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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.”
SpaceX is preparing for the 13th integrated flight test of its Starship system, with a targeted launch as early as Thursday, July 16. The 90-minute launch window opens at 5:45 p.m. CT from Starbase in South Texas.
This comes roughly seven weeks after Flight 12 on May 22, underscoring the company’s accelerating pace in its rapid development campaign. The mission will use the latest Starship and Super Heavy V3 vehicles equipped with Raptor 3 engines. Booster 20 will attempt a controlled boostback burn, followed by a splashdown in the Gulf of Mexico, while Ship 40 will follow a suborbital trajectory.
Starship’s thirteenth flight test is preparing to launch as early as Thursday, July 16 → https://t.co/Rp7VwBzpWx pic.twitter.com/jdpFlQUEpF
— SpaceX (@SpaceX) July 11, 2026
Key objectives for Flight 13 will include demonstrating reliable stage separation, engine performance under various conditions, and controlled reentry.
A major milestone for Flight 13 is the first deployment of 20 next-generation Starlink V3 satellites. These satellites feature advanced laser links for inter-satellite communication, deployable solar arrays, and onboard cameras, six of which will capture imagery of Starship’s heat shield during flight.
Several heat shield tiles on Ship 40 will be painted white to serve as imaging targets, while additional experiments test upgraded tiles on aft flaps, modified attachments on the aft skirt, and load-sensing tiles to measure stresses. The upper stage will also attempt a single Raptor engine relight in space before a targeted splashdown in the Indian Ocean.
These tests build directly on lessons from Flight 12, which introduced the V3 configuration but encountered issues including a booster flip anomaly during boostback and an engine-out event on the ship. Hardware and software modifications on Booster 20 and Ship 40 aim to improve engine relight reliability, startup sequencing, and overall robustness.
Next Starship launch aiming for Thursday https://t.co/SajPPd4pdb
— Elon Musk (@elonmusk) July 12, 2026
The short interval between Flights 12 and 13 highlights SpaceX’s iterative approach. Elon Musk has repeatedly emphasized that Starship launches will become “incredibly common” in the coming years.
The company envisions scaling to rates as high as one launch per hour within 4-5 years, potentially enabling thousands of flights annually. Such cadence is essential for Starship’s goals: establishing orbital refueling for lunar and Mars missions, deploying massive satellite constellations, and making life multiplanetary.
With each flight, Starship edges closer to full reusability and operational maturity. Success on July 16 would mark another step toward routine access to space and the ambitious vision of humanity becoming a spacefaring civilization.
Tesla shared a striking video showcasing the decommissioning of the original Model S and Model X assembly line at its Fremont Factory in Northern California. Completed in just 46 days, the teardown involved heavy machinery dismantling concrete pits, removing robotic arms and conveyors, and clearing the space for new production.
The post, captioned “End of an era,” captured both the end of a historic chapter and Tesla’s aggressive pivot toward its next major initiative, Optimus.
End of an era: Decommissioning the original Model S & X assembly line in just 46 days pic.twitter.com/kGEdfhl62h
— Tesla Manufacturing (@gigafactories) July 10, 2026
The decision to retire the Model S and Model X originated during Tesla’s Q4 2025 Earnings Call in late January 2026. CEO Elon Musk announced that production of the company’s flagship sedan and SUV would wind down by the end of Q2 2026, describing it as bringing the programs to an “honorable discharge.”
Custom orders ceased around early April 2026, with the final vehicles rolling off the line in early May. A special signature delivery ceremony on May 20 marked the emotional close for these vehicles, which had defined Tesla’s early success and luxury EV segment since the Model S launch in 2012.
The primary reason for tearing down the lines was to repurpose the valuable factory floor space for high-volume production of Tesla’s Optimus humanoid robot. Musk had indicated on Earnings Calls that the Fremont S/X line would be replaced by a dedicated Optimus manufacturing line targeting a capacity of one million units per year.
This move aligns with Tesla’s broader strategic shift from traditional vehicle manufacturing toward robotics and artificial intelligence, leveraging the company’s expertise in autonomy, AI training, and high-volume production.
