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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.

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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.

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?

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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 says your Tesla will start to learn your individual preferences

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Credit: Tesla

Elon Musk said today on X that Teslas will start to learn your individual preferences. This is something that he seemed to hint toward earlier this month when he said parking was by far the biggest reason drivers intervene with Full Self-Driving.

Musk made the comment in response to notable Tesla influencer Whole Mars, who said that his vehicle will sometimes disobey the settings he has enabled for his car. He responded to the post, stating that “The car will start to remember your specific interventions and match each person’s individual preferences.”

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This is something that could be perhaps one of the biggest ways Tesla could minimize or even work closer toward eliminating interventions altogether. While FSD does a lot of things really well, many people intervene a vast majority of the time not due to major or critical safety errors.

Instead, many take over because the car is doing something that they do not like as a preference; it might park in a parking spot that is not preferred by the driver, it might linger too long in the left lane on the highway (a personal favorite), or it could even take a route that the driver does not like.

These all lead to interventions, but they are not triggered by a major safety issue. Instead, it’s just preference.

READ OUR REVIEW OF TESLA’S LATEST FSD VERSION:

Tesla Full Self-Driving v14.3.5 Early Impressions: new features and early performance

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If Teslas could start to learn the personal preferences of the person who owns them, interventions will truly begin to be less frequent. Some of this is already pretty evident, in my opinion. Teslas use a neural network to learn behaviors and accumulate data to improve performance.

For months now, we’ve tracked FSD’s performance at “Except Right Turn” stop signs, something that is very common in Pennsylvania, but many of our readers located in other parts of the U.S. have never heard of. FSD handles one Except Right Turn stop sign very well, one that I travel past frequently. Others that I do not navigate through as often do not have as confident a performance. It seems like the cars might already be doing this to an extent.

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That example is also for something that is a street sign and not necessarily a driver preference; however, I still feel it is worth mentioning because it only handles that commonly passed Except Right Turn stop sign with true confidence. Others it still seems to struggle with.

This could be one of Tesla’s big moves toward full autonomy, and it could be a pathway to truly unsupervised driving. Every day, millions of cars on the road travel at a human driver’s personal preferences with no incident. Why can’t autonomous vehicles still cater to a passenger’s preferences while being autonomous? Tesla seems to have the idea that it would be possible.

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Ron DeSantis calls out media bias in Tesla crash coverage

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Credit: ABC News

Florida Governor Ron DeSantis has sharply criticized legacy media outlets for what he describes as selective and biased reporting on vehicle accidents involving Tesla. In a recent X post, DeSantis questioned why headlines routinely spotlight the Tesla brand in crash stories, even when human error is the clear cause, while similar incidents with other automakers often receive generic treatment.

A prime example is the June 19, 2026, fatal crash in Katy, Texas. A Tesla Model 3 driven by Michael Butler struck a brick home at high speed, killing 76-year-old Martha Avila inside. Initial reports and headlines prominently featured “Tesla crash” and referenced the driver’s claim that an automated driving-assistance system was engaged.

Many outlets quickly speculated that Full Self-Driving or Autopilot were the cause of the crash, immediately blaming the suites for the accident shortly after it happened.

However, Tesla responded shortly after the accident with vehicle data that showed Butler manually overrode the system by pressing the accelerator to 100 percent, reaching 73 MPH in a residential area, more than double the speed limit. The accelerator remained floored after impact.

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Tesla finally clarifies fatal Texas crash, confirms driver manually overrode acceleration

The National Transportation Safety Board (NTSB) later confirmed these findings, and Butler now faces manslaughter charges. His phone searches also included queries like “Tesla FSD too timid,” suggesting he may have intervened aggressively. Despite this, many headlines continued to center Tesla’s technology rather than the driver’s actions.

DeSantis highlighted a Washington Post headline, which was labeled, “Newly released photo shows wreckage of Tesla crash that killed grandmother.”

The subheadline noted the driver overrode assistance and floored the accelerator, yet the brand name dominated the framing. He asked whether legacy outlets typically name the make of a car in routine crashes or reserve that treatment for Tesla to push a narrative.

