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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.”
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Tesla confirms crucial detail of Miami Robotaxi launch
Tesla has confirmed a crucial detail of its Miami Robotaxi launch, stating that the fleet is operating on an Unsupervised basis, joining a few other cities where company employees do not watch over the vehicles from inside.
Tesla’s Head of AI, Ashok Elluswamy, confirmed the detail on X, answering a highly speculated question about the Robotaxi Service in Miami, which was launched on June 3:
Unsupervised
— Ashok Elluswamy (@aelluswamy) July 3, 2026
The first launch of Robotaxi in Florida, Miami presents a unique opportunity for Tesla as it is operating the Unsupervised Robotaxi ride-hailing service in a major tourist hotspot in the Sunshine State. It also signals the suite will expand to other cities soon; many have requested Orlando, a heavy tourist spot with Disney and other resorts nearby, get access to the program soon as well.
Miami is getting a conservative rollout as well, just as Tesla has done with other cities. The initial geofence covers a compact 10–14 square mile zone in western Miami-Dade County, primarily West Miami extending toward Doral and Sweetwater. It is bounded roughly by SR-826 (Palmetto Expressway) to the north and US-41 (Tamiami Trail) to the south, excluding downtown Miami, Miami Beach, the airport, and most of Coral Gables.
Tesla has also been pretty slim on other details. For example, Tesla has not disclosed the exact fleet size, but field reports and license plate tracking indicate just two unsupervised Model Y vehicles were active on launch day, increasing to three within 48 hours.
According to The Road to Autonomy, a nearby staging lot near Miami International Airport holds dozens of Cybercabs alongside additional Model Y units, suggesting capacity for rapid scaling as demand and data collection grow.
The confirmation of Robotaxi being Unsupervised carries immense weight. It establishes that Tesla’s Miami Robotaxi operations run without human safety drivers or remote supervision, relying entirely on the company’s Full Self-Driving technology. Miami becomes the second major U.S. city after Austin to offer unsupervised Robotaxi rides from day one.
The move reflects rapid progress in Tesla’s AI efforts. Neural networks trained on vast real-world data now handle complex urban environments, including South Florida’s heavy traffic, pedestrians, and rainy conditions. Industry observers see it as validation of Tesla’s vision-centric, data-driven approach versus traditional rule-based systems; a truly unorthodox approach in this day and age.
Challenges remain, including regulatory oversight, public trust, and scaling the fleet to match geofence ambitions. Miami’s small initial footprint and limited vehicles highlight a deliberate, measured expansion strategy focused on safety and data gathering.
Nevertheless, the unsupervised confirmation marks a pivotal milestone. It showcases technical readiness and advances Tesla’s vision of transforming vehicles into autonomous revenue generators while reshaping urban mobility. For Miami users, driverless transportation has moved from concept to reality.
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Radiologist who drove Tesla off cliff has attempted murder charges dismissed
A California radiologist who drove his Tesla Model Y off a 250-foot cliff in an attempt to kill his family has had his charges dismissed after doctors say he is “doing well” in a mental health program.
Dharmesh Patel was charged with three counts of attempted murder in connection with a January 2023 crash where he drove his Tesla off a cliff, injuring his wife and two children, aged 7 and 4 at the time.
Patel drove the Tesla off Devil’s Slide in California, an area that is extremely rough to the point that investigators and rescuers expected the worst when arriving at the scene for the first time. Patel supposedly had schizoaffective disorder, according to Deputy District Attorney Dominique Davis.
Shockingly, Patel’s wife, who was in the vehicle, testified that she did not want her husband to be prosecuted, noting that their children missed their father and they wanted him to come back home. Patel’s attorney argued, “not everyone who commits a crime is a criminal.”
Doctor who took Tesla off cliff gets support from unlikely person
A three-day trial in Mental Health Diversion Court ruled in Patel’s favor, which kept him out of jail and instead on house arrest. He was admitted to a Mental Health Diversion Program, which he successfully completed, the Associated Press reported. San Mateo County District Attorney Steve Wagstaffe said the judge was “required by law” to dismiss the charges:
“If the person who’s given mental health diversion follows the treatment plan, there’s nothing that can be done, and at the end of the two years he gets it wiped out of his record.”
Wagstaffe said he has argued, along with other DAs in California, to have attempted murder removed from the list of charges eligible to be dismissed due to mental health diversion programs.
Patel had the charges officially dismissed on Monday; his wife waited for him as he left court and they departed the building together, according to Mercury News. Patel surrendered his California medical license in December.
The crash has been one of the best examples of Tesla’s incredible engineering, which has saved four lives in this particular instance. The car was totalled but kept the four human beings alive and safe, which is something that many referred to as “an absolute miracle.”
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Tesla battery recycling efforts increased 20 percent last year
A common misconception of anti-EV proponents is that the batteries used in the vehicles are detrimental to the environment and that they cause more waste than they are worth. But a look at Tesla’s battery recycling efforts last year shows the company is doing more than ever to recover materials and give portions of the cells a second life.
Tesla reported a significant milestone in its sustainability efforts last year, with battery recycling volumes rising 20% compared to 2024. According to the company’s 2025 Impact Report, Tesla recycled over 14,000 metric tons of battery material through a combination of in-house processing at its Gigafactories and collaborations with third-party recycling partners.
Tesla: “In 2025, we recycled over 14,000 metric tons of battery material through a combination of in-house processing and through our network of recycling partners.”
That’s equivalent to 46,000 long-range battery packs, a +20% increase from 2024. pic.twitter.com/TC3Nz7Kaqf
— Sawyer Merritt (@SawyerMerritt) July 7, 2026
This amount of recovered material is equivalent to the resources needed to produce approximately 46,000 long-range battery packs. The increase reflects growing operational scale as Tesla’s global vehicle fleet expands and more batteries reach end-of-life or manufacturing scrap becomes available for processing.
Tesla and Battery Recycling
Battery recycling forms a core part of Tesla’s circular economy strategy. The company designs its batteries for longevity, often exceeding 200,000 miles of driving, and prioritizes repairs, remanufacturing, and second-life applications before full recycling.
Once packs are decommissioned, Tesla ensures 100% are recycled with no materials sent to landfills. This approach recovers critical metals including lithium, nickel, cobalt, and copper, which can be refined and reused in new battery production.
Tesla has advanced hydrometallurgical recycling processes capable of achieving recovery rates up to 98% for key battery metals. These methods are more efficient and environmentally friendly than traditional pyrometallurgical techniques, reducing energy use and enabling higher-purity materials suitable for direct reintegration into battery manufacturing.
Tesla co-founder JB Straubel confirms Redwood’s battery recycling operations are already profitable
In-house capabilities are supplemented by a network of specialized partners, creating a robust system that handles both production scrap and end-of-life packs.
The environmental and economic benefits are substantial. Recycling reduces reliance on virgin mining, lowers the carbon footprint associated with raw material extraction and processing, and helps stabilize supply chains for critical minerals amid rising global EV demand. As millions of Tesla vehicles age, the volume of recyclable material is expected to grow significantly in the coming years.
This 20% year-over-year growth demonstrates the effectiveness of Tesla’s investments in recycling infrastructure and technology. It positions the company as a leader in addressing one of the automotive industry’s major sustainability challenges. Continued innovation in battery design for easier disassembly and higher recyclability will further enhance these efforts.
Overall, Tesla’s progress in 2025 highlights how scaling recycling operations supports both environmental goals and long-term business resilience in the transition to electric mobility. As the EV market matures, such closed-loop systems will become increasingly vital for sustainable growth.