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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.”
A Texas man has been arrested and charged with manslaughter after his Tesla crashed into a home last month, striking a woman inside and killing her. The driver, Michael Butler, claimed the vehicle was in self-driving mode, but information from Tesla shows that Butler overrode the system.
Butler was arrested on Wednesday and booked at the Harris County, Texas, jail. He remained in custody through Thursday and Friday; he did not enter a plea, and his next court hearing is scheduled for Monday.
Tesla finally clarifies fatal Texas crash, confirms driver manually overrode acceleration
There are a handful of new clues in the case that could clear Tesla of any wrongdoing, especially as the woman who was killed’s family, the Avilas, filed a wrongful death lawsuit against Tesla and Butler, seeking at least $1 million in damages.
Charging documents from the Harris County prosecutor now show that Butler, who was working DoorDash the evening of the accident, had been using Full Self-Driving mode without incident through the duration of multiple deliveries that evening.
In the moments leading up to the crash, while in FSD and approaching a left turn, Butler pressed the accelerator pedal, overriding FSD’s speed control, and continued to push it until it reached 100 percent. This caused rapid acceleration; the brake pedal was never pressed, and there is no data to show that Butler aimed to turn away from the curb or house.
The charging documents state:
“I noted that the brake pedal was never pressed in the final minute before the crash. I also did not see any data to indicate that the driver attempted to turn away from the curb that he eventually struck. Further, I observed that no mechanical error was detected or recorded by the vehicle before BUTLER and the Tesla struck the curb.”
Additionally, a forensic analysis of Butler’s phone showed that he searched Google around the time of the crash with queries questioning why FSD was “too timid,” “not aggressive enough,” and even searched, “FSD is not aggressive enough for city driving.”
The documents outlined this:
“Investigator Veal also informed me that he had received BUTLER’s cell phone from Deputy Amad and that HDAO digital forensics team had completed a data extraction and download of the phone. Multiple Google searches related to Tesla had been made from BUTLER’s phone in the months leading up the crash. I noted multiple searches in May of 2026 indicating an apparent frustration with Tesla’s FSD mode, including the following searches: “Tesla fsd not aggressive enough 2026 model,” “Tesla fsd not [sic) aggressive enough 2026,” “FSD is not aggressive enough for city driving,” and “tesla fsd too timid.”‘
Tesla had claimed just after the crash that its internal data showed Butler had overridden the system’s speed control and pressed the accelerator completely, causing the vehicle to travel at an excessive rate of speed. Eventually, the car slammed into Avila’s house, killing her.
Butler has now been formally charged with Manslaughter, a felony.
Tesla shocked with its quarterly delivery report yesterday by reporting it delivered 480,126 vehicles in the second quarter of 2026, a 25 percent year-over-year jump that crushed Wall Street estimates of roughly 400,000–408,000 units. Production reached 451,758, with Model 3 and Model Y accounting for the vast majority.
The result ended two years of annual delivery declines and drew down inventory, signaling demand that outpaced earlier production.
Tesla bears had long warned that the expiration of the U.S. federal EV tax credit would hammer demand. Without the $7,500 incentive, they argued, American buyers would balk at higher effective prices, leading to a sharp slowdown.
Will Tesla thrive without the EV tax credit? Five reasons why they might
That narrative has not played out as predicted. While U.S. EV sales faced broader headwinds, Tesla’s global numbers held firm, underscoring the company’s ability to offset domestic pressure through other levers.
There are several plausible factors that explain Tesla’s strength during this quarter. Let’s take a look at them:
Rising Gas Prices
Rising gas prices provided a powerful tailwind, especially in the U.S.
Geopolitical tensions tied to the Iran conflict pushed fuel costs higher earlier in the year, amplifying the lifetime savings of electric vehicles. Even as oil prices later moderated, the psychological and financial impact lingered, encouraging fleet operators and private buyers to accelerate EV purchases. European sales rebounded sharply, helping drive the quarter’s outperformance.
Full Self-Driving Adoption
Advances in Full Self-Driving (FSD) supervised software also appear to have boosted appeal. Tesla expanded FSD availability in select European markets and continued refining the system.
No complaints from me because I finally got to enjoy this drive on FSD; I usually like to manually drive down this mountain https://t.co/RBFniRPSR0 pic.twitter.com/XQ5sOpN1Yg
— TESLARATI (@Teslarati) June 26, 2026
For tech-oriented buyers, the promise of future autonomy and enhanced driver-assistance features adds perceived value beyond the car itself. This differentiation helps Tesla stand out in a crowded market where competitors focus primarily on hardware and basic range.
Pricing Strategy, Affordable Configurations
Tesla’s offerings and its pricing strategy during Q2 further stimulated demand. Tesla introduced lower-cost versions of the Model 3 and Model Y, widening accessibility without sacrificing core margins.
These moves countered affordability concerns and attracted buyers who had been waiting on the sidelines. Combined with attractive financing and leasing options, the pricing strategy converted interest into actual orders more effectively than many analysts expected.
Broad European Recovery
Supported by government incentives, corporate fleet electrification, and easing political headwinds around CEO Elon Musk, Tesla was supplied additional momentum through stronger registration numbers throughout Europe.
Strong exports from the Shanghai Gigafactory and a production ramp at Giga Berlin ensured supply met this resurgent demand. Corporate buyers, in particular, accelerated transitions to EVs to meet sustainability targets, providing a steady volume base.
These elements created a virtuous cycle that delivered the strong deliveries report. While bears correctly flagged the loss of the U.S. tax credit as a risk, Tesla’s diversified playbook demonstrated that it could remain resilient against those headwinds. The Q2 beat suggests the company remains adept at navigating shifting market conditions, even as competition intensifies.
A Tesla Semi was involved in a fatal collision on U.S. Highway 50 in Dayton, Nevada, on Sunday, June 28, 2026, marking the first known fatal crash involving the electric Class 8 truck. The incident occurred around 7:20 a.m. at the intersection with Traditions Parkway, approximately 40 miles east of Reno and close to Tesla’s Gigafactory Nevada.
According to the Lyon County Sheriff’s Office and the Nevada State Police Highway Patrol, a semi-truck struck two passenger vehicles stopped at a traffic signal. The truck hit the vehicles from behind. Two people were pronounced dead at the scene, and a third person suffered life-threatening injuries and was flown to a hospital, Forbes reported.
Preliminary statements gathered at the scene by the Lyon County Sheriff’s Office suggested the truck driver may have fallen asleep at the wheel. However, the Nevada Highway Patrol, which is leading the investigation, stated that the official cause has not yet been determined.
Additional information is expected to be released early the following week. The truck was seized for evidence as part of the ongoing probe.
Responders at the scene included deputies from the Lyon County Sheriff’s Office, personnel from the Nevada Highway Patrol, Central Lyon County Fire Department, and the Nevada Department of Transportation. The crash led to the temporary closure of U.S. 50 in both directions.
The Tesla Semi is Tesla’s battery-electric heavy-duty truck, produced at the nearby Gigafactory in Nevada. Authorities initially described the vehicle as a semi-truck; its make was subsequently confirmed through reporting and scene identification; an interesting bit of information here, as the Semi is not yet available publicly and many do not know that Tesla builds electric trucks.
The investigation remains active, with no further official details on contributing factors or vehicle systems released as of early July 2026.
This incident highlights ongoing scrutiny of commercial vehicle safety on Nevada highways, particularly involving fatigue. Law enforcement continues to gather evidence and witness statements.
Texas man charged in fatal Tesla crash where he blamed Autopilot
Tesla’s strong Q2 deliveries: Four key drivers behind the surprise
