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Researchers develop artificial intelligence that can identify cancer cells
Scientists from Osaka University in Japan have developed artificial intelligence (AI) that can identify different types of cancers based on microscopy images of their cells. The AI was also able to determine whether the cancer cells were resistant to radiation, and further learned the differences between human and animal cancers. Since the accuracy and timeliness of traditional methods of identifying cancer cells are prone to delays and errors, an accurate and automated system for accomplishing this would be beneficial to cancer research and treatment overall. The results of the scientists’ research were published in the December 2018 issue of Cancer Research.
The type of AI developed for the cell identification is called a convolutional neural network (CNN); it’s loosely based on the connectivity patterns used by neurons in the brain and primarily used for classifying images. As described in their publication, the scientists used a training set of 10,000 images each of human cervical cancer cells (ME-180) and mouse squamous cancer cells (NR-S1), e.g., the thin, flat types of cells found on the surface of the skin and thin linings around various organs throughout the body. They also included images of radioresistant clones with the set, and ultimately obtained a 96% accuracy in a 2,000 image test.
Because the types of cells in a single cancerous tumor can vary widely, identifying the specific cells present is important for determining the best treatment. Thus, having a tool to provide this information quickly and accurately could have a significant impact. The Osaka team hopes to expand the types of cancers their AI can identify and ultimately establish a universal system that can identify all cancer cell types.
Using artificial intelligence in the battle against cancer is being explored throughout the world as the number of uses devised expands. In one notable instance, a team of scientists from The Institute of Cancer Research in London and the University of Edinburgh has developed an AI technique called REVOLVER (repeated evolution of cancer) which identifies DNA mutation patterns in cancers to predict the ways they will change in response to treatment. Similar to how bacteria become resistant to antibiotics, so too can cancers become resistant to the drugs used against them. By removing the unpredictability variable in cancer behavior, scientists would be able to stay ahead of the disease’s progress and tailor treatments accordingly.
The collaboration between AI and healthcare overall is growing, not just in cancer research – even Google is making contributions to the field. Fortunately, the agencies regulating developments are also attuned to the changes. Earlier this year at the AcademyHealth 2018 Health Datapalooza, the U.S. Food and Drug Administration (FDA) Commissioner Scott Gottlieb, MD signaled the agency’s positive position towards the field. “AI holds enormous promise for the future of medicine, and we’re actively developing a new regulatory framework to promote innovation in this space and support the use of AI-based technologies,” he stated at the event. He also referred to the agency’s plans to streamline their regulations and tools to be sufficiently flexible to handle the rapid pace of advancements and “focus on the ways in which real-world data flows.”
Ahead of its highly anticipated unveiling, Tesla’s upcoming Roadster received a new patent that aims to keep it grounded while enabling white-knuckle speeds.
The patent, which was granted on September 29, is titled “Electric Car Fan,” bluntly stating its design but not its purpose, which is further detailed in the text of the application. Interestingly, it comes two weeks before the Roadster event, which was delayed due to unfavorable weather on Thursday, which could cause issues, as Tesla revealed the event must be held outdoors.
🚨 The design uses electrically driven ducted fans, typically shown as a row of four at the rear, powered by the vehicle’s high-voltage battery.
The fans pull air from an underbody inlet, route it through ducts, and expel it from a larger rear outlet that functions as a… https://t.co/CHQB9u9UA3 pic.twitter.com/QVXmWTdggh
— TESLARATI (@Teslarati) September 29, 2026
The purpose is to solve a problem that is relatively unique to high-performance electric cars. Instant motor torque is useless if the tires cannot plant that force, and conventional wings and underbody tunnels generate downforce only when air is already rushing past the car. At launch, in slow corners, and under hard braking from modest speed, passive aerodynamic additions contribute essentially very little to downforce.
Tesla’s filing says that its fans can produce the downforce needed, independent of vehicle velocity, then ease off so the same hardware does not pile on drag at highway speeds, an issue that can come from excessive body modifications.
The hardware outlined in the patent is a ducted-fan package that is placed into the rear of the vehicle. An underbody inlet between the rear wheels feeds a duct that rises to a wide outlet in the diffuser. In that outlet are four axial fans, which are divided by vertical strakes. They will pull air from under the floor and press the chassis onto the pavement.
The language in the patent claims it can cut drag rather than add to it while simultaneously increasing downforce.
Tesla Roadster event requires restricted airspace, and the FAA obliges
The fans run from the high-voltage battery and a vehicle control system, so output can be modulated rather than left on as a fixed penalty.
There are additional strengths that can come from this design, like extra tire load at low speed, which can contribute to even more face-melting acceleration rates, decrease stopping distance, and sharper turn-in before a wing has air to work with. Adjustable fan speed lets the car add grip only when needed, so it can be catered to the force of a turn or acceleration.
These designs were previously used, and banned, in some competitive settings. The Brabham BT46B was banned in F1 competition for using a similar fan design and being labeled as too effective.
Tesla still lists the Roadster as having a sub-two-second 0-60 MPH time and a 250-plus-MPH top speed, and there are expectations for a SpaceX cold-gas thruster package that could not only increase acceleration but potentially cause the vehicle to hover.
