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.
The Tesla Diner has been subject to many points of criticism since its launch in mid-2025, and skeptics and disbelievers claim the company’s latest novel concept is on its way down, but there’s a lot of evidence to state that is not the case.
The piece cites anecdotal evidence like empty parking lots, more staff than customers during a December visit, removed novelty items, like Optimus robot popcorn service and certain menu items, the departure of celebrity chef Eric Greenspan in November 2025, slow service, high prices, and a shift in recent Google/Yelp reviews toward disappointment.
The piece frames this as part of broader Tesla struggles, including sales figures and Elon Musk’s polarizing image, calling it a failed branding exercise rather than a sustainable restaurant.
This narrative is overstated and sensationalized, and is a good representation of coverage on Tesla by today’s media.
Novelty Fade is Normal, Not Failure
Any hyped launch, especially a unique Tesla-branded destination blending dining, Supercharging, and a drive-in theater, naturally sees initial crowds taper off after the “Instagram effect” wears down.
Tesla makes major change at Supercharger Diner amid epic demand
This is common for experiential spots in Los Angeles, especially pop-up attractions or celebrity-backed venues. The article admits early success with massive lines and social media buzz, but treats the return to normal operations as “dying down.”
In reality, this stabilization is a healthy sign of transitioning from hype-driven traffic to steady patronage.
Actual Performance Metrics Contradict “Ghost Town” Claims
- In Q4 2025, the Diner generated over $1 million in revenue, exceeding the average McDonald’s location
- It sold over 30,000 burgers and 83,000 fries in that quarter alone. These figures indicate a strong ongoing business, especially for a single-location prototype focused on enhancing Supercharger experiences rather than competing as a mass-market chain
It’s not a ghost town lol. The @Tesla Diner still had over 30,000 burger orders and 83,000 fries orders in Q4. The diner generated over $1M in revenue in Q4, a $4M annual run rate, which is more than the average McDonald’s…. pic.twitter.com/XvAGLUqxej
— Sawyer Merritt (@SawyerMerritt) January 4, 2026
Conflicting On-the-Ground Reports
While the article, and other similar pieces, describe a half-full parking lot and sparse customers during specific off-peak visits, other recent accounts push back:
- A January 2026 X post noted 50 of 80 Supercharger stalls were busy at 11 a.m., calling it “the busiest diner in Hollywood by close to an order of magnitude
TESLA DINER 🍔
Frantic!!!
Crazy busy. pic.twitter.com/wMbmr8SFFn
— Rich & Sharon (@HullTeslaModel3) January 4, 2026
- Reddit discussions around the same time describe it as not empty when locals drive by regularly, with some calling the empty narrative “disingenuous anti-Tesla slop.”
When we visited it last week it was packed. We had to wait to enter, get a table and go to the restroom. We were lucky to find a spot to charge.
— Rani G (@ranig) January 4, 2026
Bottom Line
The Tesla Diner, admittedly, is not the nonstop circus it was at launch–that was never sustainable or intended. But, it’s far from “dying” or an “empty pit stop.”
It functions as a successful prototype: boosting Supercharger usage, generating solid revenue, and serving as a branded amenity in the high-traffic EV market of Los Angeles.
News
Tesla stands to win big from potential adjustment to autonomous vehicle limitations
Enabling scale, innovation, and profitability in a sector that is growing quickly would benefit Tesla significantly, especially as it has established itself as a leader.
Tesla stands to be a big winner from a potential easing of limitations on autonomous vehicle development, as the United States government could back off from the restrictions placed on companies developing self-driving car programs.
The U.S. House Energy and Commerce subcommittee will hold a hearing later this month that will aim to accelerate the deployment of autonomous vehicles. There are several key proposals that could impact the development of self-driving cars and potentially accelerate the deployment of this technology across the country.
These key proposals include raising the NHTSA’s exemption cap from 2,500 to 90,000 vehicles per year per automaker, preempting state-level regulations on autonomous vehicle systems, and mandating NHTSA guidelines for calibrating advanced driver assistance systems (ADAS).
Congress, to this point, has been divided on AV rules, with past bills like the 2017 House-passed measure stalling in the Senate. Recent pushes come from automakers urging the Trump administration to act faster amid competition from Chinese companies.
Companies like Tesla, who launched a Robotaxi service in Austin and the Bay Area last year, and Alphabet’s Waymo are highlighted as potential beneficiaries from lighter sanctions on AV development.
The NHTSA recently pledged to adopt a quicker exemption review for autonomous vehicle companies, and supporters of self-driving tech argue this will boost U.S. innovation, while critics are concerned about safety and job risks.
How Tesla Could Benefit from the Proposed Legislation
Tesla, under CEO Elon Musk’s leadership, has positioned itself as a pioneer in autonomous driving technology with its Full Self-Driving software and ambitious Robotaxi plans, including the Cybercab, which was unveiled in late 2024.
The draft legislation under consideration by the U.S. House subcommittee could provide Tesla with significant advantages, potentially transforming its operational and financial landscape.
