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Researchers develop artificial intelligence that can identify cancer cells

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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.

Microscopic image of skin cancer cells (squamous) in a mouse (blue). | Credit: Catherine and James Galbraith, Oregon Health and Science University, Knight Cancer Institute/NIH, CC BY-NC 2.0.

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.”

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Accidental computer geek, fascinated by most history and the multiplanetary future on its way. Quite keen on the democratization of space. | It's pronounced day-sha, but I answer to almost any variation thereof.

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Tesla Full Self-Driving shows stunning maneuver in Europe to silence skeptics

In a striking demonstration of autonomous driving prowess, Tesla’s Full Self-Driving (FSD) system recently showcased its capabilities on the narrow rural roads of the Netherlands. Captured in two in-car videos, the system encountered scenarios that would challenge even the most experienced human drivers.

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Credit: Tesla

Tesla Full Self-Driving, fresh on the heels of its approval for operation on European roads for the first time, showed off a stunning maneuver that will certainly silence any skeptics on the continent.

Fresh off its approval in the Netherlands, Full Self-Driving is working toward a significant expansion into more parts of Europe.

In a striking demonstration of autonomous driving prowess, Tesla’s Full Self-Driving (FSD) system recently showcased its capabilities on the narrow rural roads of the Netherlands. Captured in two in-car videos, the system encountered scenarios that would challenge even the most experienced human drivers.

In the first clip, a wide tractor occupied more than half the lane on a tight two-way road. Rather than braking abruptly or forcing a collision risk, FSD smoothly edged the vehicle onto the adjacent bike path—using the extra space with precision—before seamlessly returning to the lane once clear.

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The second clip was equally demanding: while overtaking a group of cyclists, an oncoming car approached at speed.

FSD maintained a safe, minimal buffer to the cyclists while timing the pass perfectly, avoiding any swerve or hesitation that could unsettle passengers or other road users.

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This maneuver highlights FSD’s advanced spatial reasoning and predictive planning. On roads often under three meters wide, with no room for error, the system calculated available clearance in real time, incorporated shoulder and path geometry, and executed a controlled deviation without compromising safety.

It treated the bike path as a legitimate extension of navigable space, something many drivers might hesitate to do, while respecting Dutch road norms and cyclist priority.

Such feats align closely with a growing library of impressive FSD maneuvers documented on camera worldwide.

In urban Amsterdam, for instance, FSD has navigated the world’s densest cyclist environments, weaving through hundreds of unpredictable bike movements on canal-side streets with tram tracks and pedestrians.

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One uncut drive showed it yielding smoothly at crossings, overtaking where needed, and even handling a near-perfect auto-park in a tight residential spot, demonstrating the same low-speed precision seen in the rural clips.

Teslas using FSD have tackled turbo roundabouts in the Netherlands, complex multi-lane circles notorious for geometry challenges, merging confidently while yielding to traffic. Similar clips depict smooth handling of construction zones, emergency vehicle pull-overs, and gated parking barriers, where the car stops precisely, waits for clearance, and proceeds without driver input.

Collectively, these examples illustrate FSD’s evolution toward handling the unpredictable.

The rural Netherlands maneuvers aren’t isolated. Instead, they reflect a pattern of spatial awareness, cyclist deference, and traffic anticipation seen from city streets to highways.

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As FSD continues refining through real-world data, videos like this one are certainly building a compelling case for its readiness on Europe’s varied roads.

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Tesla utilizes its ‘Rave Cave’ for new awesome safety feature

Part of the massive interior overhaul of both the Model 3 “Highland” and Model Y “Juniper” was the addition of interior accent lighting to help bring out the mood of the vehicle, increase the customization of the interior, and to create a unique listening experience.

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Credit: Tesla | X

Tesla is utilizing its ‘Rave Cave’ for an awesome new safety feature that will arrive with the upcoming Spring Update for 2026.

