). Is it any wonder, then, why businesses might be interested in the functionality of the organ that is doing the receiving?
Turns out, there’s an enormous amount of science behind “hacking” a nose. Identifying smells is more than just categorizing chemical mixtures as “floral” or “masculine”. The multitude of chemical combinations available generates such a vast amount of data that scientists have implemented computer neural networks to analyze and classify it. Also, the actual mechanics of smelling something impacts the way the smell is received and processed in the brain. Computers and scientific instruments come in handy there as well. To really get to the core of human response to an aroma, lots of non-human tools are needed, and this is essentially where the TruffleBot fits in the greater realm of “olfactory” science.
I think this is a Sumerian variant for “fruity”. | Credit: AstroJane’s bathroom collection.
More Than Just Your Money
Perhaps one of the most innovative uses found for electronic noses is in disease research. One of the limitations of human smell is its overall weakness. A dog’s sense of smell is around 40 times better than a human’s, and a bear’s is a whopping 2,100 times superior to ours. That said, when researchers learned that certain diseases give off certain odors, the human nose wasn’t exactly the first choice to utilize in sensing them.
An electronic nose makes good use of the simple fact that organic matter releases chemicals into the air. For example, when a plant has been impacted by a fungus, the changes brought on in the plant’s structure release what’s called “volatile organic compounds” (VOCs). These VOCs can be detected by the sensors in an electronic nose and then provide information on the type of disease present without destroying the plants being tested.
Humans have some amazing things to gain from electronic noses, too. Using sensors to process odors from VOCs, things like digestive diseases, kidney diseases, and diabetes, among many others, are all receiving scientific attention for non-invasive diagnosis by these types of devices. With improvements brought on by inventions like TruffleBot, especially combined with its low-cost and resulting accessibility, a future involving remote diagnoses for any number of illnesses and diseases seems more possible every day.
SpaceX’s massive investment in AI will make it a big winner, Argus Research said after the company’s successful earnings call last week.
The firm also upgraded shares to a Buy from Hold and set a $160 price target.
SpaceX (NASDAQ: SPCX) is currently recovering from its heavy AI infrastructure investments, as it spent nearly $16 billion in Q2 alone. The company did this primarily by monetizing high-demand GPU compute capacity at a much faster pace than traditional data center economics would suggest.
Company CFO Bret Johnsen said that SpaceX would be able to pay back anything on new deployments within a year.
There are plenty of ways the company can do this:
Leasing excess compute capacity through contracts
SpaceX has already built Colossus and Colossus II, largely for its own model training. However, much of that capacity is already rented out to third parties. It already has major deals with Anthropic, Google, and Reflection AI. These partnerships are adding billions per month to SpaceX’s spreadsheet.
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High utilization driven by industry-wide scarcity
The demand for advanced AI training and inference capacity continues to exceed what is available for use. SpaceX can fill new racks quickly after they come online, so the capital deployed converts into revenue with minimal idle time.
Additionally, management and outside observers have described the new compute capital as behaving more like a cost-of-goods-sold than traditional multi-year capex, especially because of this rapid monetization pattern.
Capacity has already scaled from ~0.4 GW a year to 1.4 GW annually by the end of Q2. There are targets of more than 2 GW by year-end.
High incremental margins on the rental business once capacity is online
GPU cloud providers often operate at strong gross margins. SpaceX can monetize capacity that was already partially built or can be added efficiently. This means that incremental EBITDA margins on the rental revenue are usually high. This accelerates cash recovery relative to the gross capital outlay.
Parallel monetization of its own AI software and applications
Beyond pure infrastructure rental, SpaceX also generates revenue from Grok through subscriptions and usage, from X through ads, data, and other related services, enterprise APIs, and the planned integration of the Cursor coding tools acquisition.
These application layers ride on the same compute infrastructure and provide additional high-margin streams that could offset build-out costs. AI-segment revenue overall rose sharply to about $2.6 billion in Q2, according to Motley Fool. This was driven primarily by the infrastructure contracts, but the software side is also partially responsible.
Efficient, large-scale deployment and vertical integration advantages
SpaceX has emphasized the rapid construction of power and cooling infrastructure and favorable cost-per-megawatt economics relative to industry benchmarks in some disclosures.
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Combined with its ability to scale capacity aggressively and the fact that many contracts start generating revenue within months of capacity coming online, the effective payback compresses dramatically compared with more conventional multi-year data-center projects.