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This pattern appears widespread. Crashes involving Ford, Chevrolet, or Toyota vehicles frequently appear as “pickup truck slams into home” or “fatal car crash kills pedestrian” without brand specifics, especially absent new technology angles.

High-profile Ford F-150 or Chevy Silverado incidents tied to large sales volumes often escape brand-callout scrutiny. In contrast, Tesla stories consistently lead with the manufacturer, amplifying perceptions of risk despite data showing strong overall safety performance:

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Tesla’s own 2025 Impact Report indicates vehicles using FSD logged 0.19 major incidents per million miles, roughly eight times fewer than the U.S. average. Models like the Model Y also rank among the safest in IIHS and NHTSA testing for occupant protection. Critics argue disproportionate coverage ignores these statistics and driver behavior factors, such as younger or more aggressive Tesla owners in some studies.

DeSantis frames this as part of a broader political agenda against innovative American companies like Tesla. By consistently naming Tesla while downplaying others, media outlets risk eroding public trust and shaping perceptions detached from the evidence of human error in most cases.

As autonomous technology evolves across the industry, consistent and factual reporting will be essential to separate real safety concerns from narrative-driven coverage.

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Tesla enters two new markets on two different continents in one week

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Tesla entered two new markets this week by advancing its presence in Latvia (Europe) and officially launching operations in Uruguay (South America), marking a rapid dual-continent expansion.

These moves underscore the company’s strategy to tap into emerging EV markets with supportive policies, renewable energy grids, and growing demand for sustainable transport.

Latvia: Strengthening the Baltic Footprint

In Latvia, Tesla has built on its earlier registration of Tesla Latvia SIA in late 2025 with recent steps toward full operations, including job postings for a service center and representation in Riga. This aligns with broader Baltic expansion following Lithuania’s model of pop-up stores and service centers.

EV penetration in Latvia stands at around 7 percent for BEVs in new passenger car registrations. 2025 data showed 1,602 BEVs out of about 22,500 total, or 7.1 percent, with combined plug-ins nearing 19 percent. Growth has been steady but below the European average, supported by government subsidies and infrastructure development. Tesla models like the Model 3 lead local EV registrations.

Vehicles for the Latvian market will likely be sourced from Gigafactory Berlin or Gigafactory Shanghai. Charging infrastructure is robust for the region as well, with over 400- 2,000 public points, with Tesla Superchargers in Riga, Jūrmala, and along Via Baltica routes offering up to 250 kW.

Uruguay: Third South American Country

Tesla teased its Uruguay arrival with “Estamos llegando,” or, “We are arriving,” on social media, followed by an official presentation scheduled for mid-July.

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The company established Tesla Uruguay SAS, homologated Model 3 and Model Y (three versions each), and appointed local leadership. This makes Uruguay Tesla’s third official South American market after Chile and Colombia.

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Uruguay boasts one of Latin America’s highest EV penetrations, with battery-electric vehicles exceeding 20 percent market share recently, driven by tax incentives, high fuel prices, and a nearly 95-100 percent renewable electricity grid. Hundreds of Teslas already operate via grey imports, but official sales bring warranties, service, and support.

Vehicles will be imported from Gigafactory Shanghai, enabling competitive pricing for Model 3 and Model Y. Charging plans include Supercharger development alongside existing infrastructure, leveraging the country’s green energy advantage for affordable operation.

Tesla Superchargers follow Model 3 and Model Y to South American country

Tesla’s Dual Continent Expansion

Tesla’s simultaneous push into Latvia and Uruguay demonstrates efficient scaling: prioritizing service and infrastructure first, then direct sales in high-potential niches. In Europe, it fills Baltic gaps; in Latin America, it counters Chinese dominance while leveraging renewables.

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This dual move signals Tesla’s ambition to accelerate global EV adoption amid varying regional paces. By addressing local needs, like subsidies in Latvia or incentives and green grids in Uruguay, Tesla not only boosts volumes but advances its mission of sustainable energy.

For investors and consumers, it highlights resilience and opportunity in diverse markets, potentially paving the way for further growth in underserved regions. With strong fundamentals in both, these entries could yield long-term gains as EV transitions mature worldwide.

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