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.
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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.
Tesla released Full Self-Driving version 14.3.7 yesterday, and after about 90 miles of testing today, it is evident there are some definite fixes from version 14.3.6, which I wrote about last week and called a regression.
Within the first 40 minutes of my drive on v14.3.7, it saved me from getting into an accident with an unaware Dodge Charger driver, and some of the things Tesla seemed to miss in v14.3.6 were definitely improved. All in all, the release so far has some really great performance, and I’m looking forward to testing it further.
For now, here’s everything I noticed with v14.3.7:
Overall Improvement
Just generally speaking from a ride perspective, this was a really great experience. A lot of the hesitancy I experienced on v14.3.6 was gone. There were no instances of brake-stabbing, wheel-jerking, or any uncertain or unconfident movements. It was void of anything that I felt made it timid with v14.3.6.
The one thing I do hope to see down the road is a smaller need to adjust Speed Profiles so often. Because Tesla calls FSD “Supervised,” I’m okay with needing to hit the scroll wheel a few times a drive.
However, I hope that things can be incrementally improved upon with speed. Sometimes it’s too fast; other times it’s too slow. It’s a difficult thing to hone in and refine, but I hope it eventually gets there.
I didn’t notice any significant left lane camping or any behaviors that were completely out of line. I am hopeful that this opinion does not change, but after driving a few days with this version and putting it in a variety of different situations, you are exposed to more behaviors, some of which are not necessarily what I’d prefer.
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The big things to notice, at least in my experience thus far, are that the major issues with previous versions — meaning the braking stabbing and wheel jerking — simply weren’t there. That’s enough to already consider this progress compared to .6.
Manual Signal Override is More Responsive
On .6, I had quite a few issues with FSD ignoring my manually input turn signals. If Tesla wants to call it “Supervised,” then the car should not ignore any input the driver gives. If I touch the accelerator on FSD, the car speeds up.
🚨 Tesla FSD v14.3.7 obeying manual turn signals https://t.co/6eqToXpQfC pic.twitter.com/vHBlFQ4PDV
— TESLARATI (@Teslarati) August 2, 2026
The car did a great job of obeying my turn signals when I wanted it to change lanes, which is welcome.
Parking Lot Performance
Before .6, I traditionally took over in nearly every parking lot my car entered, because I knew it would not park somewhere that I wanted, and usually, it was just a tad too timid in this setting.
The one bright spot of .6 was how well it handled parking lots. This continued with v14.3.7:
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I’m always really happy to see progress at all, but once parking preferences come to FSD, as long as this performance is still around, that could potentially be the biggest improvement I’ve seen in FSD in the year I’ve been using it personally on a daily basis.
Full Self-Driving Averts Disaster
A Dodge Charger changed into my lane without checking if I was there, running me off the road. FSD made the initial avoidance maneuver; I grabbed the wheel out of instinct, looked in my side mirror to ensure I had nobody following closely behind, hit the brake, and straightened the car back up to avoid a curb:
🚨 Guys this is why you all NEED to stay vigilant behind the wheel, even on Tesla Full Self-Driving
Human drivers are UNHINGED and have no idea what they’re doing anymore. This was a kid obviously younger than 20 years old with zero awareness.
First drive with v14.3.7 https://t.co/1vTbCMpCn8 pic.twitter.com/lz7KKEF6bj
— TESLARATI (@Teslarati) August 2, 2026
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There have been quite a few responses to this video stating that I should never have grabbed the wheel. To be honest, I really wish I had not done so, because I do believe FSD would have avoided any sort of collision with anything, including the car or the curb.
However, this was the first time I had ever been this close to being hit while using FSD. My natural reaction was to take over. I think if I had had something like this happen before, my reaction might have been different.
Hitting the brake avoided hitting the curb, while FSD swerved to avoid the car. My concern after the car was clear of my front end was the curb. All in all, I’m really happy with how things turned out, and I think anyone could be a critic of how I handled it. I only had a split second to really make a decision, and thankfully, any damage was avoided.
It is clear FSD managed to avoid the car coming down before I was able to. I truly credit FSD for avoiding the collision.
What Needs to Improve
Better Recognition of Potholes, Uneven Roads, Sharp Changes in Roadway/Bumps
On Friday, my Fianceè and I were in the car, and FSD was driving us. We crossed over a roadway that has a traffic light, and FSD was traveling at 40 MPH on Standard, 5 MPH over the speed limit. Everything was more than reasonable.
However, the road we were crossing at the light has a major bump both as you start and finish crossing it. Without a speed reduction, your car can go airborne. The Tesla did just this on Friday on v14.3.6; it was an uncomfortable bounce that pretty much confirmed I would not ever let FSD go over again unless we were sitting at that intersection when there is a red light.
I even tried scrolling down into Sloth quickly, but I ended up just taking over:
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This is that big bounce that I mentioned in the quoted post.