SpaceX’s dominant near-term recovery path will turn the AI clusters into a hyperscale-style compute rental business for other leading AI companies while still using a portion for internal models.
Tesla headlights have caused a recall of over 20,000 of the company’s two most popular vehicles, the Model 3 and Model Y, due to the low-beam bulb exceeding the maximum allowed intensity according to federal standards.
Tesla initiated the recall with the National Highway Traffic Safety Administration (NHTSA) this morning, stating that the low-beam output “exceeds the maximum allowed intensity in the outer upper-right and outer upper-left areas of the 10U and 90U zone, as prescribed in FMVSS No. 108.”
Tesla sourced the impacted headlights from Marelli Automotive Lighting, a Mexico-based company. The recall impacts 2020-2023 Model Y vehicles and 2017-2023 Model 3 vehicles. It is estimated that every VIN in this recall is impacted by the defect.
🚨 Tesla is recalling 20,349 2020-23 Model Y vehicles and 2017-23 Model 3 vehicles due to an excessively bright headlamp low beam.
Currently, there is no remedy plan in place, as it is still being developed. pic.twitter.com/y34cIO2U0B
— TESLARATI (@Teslarati) August 11, 2026
Typically, Tesla would remedy recalls of this nature through an Over-the-Air software update, which has been a major focus of criticism by the company and its supporters because the NHTSA still refers to it as a “recall,” even though it requires no action by the vehicle owner. The fix is shipped over the internet and downloaded to the car.
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However, there appears to be a potentially different solution for this problem. Tesla has not developed a remedy for this issue, so it could potentially be on the way. The big issue appears to be the fact that these recalled lamps are out of production, and this is an old body style for both vehicles. The headlights and front-end designs are completely different.
Tesla switched to another supplier when the affected headlight design was discontinued. It plans to begin notifying owners of their remedy options by September 15.
Tesla filed a petition protesting the recall to fix the vehicles’ headlight issue, but the NHTSA denied it. Now, Tesla will come up with a solution to fix it.
Elon Musk
Another Tesla SpaceX merger prediction by ARK Invest has Elon Musk talking
Elon Musk again denies a Tesla China split as new SpaceX merger speculation resurfaces quickly.
Elon Musk restated that Tesla has no plans to separate its China business from the rest of the company, responding to a new round of merger speculation from ARK Invest.
On the firm’s “Brainstorm” podcast, Cathie Wood’s team, including chief futurist Brett Winton and research director Nick Grous, argued a Tesla and SpaceX combination remains likely, with an announcement possible before the end of the year even if the deal itself would not close that quickly. Winton called Tesla’s Shanghai operations a “small ish wrinkle” for a merger rather than a real obstacle, since SpaceX’s national security work with the U.S. government sits uneasily next to Tesla’s manufacturing base in China.
Musk pushed back on the framing directly. “China is awesome. I strongly encourage people to visit,” he wrote on X. He also repeated language he first used in late July, when the Wall Street Journal reported that Tesla executives had been told to prepare for a possible spinoff, sale, or closure of the China business ahead of a SpaceX tie up. Musk called that report “absurdly fake news” at the time, adding that a separation had “never even come up in a discussion ever,” a line he echoed again this week.
The repeated denial has not settled the underlying question, because Shanghai’s role in Tesla’s business is exactly what makes a merger complicated. Gigafactory Shanghai still ships more than half of Tesla’s global deliveries and functions as the company’s main export hub for Europe and Asia. Teslarati previously reported on Musk’s initial denial, and the merger conversation itself has been building since SpaceX’s IPO gave it public shares to use as acquisition currency.
Wedbush’s Dan Ives has pegged the odds of a Tesla SpaceX merger at 80 to 90 percent by early 2027, and ARK’s prediction of a year end announcement adds another data point to that timeline, even as Musk keeps rejecting the specific mechanics reporters have described. Neither position rules out the other. Musk can deny a China spinoff was ever discussed while analysts still expect some form of combination to move forward, since ARK and Ives are both describing convergence at the corporate level, not necessarily the internal restructuring the Journal described in July.
For now, Tesla’s China business remains intact, and Musk’s comments this week make clear he has no interest in publicly walking that position back, no matter how often the merger question resurfaces.
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SpaceX AI investment gamble will make it a big winner, firm says
Tesla headlights cause recall of over 20,000 Model 3 and Model Y
