News
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.
Energy
Taiwan power firm bets big on Tesla Megapacks as AI data center thirst grows
Taiwan’s Apollo Power orders 260 Tesla Megapacks, betting AI data centers will need more electricity.
A Taiwanese power company has ordered 260 Tesla Megapack 2XL units, roughly 1GWh of storage, betting that electricity rather than chips will decide how fast AI data centers come online. Apollo Power signed the contract with Tesla’s Taiwan energy arm on October 8, according to the company’s filing with the Taiwan stock exchange.
The filing says the units are meant for behind the meter storage and resilient grid projects, with delivery in batches from the end of 2027 and sites operating in 2028. Apollo and Tesla did not disclose a price, citing a confidentiality agreement. Apollo plans to pay for the equipment through a cash capital increase and bank financing, and it noted the purchase is not revenue and does not mean it holds firm orders from its partners.
Biggo reported that only about 33 units are under signed customer contracts, with roughly 150 more in negotiation. The same report put total project investment near NT$130 billion, but that figure includes installation work, with the equipment itself making up about 40 to 50 percent. In other words, a large share of this order is Apollo reserving supply ahead of demand. Apollo’s chairman told local media global large storage supply is tight, which is why the company locked in the units early, according to Yahoo Taiwan Finance.
Apollo also launched an AI data center and grid resilience alliance with Phison, Gigabyte and Shihlin Electric. The pitch rests on a pilot at Phison’s Zhunan plant, where Apollo and Tesla Energy Taiwan installed grid forming Megapack 2XLs in June. Tesla Energy Taiwan general manager Sun Hsiao-Han said the project went from demo to 1GWh in four months, and that Tesla Energy has deployed more than 50GWh worldwide.
Taiwan’s cabinet has approved amendments that would require large energy users to install their own generation and storage, which gives enterprise storage a regulatory tailwind.
The deal fits a pattern Teslarati has tracked. Tesla’s Megablock targets 1GWh commissioned in 20 business days, a pitch aimed squarely at fast moving data center builds. Megapacks already back xAI’s Colossus in Memphis and a 400MW AI campus in Brazil. Sun Media adds that Megapack 2XL was named among the first products in Nvidia’s DSX Ready qualification for battery storage in AI factories.
Deliveries are more than a year away, so the real test is how much of that 260 unit order turns into signed customer contracts.
For a century, the car has asked the same thing of its owner, which is basically to pay attention. Even the best ride-hailing app like Uber or Lyft only moved the problem into someone else’s hands. You stopped driving, but you still sat in a stranger’s car, while half listening, and wondering whether to take a phone call in the car without being rude. The Cybercab has no wheel, no pedals and no driver. With Grok @bot now live inside it, it becomes something else entirely, and I think that matters more than the fleet count that everyone is tracking.
Grok @bot is an agent, not a voice assistant. A rider signs in once, and from then on can say what they need and watch it happen. Order dinner from a favorite restaurant. Fill the grocery cart. Move money, answer email, adjust a calendar, push a work project forward. Tesla engineer Yun-Ta Tsai confirmed it is enabled across every Cybercab and the rest of the Model Y fleet, and Tesla’s own pitch is that Full Self-Driving handles the commute while Grok handles the errands.
Think about what that does to a thirty minute ride. Uber sells you a trip, while Waymo sells you the same trip in a more private setting. Tesla is selling the thirty minutes themselves, returned to you with an assistant attached. Errands that used to eat a Saturday get done between pickup and drop off. The ride stops being dead time between two places and becomes a place of its own.
Tesla integrates Grok Bot into its vehicles for the ultimate personal assistant
Best of all, your Bots follow you into any Cybercab, and presumably your own Tesla, then logs you out automatically when you step out. Anyone can bolt a chatbot onto a screen, but much harder to own the vehicle, the autonomy stack and the assistant at once. It also quietly ties SpaceX’s Super Intelligence business to Tesla’s fleet, after Tesla converted its xAI stake into SpaceX equity. The relationship between those two companies is getting harder to describe as separate.
This is also where the hard questions start, because an agent that can spend your money in a vehicle other people also ride in needs some answers. How does it handle a voice it shouldn’t trust? What gets recorded, who can see it, and for how long? What happens when a rider leaves halfway through a task?
If Tesla gets those answers right, the scoreboard changes. We have been counting Cybercabs and wait times. The more telling number may be what riders accomplish per trip. That is data almost no one else will ever have, and it is the real reason to watch Grok @bot.
What do you think? Leave me a comment.
News
Why Elon Musk’s target date for buying an Optimus robot is harder than it sounds
Musk says China’s magnet export ban cost Optimus months, and robot hands remain shockingly hard.
Elon Musk says China’s export curbs on magnets used in electric motors set back Tesla’s Optimus program by two to three months, and that the robot’s hands remain the hardest part of the project. He made the comments Saturday during a live interview with Tesla Owners Silicon Valley at the X Takeover event at Giga Texas, in front of roughly 2,000 attendees. The Optimus discussion begins around the 49 minute mark of the stream.
On the hands, Musk was blunt and noted that a general purpose humanoid needs fine motor skills that are “incredibly difficult to get right. Shockingly difficult,” he said in the interview. He pointed to a problem he says no one has demonstrated yet: “One of the hardest things also generally is to do precision and force at the same time,” such as driving a small self tapping screw into wood. Touch sensors add another layer, since it is “actually kind of hard to get touch sensors that elastically deform and can handle high cycle life and it won’t just break after a few thousand cycles.”
He also took aim at rival robot videos. “Any complicated looking robot demo, it’s a canned demo. It’s not real,” Musk said, adding that real AI means showing a robot something it has never seen and watching it still cope, the way FSD handles a city it has never driven.
Musk expects the Optimus ramp to be slower than a new vehicle production ramp. “The initial part of that S curve of production ramp is going to be very slow at the beginning,” Musk said, partly because “unlike cars, there’s no pre existing supply chain for robot stuff.” That echoes his July reply on X that Optimus production “will be extremely slow at first, as everything is new.”
The magnet disclosure puts a number on a problem Musk first raised in 2025. He said China “prevented the export of magnets for use in electric motors” and that it “set back the Optimus program by like two or three months.” Then he added: “We had robots with no arms.” Tesla’s fix is to bring the supply chain home. “You’ve got to be able to make all the parts domestically,” he said. Teslarati reported in April 2025 that Musk tied the issue to permanent magnets in the arm actuators, where motors have to be as small as possible.
Tesla Optimus V3 hand and arm details revealed in new patents
Production is moving regardless, with a reported internal goal of more than 1,000 a week by the end of 2026. Teslarati recently covered how Tesla is certifying supply partners in China for Optimus parts, while the company’s hand design has been the subject of new patent filings.
Musk has said he wants Optimus available to the public by late 2027, though Tesla has not confirmed that date or published updated production figures.
Taiwan power firm bets big on Tesla Megapacks as AI data center thirst grows
Tesla Cybercab and Robotaxi’s real advantage won’t be the ride service
Why Elon Musk’s target date for buying an Optimus robot is harder than it sounds
The Pentagon taps Elon Musk to design the battlefield of the future
Tesla Roadster’s new patent preps white-knuckle speeds, keeping it grounded
