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Engineers develop bio-machine nose that can “sniff” and classify odors

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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.

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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.

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.

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Accidental computer geek, fascinated by most history and the multiplanetary future on its way. Quite keen on the democratization of space. | It's pronounced day-sha, but I answer to almost any variation thereof.

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Elon Musk

Elon Musk shuts down talk of TSMC taking over Terafab

Musk says Tesla and SpaceX will build and run Terafab, with TSMC limited to renting.

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SpaceX Terafab rendering

Elon Musk has drawn a firm line around who will be in charge of Terafab, the giant chip factory Tesla and SpaceX are planning in Texas.

Musk replied to a post on X arguing that Taiwan Semiconductor Manufacturing Company (TSMC) would most likely end up owning and operating the plant. “No, we will build and run the fab. Let there be ZERO doubt about that,” Musk wrote. “Maybe TSMC subleases part of the Terafab if they want, but nothing more than that.”

In plain terms, a sublease means TSMC could rent a section of the complex to make chips, similar to a tenant renting one floor of an office tower. The building, the equipment decisions and the daily operation would stay with Tesla and SpaceX.

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The comment shuts down speculation that started last week. On October 2, tech journalist Tim Culpan reported that TSMC was exploring ways to help run Terafab’s factories. Musk responded the next day that it was “just discussions, but something may come of it,” as Teslarati reported at the time. That left room for a scenario where the world’s largest contract chipmaker took the wheel. Musk’s latest post closes that door.

Elon Musk teases TSMC as potential Terafab partner

Some background helps explain why this matters. Tesla designs its own AI chips today but pays outside companies like TSMC and Samsung to manufacture them. Musk unveiled Terafab in March as a joint project between Tesla, SpaceX and xAI, arguing that existing suppliers cannot expand fast enough to meet his companies’ future demand. The goal is to produce enough chips each year to supply one terawatt of computing power, roughly 50 times what the entire global AI chip industry produces now.

Those chips are meant for Tesla’s Optimus humanoid robots, the Cybercab and Full Self-Driving computers, along with chips for SpaceX’s planned data centers in orbit. Owning the factory means Musk’s companies would not have to compete with every other chip customer for time on someone else’s production lines.

Intel is still part of the picture. The company signed on in April to help design, build and package chips for the project, and CEO Lip-Bu Tan told Bloomberg this week that Intel will keep working on Terafab despite the TSMC chatter.

The project moved from concept to construction planning over the summer. In August, SpaceX confirmed the Grimes County site about an hour from Houston, sent the county a $10 million payment under its tax abatement deal and said civil work would begin shortly. The first phase carries a $16.8 billion price tag, and total spending across all phases could reach as much as $119 billion.

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TSMC chairman C.C. Wei has said a new fab typically takes two to three years to build and another one to two years to reach full output. Tesla and SpaceX have never run one, which is why TSMC’s expertise drew so much attention. Musk’s answer suggests he would rather learn that process in house than hand control of a project this central to Tesla’s robotics and autonomy plans to an outside company.

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Elon Musk

Trump to hand Elon Musk a top honor that traces back to JFK

Trump will award Elon Musk the National Medal of Science at Thursday’s White House summit.

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elon musk and donald trump in front of a tesla cybertruck at the white house

Elon Musk is set to receive the highest honor the U.S. government gives to scientists and engineers.

President Donald Trump will present Musk with the National Medal of Science on Thursday at the White House’s Science: A New Golden Age Summit, Fox News Digital first reported on Wednesday. Google cofounder Sergey Brin, Nvidia CEO Jensen Huang and AMD CEO Lisa Su will receive the same medal, while Dell Technologies CEO Michael Dell and Microsoft CEO Satya Nadella will receive the National Medal of Technology and Innovation. A White House official later confirmed the list to Reuters.

“The Trump administration is grateful for the contributions of these incredible leaders in science and technology. These recipients are helping ensure America keeps leading the world in innovation,” White House spokesperson Liz Huston told Fox News.