It’s just a tad too drastic to take at the speed FSD wants to go over it. You can see me quickly swipe down into Sloth, but I intervened. https://t.co/K20PK9ysBg pic.twitter.com/81Oc82ZJcZ
— TESLARATI (@Teslarati) August 2, 2026
A few people have said it remains related to the vision-based approach and its difficulty comprehending 3D. This is a huge issue because this can cause serious damage at certain speeds.
Navigation
Nothing new here. I still turn off “Online Routing” quite frequently to get the car to take logical routes from time to time.
Auto Wipers
Auto Wipers are just plain bad. I really hope Tesla just uses a rain sensor. I thought they had improved at one point, but I still get dry wipes, Speed 4 on a drizzle, and Speed 2 on a steady rain. In reality, these should be switched.
You can watch our full review of Tesla Full Self-Driving v14.3.7 below:
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🚨 Tesla Full Self-Driving v14.3.7 saved me from an accident! FULL REVIEW: https://t.co/1vTbCMpCn8 pic.twitter.com/9mHmKVoMVA
— TESLARATI (@Teslarati) August 2, 2026
SpaceX will report second quarter results after the market closes on Tuesday, August 4, marking the first time the company has opened its books to the public since its record IPO in June. Management will host a live audio only webcast at 4:30 p.m. ET, streamed on X, with no dial in option.
The debut carries more weight than a typical first quarter as a public company. Two trading days after the release, on August 6, the first tranche of SpaceX’s lockup expires, freeing roughly 911.5 million insider and employee shares, worth well over $100 billion at current prices and the largest such release in Wall Street history. A second, larger tranche tied to the stock trading 30 percent above its $135 IPO price never triggered, since shares have spent most of July trading below that price.
Wall Street’s models point to revenue near $6.9 billion for the quarter, up sharply from the $4.69 billion SpaceX reported in the first quarter, with a narrower per share loss than the $1.27 posted three months earlier, according to estimates compiled by Motley Fool. Those numbers will be the first look at how SpaceX’s three segments, Starlink, launch and AI, are performing independently.
SpaceX scores another massive Pentagon deal to support military satellites
Investors heading into the call have a specific list of questions. How many net new Starlink subscribers did SpaceX add after ending March with 10.3 million, and is average revenue per user holding up as the service expands into lower income markets. How much of the AI segment’s revenue reflects contract signings with Anthropic, Google and Reflection AI this year, deals that combined could annualize to nearly $28 billion if fully ramped. Whether capital expenditures, which nearly doubled in the AI segment alone between 2024 and 2025, are still accelerating or starting to plateau. And whether management offers any forward guidance at all, something SpaceX has never done publicly.
The report will also land days after Elon Musk publicly denied a Wall Street Journal report describing internal planning to separate Tesla’s China business ahead of a potential Tesla-SpaceX merger. Whether Musk or SpaceX executives address that speculation on the call, even indirectly, maybe something investors will be listening for on Tuesday.
As Teslarati reported after Musk’s own warning to short sellers last week, the CEO has made clear he expects skeptics to be proven wrong over time. Tuesday will be the first chance for the numbers themselves to make that case.
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Elon Musk
SpaceX’s Starship just got filmed by its own cargo
SpaceX released new footage of Starship in space captured by the Starlink satellites it deployed.
SpaceX released a new video Friday evening showing Starship from an angle showcased by its own Starlink satellites, watching the rocket drift away in orbit.
The 65 second clip, posted on X, stitches together footage from four cameras mounted on a single Starlink V3 satellite. It opens with a close view of Starship’s 171 foot upper stage, still catching sunlight, then pulls back as the two spacecraft separate.
The footage comes from Starship’s 13th flight test, which launched July 24 from Starbase after a scrubbed attempt and an abort caused by an engine issue the week before. When Flight 13 finally flew, it carried the first batch of functional Starlink V3 satellites Starship has ever deployed, twenty of them, with six equipped with cameras meant to scan the ship’s heat shield during reentry.
View of Starship in space from a Starlink V3 satellite on Flight 13.
This composite is made of imagery from four separate cameras on a single satellite. Six of the satellites were equipped with cameras to scan Starship’s heat shield and transmit imagery down to operators to… pic.twitter.com/sNTHHz5vLr
— SpaceX (@SpaceX) July 31, 2026
Flight 13 checked most of its boxes. Starship deployed all 20 satellites, relit a Raptor engine in space, and splashed down softly in the Indian Ocean off Western Australia. Musk’s longer term plan calls for a Starlink V3 constellation of 100,000 satellites, according to a recent FCC filing, with Starship as the only vehicle capable of launching them at the volume that requires. Each Starship flight is designed to carry up to 60 V3 satellites once the vehicle reaches routine service, well beyond what Falcon 9 can carry in a single mission.
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Starship is next expected to fly with an attempt at catching the ship itself with the launch tower’s mechanical arms, a maneuver SpaceX has so far reserved for the Super Heavy booster.
Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident
SpaceX’s biggest test yet arrives this week and it’s not a rocket launch
