News
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.”
News
Tesla Robotaxi-only Superchargers are starting to appear
For Tesla, these Robotaxi-only Superchargers represent more than convenient parking spots. They are the first bricks in a vertically integrated autonomy platform—vehicles, energy, and software working in seamless concert.
Tesla is starting to build out Robotaxi-only Superchargers as the company is truly leaning on its Full Self-Driving and autonomy efforts to solve passenger travel.
Last week, the company filed pre-permits in Arizona’s East Valley for two dedicated, non-public charging sites stocked with next-generation V4 Superchargers. The filings mark the first visible evidence of purpose-built infrastructure exclusively for autonomous Tesla vehicles, as they state they are not for public use.
In Chandler, Tesla plans to install 56 V4 stalls on an industrial parcel along South Roosevelt Avenue. Site documents describe a high-capacity setup supported by new SRP transformers, switching cabinets, and upgrades to existing underground lines.
A second site in Mesa, located at 5349 E Main Street in another industrial zone, carries the same private-use designation. Both locations sit well away from public roads and customer traffic, ensuring the chargers serve only Tesla’s internal fleet.
The sites were spotted by Supercharger observer MarcoRP.
On the same day, Tesla also submitted a draft for another proposed location in the city of Mesa, also listed as private use.
This site is located in an industrial area on the east side of the city. pic.twitter.com/jCC1IsKKKw
— MarcoRP (@MarcoRPi1) April 17, 2026
Phoenix’s East Valley offers an ideal launchpad for Robotaxi Supercharging: the location has a clean, grid-like street layout and year-round mild weather that minimizes camera degradation. Additionally, Arizona has welcomed self-driving pilots since Waymo’s early days.
By securing private depots now, Tesla can optimize charging cycles, reduce downtime, and maintain full control over vehicle hygiene and security, critical factors for high-utilization Robotaxi operations.
The type of Supercharger is telling as well, as they are V4, Tesla’s fastest and most efficient buildout.
V4 stalls deliver faster power and support bidirectional charging, features that will let idle Robotaxis feed energy back to the grid during off-peak hours. Because the sites are closed to the public, Tesla avoids congestion, vandalism risks, and the scheduling conflicts that plague shared stations.
The timing is telling. With unsupervised Full Self-Driving hardware already rolling out across the lineup and Cybercab production targets looming, Tesla is shifting from vehicle development to ecosystem readiness.
Charging infrastructure has historically been the gating factor for ride-hailing scale; building it ahead of the vehicles signals confidence that regulatory and technical hurdles are nearing resolution.
Tesla has been spotted testing Cybercab units in Arizona over the past few months, as well.
Interestingly, the permits show V4 Superchargers in the plans, although Cybercab will likely utilize wireless charging:
Tesla Cybercab spotted with interesting charging solution, stimulating discussion
For Tesla, these Robotaxi-only Superchargers represent more than convenient parking spots. They are the first bricks in a vertically integrated autonomy platform—vehicles, energy, and software working in seamless concert.
It appears Tesla is preparing to begin building out Robotaxi-only Superchargers to avoid the congestion and keep its autonomous fleet charged up to get ride-hailers to their destinations.
Elon Musk
ARK’s SpaceX IPO Guide makes a compelling case on why $1.75T may not be the ceiling
ARK Invest breaks down six reasons SpaceX’s $1.75 trillion IPO valuation may be justified.
ARK Invest, which holds SpaceX as its largest Venture Fund position at 17% of net assets, has published a detailed investor guide to why a SpaceX IPO may be grounded in a $1.75 trillion target valuation.
The financial case starts with Starlink, SpaceX’s satellite internet constellation, which has surpassed 10 million active subscribers globally as of early 2026, with 2026 revenue projected to exceed $20 billion. ARK’s research puts the total satellite connectivity market opportunity at roughly $160 billion annually at scale, and Starlink is adding customers faster than any telecom network in history. That growth alone would justify a substantial valuation.