It will be the first time Trump has presented either medal in his two terms. Congress created the National Medal of Science in 1959, and the National Science Foundation, which administers it, says 529 scientists and engineers have received it since. A presidential committee reviews nominees, but the president makes the final call.

Thursday’s group of medalists run or founded companies, and three of them sit at the center of the Super Intelligence hardware race that Musk competes in. Huang’s Nvidia supplies the GB300 chips filling SpaceX’s Colossus 2 cluster, while Su’s AMD is Nvidia’s biggest rival in data center GPUs.

Worth noting that Trump’s uncle, MIT physicist John G. Trump, received the National Medal of Science from President Ronald Reagan for his work on ionizing radiation and its uses in medicine and industry.

The Pentagon taps Elon Musk to design the battlefield of the future

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For Musk, the medal is the latest sign of how far his relationship with Trump has come since their 2025 split over the “Big Beautiful Bill” and his exit from DOGE. Last week, he sat at Trump’s left during a White House lunch where AI executives signed a voluntary safety accord, and Defense Secretary Pete Hegseth named him to help lead the Pentagon’s Project Meridian study on the future of warfare. Musk has also adopted the administration’s new vocabulary, saying on Sunday that SpaceXAI will be renamed SpaceXSI after Trump ordered federal agencies to replace “artificial intelligence” with “super intelligence.”

Musk has collected science honors before, including the Stephen Hawking Medal for Science Communication in 2019.

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Tesla FSD changed its mind mid-intersection, and it may have saved a life

Tesla shares dashcam footage of FSD Supervised stopping mid intersection to avoid a T-bone crash.

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Credit: @BLKMDL3/X

Tesla is putting another Full Self-Driving save in front of its 24.8 million followers on X.

On Tuesday morning, Tesla’s main account shared a dashcam clip with the caption “FSD Supervised preventing T-bone crash.” The footage came from an owner posting as TheNewGrid, who described what happened at a stop sign: “I looked at the car coming to the stop sign figured they would stop, my car went, then came to a stop mid intersection as they flew by. Had I been manually driving this would have resulted in a crash.”

The sequence is the notable part. FSD had already started crossing when the other driver ran the stop sign. Instead of pressing on, the car braked hard in the middle of the intersection and let the crossing vehicle pass in front of it. By the owner’s own account, they had made the same assumption the software initially made, that the other car would stop, and would not have corrected in time.

The clip is the latest in a run of safety posts Tesla has amplified over the past several days. On Saturday, the company shared a video from Selling Sunset star Jason Oppenheim, who sold his Bentley for a Model Y and said he was buying Teslas with FSD for 10 of his employees. Ashok Elluswamy, who leads Tesla AI, followed up by writing that Tesla self-driving “reacts to other people cutting into your path with super-human response times.” On Monday, a Cybertruck owner posted footage of FSD moving across three lanes from a red light to clear a path for an ambulance approaching from behind.

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This recent clip also lands a few weeks after Tesla began shipping Automatic Collision Evasion with FSD v14.3.9, a feature that can activate FSD on the driver’s behalf when a frontal collision is imminent or the driver appears distracted. Elluswamy said in September that “even earlier prediction of hazards, even faster reaction time and overall significantly better safety and collision avoidance” are coming with v15, the release Tesla has tied to round the clock Robotaxi operation.

The safety messaging matters beyond social media. Tesla has said FSD Supervised was 4.1 times less likely to crash than manual driving across 100 million kilometers on European roads, and it has been putting those figures in front of regulators. Eight EU countries have now approved FSD Supervised, with Croatia the most recent, but the EU’s bloc-wide vote originally set for October 6 has been pushed to December at the earliest.

FSD Supervised is still a Level 2 system, and the driver remains responsible at all times. Even heavy users find reasons to step in. Teslarati’s Joey Klender, who uses FSD for about 76 percent of his driving, laid out five recurring issues on Tuesday that still prompt him to intervene. Clips like this one show the other column of that ledger: moments where the software caught a mistake a human was about to make.

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