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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.”
Tesla revealed plans to develop its own maps internally to fix Navigation issues and give owners more control over their routing.
On the company’s Q3 2026 Earnings Call, a question was asked about FSD Navigation issues, particularly speed limit recognition, parking, and routing. These are issues that surface from version to version and seem to be seriously challenging for Tesla’s AI team to resolve.
Tesla’s Head of AI, Ashok Elluswamy, said in response to the question:
“You’re totally right that we shouldn’t be depending on external people’s maps. So we are building our own maps, but not like the same way as OneMoreMap. We are building an entirely new architecture with essentially AI-based mapping and navigation.”
He continued:
“It’s going to be super awesome. It’s going to be integrated with voice. You can talk to it, ask for different routes. It’s going to learn your personalized preferences, plus the fleet preferences. The collective intelligence of all the cars is going to flow into making the maps and navigation super cool.”
Elluswamy said this issue should be confronted, and the mapping should be available for people by the time the v15 release starts deploying to customers.
“And over the next several months,” he added, “it’s just going to take over all of the navigation functions, parking, destination handling. And it will know you better than you know yourself in some regard for the driving task, and then handle it fully.”
Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much
Navigation is perhaps the most notable complaint with FSD, and although it has gotten better, it is still flawed. Much of the time, FSD will take people on routes that are not preferred by the driver, but Tesla tried to combat this with a routing feature in the Summer 2026 Update.
Tesla currently relies on Google for map data, but it is sort of counterintuitive to believe the company would rely on a third party for this. These improvements will be welcome, as routing and navigation have been such a pain point for so many owners for so long.
Quotes via Motley Fool
Tesla Full Self-Driving (Supervised) showed a record attach rate at delivery for new vehicles in the third quarter of 2026.
75 percent of new vehicle deliveries in North America included a subscription to FSD software, up from 55 percent in the prior quarter, a 20-percentage-point sequential gain in the company’s most mature market.
Tesla Q3 2026 Earnings results: in-line revenues, slight beat on EPS
Tesla shed light on the Q3 Shareholder Deck that 75 percent of new deliveries came with an FSD subscription:
“FSD (Supervised)⁴ attach rate continued to grow, reaching over 75% of new vehicle deliveries in North America – our most mature market – a nearly twenty percentage point sequential increase. We believe that FSD is driving demand in markets where it is available, and we continue to work with regulators to get it approved in other markets. “
The higher attach rate accompanied strong growth in the overall FSD consumer base, as active subscriptions rose to 1.75 million, a 67 percent year-over-year increase. For the first time, more than half of paid customers are on the monthly subscription, which is priced at $99 per month in the U.S.
People are buying FSD with a car attached, not the other way around
— Elon Musk (@elonmusk) October 21, 2026
The transition to subscriptions has accelerated since Tesla discontinued the one-time purchase option in most markets earlier this year. The recurring model improves revenue visibility and margins compared with large upfront payments. With three-quarters of North American deliveries now including FSD, the software is now an evidently large contributor to Tesla’s economics and ancillary revenue.
Geographic expansion remains important for further gains. FSD is now available in nine countries in the EU, and more than 100,000 customers have driven over 160 million kilometers. Tesla is pursuing broader EU-wide approval, with a related vote expected in December. Similar progress in additional markets could support higher attach rates beyond North America.
These results came as Tesla had a strong quarterly delivery performance of 486,532 vehicles in the quarter, which came with its largest passenger-vehicle backlog in four years. Battery supply continued to limit volume, but the company has pointed to FSD as a clear difference-maker that is helping sustain demand. As supervised capabilities improve, the attach rate will likely continue to improve.
At face value, it is a key measure of how Tesla is converting sales into autonomy progress.
Update: 10/22 10:51a – Para 1 consumers changed to “customers” for accuracy.
Tesla Cybercab units finally got a definitive date for when they will be able to be purchased by customers, ending speculation regarding whether the fully autonomous vehicle would be available in the near term.
During Tesla’s third-quarter 2026 earnings call on October 21, Vice President of Engineering Lars Moravy said the company is aiming to begin delivering its purpose-built Cybercab robotaxi to customers before year-end.
🚨 In short, Cybercabs are slated to go to customers by end of the year. All units are going into Robotaxi fleet currently, per @larsmoravy
Cybercab will be “transport-as-a-service,” but vast majority of Cybercab will be “Tesla-owned,” @elonmusk says https://t.co/R8Qu8QWdmp
— TESLARATI (@Teslarati) October 21, 2026
“We’re trying to get Cybercabs to customers by the end of this year, 2026,” Moravy said. He added that production is underway on the line at Gigafactory Texas, but “all of those are currently going to our own internal Robotaxi fleet.”
Moravy explained that as operations scale, Tesla will “mainly deliver fully designed autonomous vehicles to our customers,” with the Cybercab as the first such vehicle. Initial customer deliveries will start small while the company gains experience with delivery logistics, ownership models, fleet management, and operating autonomous vehicles outside its direct control.
CEO Elon Musk reinforced the limited nature of private sales, describing the Cybercab primarily as a “transport-as-a-service” offering rather than a personal ownership vehicle like the Model 3, Model Y, or upcoming Roadster. “The vast majority of the Cybercab stuff will be Tesla-owned and transport-as-a-service,” Musk said.
The Cybercab is a two-seater vehicle developed by Tesla without a steering wheel or pedals. It relies completely on Tesla’s Full Self-Driving suite and has been in production since February. Early units have been put in Tesla’s Robotaxi service as of early September, when the company launched rides to the public. Tesla previously indicated it would aim to sell Cybercabs for about $30,000.
Unsupervised Full Self-Driving is expected to ship to consumer cars during Q2 2027, Ashok Elluswamy, Tesla’s Head of AI, indicated during the call. Early buyers or fleet operators may receive vehicles whose autonomous operation remains geographically restricted due to lagging regulatory agencies. There are some hurdles that remain ahead of Cybercab deliveries.
Tesla is building its own maps to fix Navigation issues
Tesla buyers are buying for Full Self-Driving and not for the car, data shows