Additionally, ARK notes that SpaceX has reduced the cost per kilogram to orbit from roughly $15,600 in 2008 to under $1,000 today through reusable Falcon 9 hardware. A fully operational Starship targeting sub-$100 per kilogram would represent a significant cost decline and open markets that do not currently exist. SpaceX executed a staggering 165 missions in 2025 and now accounts for approximately 85% of all global orbital launches. That infrastructure position took decades to build and would be nearly impossible to replicate at comparable cost.
SpaceX officially acquires xAI, merging rockets with AI expertise
The February 2026 merger with xAI added a layer to the valuation that straightforward financial models struggle to capture. ARK argues that at sub-$100 launch costs, orbital data centers could deliver compute roughly 25% cheaper than ground-based alternatives, without power grid delays, permitting friction, or land constraints. Musk has stated a goal of deploying 100 gigawatts of AI computing capacity per year from orbit.
The $1.75 trillion figure itself is not a conventional earnings multiple. At roughly 95x trailing revenue, it prices in Starlink’s adoption curve, Starship’s cost trajectory, and the orbital compute thesis together. The public S-1 prospectus, due at least 15 days before the June roadshow, will give investors their first complete look at the financials to test those assumptions. ARK’s position is that the track record earns the benefit of the doubt. Fully reusable rockets were considered unrealistic for years. Starlink was considered financially unviable. Both happened on timelines that surprised skeptics.
Elon Musk
Ford CEO Farley says Tesla is not who to look at for EV expertise
Interestingly, Farley has been one of the most hellbent CEOs in terms of a legacy automaker standpoint to push the EV effort. It did not go according to plan, as Ford took a $19.5 billion charge and retreated from its EV push in late 2025.
Ford CEO Jim Farley said in a recent podcast interview that Tesla is not who Americans should look at to beat Chinese carmakers.
The comments have sparked quite a bit of outrage from Tesla fans on X, the social media platform owned by Elon Musk.
Farley said that Chinese automakers are better examples of how to beat competitors. He said (via the Rapid Response Podcast):
“If you’re an American and you want us to beat the Chinese in the car business, you’re all going to want to pay attention, not necessarily to Tesla. Nothing against Tesla—they’ve been doing great—but they really don’t have an updated vehicle. The best in the business for us, cost-wise and competition-wise, supply chain, manufacturing expertise, and the I.P. in the vehicle, was really BYD. In this next cycle of EV customers in the U.S., they want pickups and utilities and all these different body styles. But they want them at $30,000, not $50,000. Like the first inning, they want them affordably.”
Despite Farley’s synopsis, it is worth mentioning that Tesla had the best-selling passenger vehicle in the world last year, and in China in March, as the Model Y continued its global dominance over other vehicles.
Musk responded to Farley’s comments by stating:
“This is before Supervised FSD is approved in China. Limiting factor is production output in Shanghai.”
This is before supervised FSD is approved in China. Limiting factor is production output in Shanghai.
— Elon Musk (@elonmusk) April 19, 2026
Interestingly, Farley has been one of the most hellbent CEOs in terms of a legacy automaker standpoint to push the EV effort. It did not go according to plan, as Ford took a $19.5 billion charge and retreated from its EV push in late 2025.
Ford cancels all-electric F-150 Lightning, announces $19.5 billion in charges
Instead, Ford is “doubling down on its affordable” EVs and said it would pivot from its previous plans.
Reaction from Tesla fans was pretty much how you would expect. Many said they have lost a lot of respect for Farley after his comments; others believe he is the last CEO anyone should be taking advice on EVs from.
Nevertheless, Farley’s plans are bold and brash; many consider Tesla the most ideal company to replicate EV efforts from. It will be interesting to see if Ford can rebound from this big adjustment, and hopefully, Farley’s plans to replicate efforts from BYD work out the way he hopes.