It is important to note that a patent is not a production part, and packaging four fans in a rear diffuser, managing noise, and potential debris are all things Tesla must consider. With that being said, the patent being granted shows Tesla is designing the Roadster to go fast, but it is also attempting to use unique strategies to combat any issues it might have at those speeds.
Tesla (NASDAQ: TSLA) showrooms have been picked clean ahead of the end of the third quarter of the year, as demand looks to be strong and delivery estimates for new vehicles are pushed into late 2026 and early 2027.
Tesla appears to have sold out of many of its Model 3 and Model Y trim levels in the United States, as only the Model Y RWD and Model Y All-Wheel-Drive are available for delivery before the end of the year.
Additionally, many showrooms are either completely empty or void of all but just one demo unit within the buildings themselves in an effort to bolster what could be one of Tesla’s best quarters in vehicle deliveries in recent memory.
I’m at Tesla right now and when I walked into their showroom I was shocked to see it basically empty.
I asked one of the people working there where all of the cars are “Gone – it’s the end of the quarter and we’ve sold out of everything… including the display vehicles”So… pic.twitter.com/rN7s3gE6sJ
— Devin Olsen (@DevinOlsenn) September 25, 2026
All the cars are gone from Tesla Century City!
All they have is Model Y L, a self-driving video playing on the background. I guess the best product is no product. Either that or they just sold the showroom cars. pic.twitter.com/mzCjWaXwww
— Whole Mars Catalog (@wholemars) September 26, 2026
Show room is empty. I asked and they have sold the demo cars too. Delivery numbers better be outstanding! pic.twitter.com/jq5N28Q6tZ
— Electric Brawl (@3lectricBrawl) September 22, 2026
Additionally, when I spoke to the guys at Tesla Mechanicsburg two weeks ago, when I returned the Model Y L, their third hauler of the week had just arrived, and every vehicle on it, along with every vehicle in their delivery lot, was accounted for and had a name attached to it for delivery.
Talking to the guys at the Mechanicsburg showroom on Friday, they couldn’t believe they had ANOTHER hauler coming in of cars for delivery—and each was accounted for
No car just sitting in inventory. They’re expecting a BIG quarter, and this is more than just the Y L https://t.co/ce801GkKVv
— TESLARATI (@Teslarati) September 21, 2026
Tesla saw a 25 percent increase in deliveries in Q2 compared to the same quarter the year before. The vast majority of the 480,126 units it delivered, 467,762 vehicles to be exact, were the Model 3 and Model Y.
In Q3 2025, Tesla delivered 497,099 vehicles, once again a figure that was dominated by the company’s two mass-market vehicles. Analysts have unusually wide predictions for this quarter, likely because so many firms missed the Q2 delivery figure by such a substantial margin; Wall Street predicted 408,000 cars, while Tesla delivered 480,000.
Goldman Sachs has Tesla slotted for 435,000 deliveries in Q3, while JPMorgan said it anticipates 482,000. The median guess is about 449,000 deliveries for Q3.
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Tesla’s Automatic Collision Evasion feature can be seen in one of the first owner videos of it in action.
Tesla owner Spencer (@scotsrule08) posted on Monday that the feature “worked flawlessly,” saying FSD reengaged itself just as he was about to hit a curb. Ashok Elluswamy, who leads Tesla’s AI team, shared the clip and wrote, “A guardian angel always looking out for you.”
The video arrives in the middle of a staged rollout. Tesla first shipped Automatic Collision Evasion with FSD (Supervised) v14.3.9 in software update 2026.27.6 earlier this month, which Teslarati covered as it reached cars. Update 2026.27.10, which began going out on September 19, carried the feature improvements with FSD v14.3.10, according to release notes tracked by Not a Tesla App. The newer 2026.27.11 build is now reaching another wave of vehicles.
The new Automatic Collision Evasion feature worked flawlessly! FSD reengaged itself just as I was about to hit a curb.
Kudos @Tesla_AI team! 👏 pic.twitter.com/Fbp15HhpL2
— Spencer (@scotsrule08) September 28, 2026
The feature only runs on HW4 vehicles, and it requires an active FSD purchase or subscription with both FSD (Supervised) and Automatic Emergency Braking enabled. HW3 owners receive FSD v14.2 Lite in the same updates, but that build does not include collision evasion.
Tesla’s release notes describe two triggers. The first is an imminent frontal collision that braking alone may not prevent, in which case the car can activate FSD to steer, brake or accelerate around the hazard. That scenario is limited to highways below 85 mph, with no pedestrians or cyclists detected and no slippery road surface. The second covers a driver who appears inattentive, such as reaching into the back seat, or who seems to have switched off FSD by accident. Spencer’s curb clip appears to fall into that second category.
Tesla plans big safety improvements for Full Self-Driving v15
Once the system takes over, the accelerator is muted and light brake input will not cancel the maneuver. Drivers need to apply firm, deliberate steering force to take back control, and the car chimes to hand control back once the danger has passed.
Elluswamy recently noted that earlier hazard prediction, faster reaction time and better collision avoidance would arrive with FSD v15, the next major version.
Tesla Roadster’s new patent preps white-knuckle speeds, keeping it grounded
Tesla showrooms picked clean ahead of Q3 end as demand looks strong