NHTSA Exemption Cap Increase
First, the proposed increase in the NHTSA exemption cap from 2,500 to 90,000 vehicles annually would allow Tesla to scale up development dramatically.
Currently, regulatory hurdles limit how many fully autonomous vehicles can hit the roads without exhaustive approvals. For Tesla, this means accelerating the rollout of its robotaxi fleet, which Musk envisions as a network of millions of vehicles generating recurring revenue through ride-hailing. With Tesla’s vast existing fleet of over 6 million vehicles equipped with FSD hardware, a higher cap could enable rapid conversion and deployment, turning parked cars into profit centers overnight.
Preempting State Regulations
A united Federal framework would be created if it could preempt State regulations, eliminating the patchwork of rules that currently complicate interstate operations. Tesla has faced scrutiny and restrictions in states like California, especially as it has faced harsh criticism through imposed testing limits.
A federal override of State-level rules would reduce legal battles, compliance costs, and delays, allowing Tesla to expand services nationwide more seamlessly.
This is crucial for Tesla’s growth strategy, as it operates in multiple markets and aims for a coast-to-coast Robotaxi network, competing directly with Waymo’s city-specific expansions.
Bringing Safety Standards to the Present Day
Innovation in the passenger transportation sector has continued to outpace both State and Federal-level legislation, which has caused a lag in the development of many things, most notably, self-driving technology.
Updating these outdated safety standards, especially waiving requirements for steering wheels or mirrors, directly benefits Tesla’s innovative designs. Tesla wanted to ship Cybertruck without side mirrors, but Federal regulations required the company to equip the pickup with them.
Cybercab is also planned to be released without a steering wheel or pedals, and is tailored for full autonomy, but current rules would mandate human-ready features.
Streamlined NHTSA reviews would further expedite approvals, addressing Tesla’s complaints about bureaucratic slowdowns. In a letter written in June to the Trump Administration, automakers, including Tesla, urged faster action, and this legislation could deliver it.
In Summary
This legislation represents a potential regulatory tailwind for Tesla, but it still relies on the government to put forth action to make things easier from a regulatory perspective. Enabling scale, innovation, and profitability in a sector that is growing quickly would benefit Tesla significantly, especially as it has established itself as a leader.
News
Nvidia CEO Jensen Huang explains difference between Tesla FSD and Alpamayo
“Tesla’s FSD stack is completely world-class,” the Nvidia CEO said.
NVIDIA CEO Jensen Huang has offered high praise for Tesla’s Full Self-Driving (FSD) system during a Q&A at CES 2026, calling it “world-class” and “state-of-the-art” in design, training, and performance.
More importantly, he also shared some insights about the key differences between FSD and Nvidia’s recently announced Alpamayo system.
Jensen Huang’s praise for Tesla FSD
Nvidia made headlines at CES following its announcement of Alpamayo, which uses artificial intelligence to accelerate the development of autonomous driving solutions. Due to its focus on AI, many started speculating that Alpamayo would be a direct rival to FSD. This was somewhat addressed by Elon Musk, who predicted that “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.”
During his Q&A, Nvidia CEO Jensen Huang was asked about the difference between FSD and Alpamayo. His response was extensive:
“Tesla’s FSD stack is completely world-class. They’ve been working on it for quite some time. It’s world-class not only in the number of miles it’s accumulated, but in the way it’s designed, the way they do training, data collection, curation, synthetic data generation, and all of their simulation technologies.
“Of course, the latest generation is end-to-end Full Self-Driving—meaning it’s one large model trained end to end. And so… Elon’s AD system is, in every way, 100% state-of-the-art. I’m really quite impressed by the technology. I have it, and I drive it in our house, and it works incredibly well,” the Nvidia CEO said.
Nvidia’s platform approach vs Tesla’s integration
Huang also stated that Nvidia’s Alpamayo system was built around a fundamentally different philosophy from Tesla’s. Rather than developing self-driving cars itself, Nvidia supplies the full autonomous technology stack for other companies to use.
“Nvidia doesn’t build self-driving cars. We build the full stack so others can,” Huang said, explaining that Nvidia provides separate systems for training, simulation, and in-vehicle computing, all supported by shared software.
He added that customers can adopt as much or as little of the platform as they need, noting that Nvidia works across the industry, including with Tesla on training systems and companies like Waymo, XPeng, and Nuro on vehicle computing.
“So our system is really quite pervasive because we’re a technology platform provider. That’s the primary difference. There’s no question in our mind that, of the billion cars on the road today, in another 10 years’ time, hundreds of millions of them will have great autonomous capability. This is likely one of the largest, fastest-growing technology industries over the next decade.”
He also emphasized Nvidia’s open approach, saying the company open-sources its models and helps partners train their own systems. “We’re not a self-driving car company. We’re enabling the autonomous industry,” Huang said.
Tesla Diner becomes latest target of gloom and doom narrative
Tesla stands to win big from potential adjustment to autonomous vehicle limitations