Optimus, Tesla’s general-purpose humanoid robot, is designed to perform repetitive or dangerous tasks in factories, warehouses, and eventually homes. Powered by Tesla’s AI and Neural Networks, it aims to be a versatile, affordable platform. Production of Optimus Gen 3 is already underway in limited form at Fremont, with full-scale output on the converted line expected to begin in late July or August.
Tesla is targeting rapid scaling, with internal ambitions pointing toward tens or even hundreds of thousands of units annually by the end of 2026.
Longer-term, Tesla is constructing a much larger second-generation Optimus facility at Giga Texas, with potential capacity reaching millions of units per year. The company views Optimus as a transformative product that could eventually surpass its automotive business in scale and value, enabling widespread deployment of useful robots across industries. CEO Elon Musk has even predicted it would be the most popular product of all-time.
As one era closes at Fremont, another is rapidly taking shape.
Elon Musk posted a candid admission on his social media platform X on June 9, declaring that he had been “clearly wrong” about Anthropic. The statement marked a notable reversal from his earlier skepticism toward the AI company.
In September, Musk had written, “Winning was never in the set of possible outcomes for Anthropic,” reflecting his view at the time that the startup had lacked the foundation or even the trajectory to succeed in what is an incredibly intense race for advanced artificial intelligence.
Musk’s latest post came amid discussion of Anthropic’s reliance on external compute resources. He praised the company’s progress, stating that Anthropic is “obviously currently the leader in AI” and that “no company has released a model as good as Mythos/Fable,” with expectations of a strong follow-up in Mythos 2.
The tone shifted dramatically from dismissal to acknowledgement of superior performance.
I was clearly wrong about Anthropic. They are obviously currently the leader in AI. No company has released a model as good as Mythos/Fable and they will undoubtedly have Mythos 2 ready soon.
And I would never cut them off in a way that hurt them badly, even as a competitor.…
— Elon Musk (@elonmusk) July 9, 2026
The context of Musk’s comments added significance. Anthropic has been operating under a recent compute deal with SpaceXAI, Musk’s AI infrastructure-focused venture. The pair entered a short-term GPU lease agreement initiated in May, providing Anthropic access to critical computing power for training and deploying its frontier models.
SpaceXAI signs agreement with Anthropic for massive AI supercomputer access
Some observers had speculated that Musk could leverage this dependency to disadvantage a rival. Musk directly addressed the possibility, writing, “I would never cut them off in a way that hurt them badly, even as a competitor. That’s not my style.”
To support his commitment to ethical competition, Musk referenced concrete examples from his other companies. Tesla famously open-sourced its entire portfolio of electric vehicle patents in 2014. The move was designed to accelerate the global adoption of sustainable transportation technology rather than protect proprietary advantages.
Tesla also made its Supercharger network available to competing electric vehicle manufacturers, transforming what could have remained an exclusive charging ecosystem into a shared infrastructure that benefits the broader industry and reduces barriers for EV adoption.
Musk further pointed to SpaceX’s practices, noting that the company launches satellites for competing commercial systems “with no increase in price or use of unfair terms.” He extended the principle to his social platform, observing that “even my worst enemies attack me on this platform,” underscoring preference for open discourse over retaliation.
These examples have illustrated Musk’s long-standing philosophy that long-term technological progress is best served by open competition and infrastructure sharing rather than leveraging market power to stifle rivals. In the fast-evolving AI sector, where compute resources and model capabilities determine leadership, Musk’s stance suggests a willingness to compete on innovation and performance alone.
Musk’s admission arrives as SpaceXAI itself advances its own frontier models while maintaining business relationships across the ecosystem. By publicly correcting his earlier assessment and reaffirming principles of fair play, Musk highlights a model of competition that prioritizes advancement of the field over short-term tactical advantages.
SpaceX reveals Starship Flight 13 launch date
Tesla shows rapid teardown of Model S and X lines, paving the way for Optimus at Fremont