Part of the massive interior overhaul of both the Model 3 “Highland” and Model Y “Juniper” was the addition of interior accent lighting to help bring out the mood of the vehicle, increase the customization of the interior, and to create a unique listening experience.

Tesla added a Sync Lights feature that will strobe the accent strips with the beat of the music.

It is one of the most unique and one of the coolest non-functional features of a Tesla, as it does not improve the driving of the vehicle, but makes it a cool and personal addition to the interior.

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However, Tesla is going to take it one step further, as the Rave Cave lights will now be used for blind spot recognition. This feature will be added as the Spring 2026 Update starts to roll out.

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Tesla writes:

“Accent lights now turn red when an object is in your blind spot and your turn signal is engaged, or when an approaching object is detected while parked.”

This neat new safety feature will now increase the likelihood of a driver, who is operating their Tesla manually, of seeing the blind spot warnings that are currently available on the A pillar and on the center touchscreen.

These new alerts will now warn drivers of cross traffic as they back out of a parking space with little to no visibility of what is coming. It is a great new addition that will only increase the safety of the vehicles, while also utilizing something that is already installed in these specific Model 3 and Model Y units.

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The Model 3 and Model Y were the central focus of the Spring 2026 Update, especially considering the fact that the Model S and Model X are basically gone, with only a few hundred units left. Additionally, Tesla included new Immersive Sound and Car Visualization for the Model 3 and Model Y specifically in this new update.

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Tesla parked 50+ Cybercabs outside its Texas Factory with some crash tested

Dozens of Tesla Cybercabs have been spotted at Giga Texas crash testing facility ahead of launch.

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Tesla Cybercab fleet spotted at Gigafactory Texas [Credit: Joe Tegtmeyer)
Tesla Cybercab fleet spotted at Gigafactory Texas on April 13, 2026 [Credit: Joe Tegtmeyer)

Drone footage captured by longtime Giga Texas observer Joe Tegtmeyer shows over 50 units of Tesla Cybercab at the Austin factory campus, including several units clustered by Tesla’s on-site crash testing facility.

The outbound lot at Gigafactory Texas sits just outside the factory exit and serves as the primary staging area where finished vehicles are held before being loaded onto transport carriers or dispatched for validation testing. On any given day, the lot holds a mix of Model Y and Cybertruck units alongside the growing Tesla Cybercab fleet, as can be seen in the drone footage captured by Joe Tegtmeyer.

Tesla Cybercab fleet spotted at Gigafactory Texas [Credit: Joe Tegtmeyer)

Tesla Cybercab fleet spotted at Gigafactory Texas on April 13, 2026 [Credit: Joe Tegtmeyer)

Roughly 50 Cybercab units are visible across the campus, parked in tight organized rows. Most of the units visible still carry steering wheels and pedals, temporary additions Tesla included to satisfy current safety regulations while the vehicles accumulate real-world data ahead of full regulatory approval for a steering wheel-free design.

Tesla Cybercab fleet spotted at Gigafactory Texas [Credit: Joe Tegtmeyer)

Tesla Cybercab fleet spotted at Gigafactory Texas [Credit: Joe Tegtmeyer)

Tesla operates dedicated Crash Labs at both its Giga Texas and Fremont facilities that are purpose-built for controlled structural crash tests. Historically, automakers begin intensive crash testing roughly one to two months before volume production kicks off. The Cybertruck followed almost exactly that pattern. The Cybercab appears to be on the same track facility that we first saw back in October 2025.

Tesla Cybercab crash test units spotted at Gigafactory Texas [Credit: Joe Tegtmeyer)

Tesla Cybercab crash test units spotted at Gigafactory Texas [Credit: Joe Tegtmeyer)

The first production Cybercab rolled off the Giga Texas line on February 17, 2026. Volume production is now targeted for April. Musk previously wrote on X that “the early production rate will be agonizingly slow, but eventually end up being insanely fast,” and separately stated Tesla is targeting at least 2 million Cybercab units per year. Commercial robotaxi service in Austin is targeted for late 2026.

 

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