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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.
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.
Elon Musk
Elon Musk’s X will start using a Tesla-like software update strategy
The initiative seems designed to accelerate updates to the social media platform, while maintaining maximum transparency.
Elon Musk’s social media platform X will adopt a Tesla-esque approach to software updates for its algorithm.
The initiative seems designed to accelerate updates to the social media platform, while maintaining maximum transparency.
X’s updates to its updates
As per Musk in a post on X, the social media company will be making a new algorithm to determine what organic and advertising posts are recommended to users. These updates would then be repeated every four weeks.
“We will make the new 𝕏 algorithm, including all code used to determine what organic and advertising posts are recommended to users, open source in 7 days. This will be repeated every 4 weeks, with comprehensive developer notes, to help you understand what changed,” Musk wrote in his post.
The initiative somewhat mirrors Tesla’s over-the-air update model, where vehicle software is regularly refined and pushed to users with detailed release notes. This should allow users to better understand the details of X’s every update and foster a healthy feedback loop for the social media platform.
xAI and X
X, formerly Twitter, has been acquired by Elon Musk’s artificial intelligence startup, xAI last year. Since then, xAI has seen a rapid rise in valuation. Following the company’s the company’s upsized $20 billion Series E funding round, estimates now suggest that xAI is worth tens about $230 to $235 billion. That’s several times larger than Tesla when Elon Musk received his controversial 2018 CEO Performance Award.
As per xAI, the Series E funding round attracted a diverse group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group, among others. Strategic partners NVIDIA and Cisco Investments also continued support for building the world’s largest GPU clusters.
News
Tesla FSD Supervised wins MotorTrend’s Best Driver Assistance Award
The decision marks a notable reversal for the publication from prior years, with judges citing major real-world improvements that pushed Tesla’s latest FSD software ahead of every competing ADAS system.
Tesla’s Full Self-Driving (Supervised) system has been named the best driver-assistance technology on the market, earning top honors at the 2026 MotorTrend Best Tech Awards.
The decision marks a notable reversal for the publication from prior years, with judges citing major real-world improvements that pushed Tesla’s latest FSD software ahead of every competing ADAS system. And it wasn’t even close.
MotorTrend reverses course
MotorTrend awarded Tesla FSD (Supervised) its 2026 Best Tech Driver Assistance title after extensive testing of the latest v14 software. The publication acknowledged that it had previously criticized earlier versions of FSD for erratic behavior and near-miss incidents, ultimately favoring rivals such as GM’s Super Cruise in earlier evaluations.
According to MotorTrend, the newest iteration of FSD resolved many of those shortcomings. Testers said v14 showed far smoother behavior in complex urban scenarios, including unprotected left turns, traffic circles, emergency vehicles, and dense city streets. While the system still requires constant driver supervision, judges concluded that no other advanced driver-assistance system currently matches its breadth of capability.
Unlike rival systems that rely on combinations of cameras, radar, lidar, and mapped highways, Tesla’s FSD operates using a camera-only approach and is capable of driving on city streets, rural roads, and freeways. MotorTrend stated that pure utility, the ability to handle nearly all road types, ultimately separated FSD from competitors like Ford BlueCruise, GM Super Cruise, and BMW’s Highway Assistant.
High cost and high capability
MotorTrend also addressed FSD’s pricing, which remains significantly higher than rival systems. Tesla currently charges $8,000 for a one-time purchase or $99 per month for a subscription, compared with far lower upfront and subscription costs from other automakers. The publication noted that the premium is justified given FSD’s unmatched scope and continuous software evolution.
Safety remained a central focus of the evaluation. While testers reported collision-free operation over thousands of miles, they noted ongoing concerns around FSD’s configurable driving modes, including options that allow aggressive driving and speeds beyond posted limits. MotorTrend emphasized that, like all Level 2 systems, FSD still depends on a fully attentive human driver at all times.
Despite those caveats, the publication concluded that Tesla’s rapid software progress fundamentally reshaped the competitive landscape. For drivers seeking the most capable hands-on driver-assistance system available today, MotorTrend concluded Tesla FSD (Supervised) now stands alone at the top.
News
Elon Musk’s Grokipedia surges to 5.6M articles, almost 79% of English Wikipedia
The explosive growth marks a major milestone for the AI-powered online encyclopedia, which was launched by Elon Musk’s xAI just months ago.
Elon Musk’s Grokipedia has grown to an impressive 5,615,201 articles as of today, closing in on 79% of the English Wikipedia’s current total of 7,119,376 articles.
The explosive growth marks a major milestone for the AI-powered online encyclopedia, which was launched by Elon Musk’s xAI just months ago. Needless to say, it would only be a matter of time before Grokipedia exceeds English Wikipedia in sheer volume.
Grokipedia’s rapid growth
xAI’s vision for Grokipedia emphasizes neutrality, while Grok’s reasoning capabilities allow for fast drafting and fact-checking. When Elon Musk announced the initiative in late September 2025, he noted that Grokipedia would be an improvement to Wikipedia because it would be designed to avoid bias.
At the time, Musk noted that Grokipedia “is a necessary step towards the xAI goal of understanding the Universe.”
Grokipedia was launched in late October, and while xAI was careful to list it only as Version 0.1 at the time, the online encyclopedia immediately earned praise. Wikipedia co-founder Larry Sanger highlighted the project’s innovative approach, noting how it leverages AI to fill knowledge gaps and enable rapid updates. Netizens also observed how Grokipedia tends to present articles in a more objective manner compared to Wikipedia, which is edited by humans.
Elon Musk’s ambitious plans
With 5,615,201 total articles, Grokipedia has now grown to almost 79% of English Wikipedia’s article base. This is incredibly quick, though Grokipedia remains text-only for now. xAI, for its part, has now updated the online encyclopedia’s iteration to v0.2.
Elon Musk has shared bold ideas for Grokipedia, including sending a record of the entire knowledge base to space as part of xAI’s mission to preserve and expand human understanding. At some point, Musk stated that Grokipedia will be renamed to Encyclopedia Galactica, and it will be sent to the cosmos.
“When Grokipedia is good enough (long way to go), we will change the name to Encyclopedia Galactica. It will be an open source distillation of all knowledge, including audio, images and video. Join xAI to help build the sci-fi version of the Library of Alexandria!” Musk wrote, adding in a later post that “Copies will be etched in stone and sent to the Moon, Mars and beyond. This time, it will not be lost.”
Elon Musk’s X will start using a Tesla-like software update strategy
Tesla FSD Supervised wins MotorTrend’s Best Driver Assistance Award
