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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 (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue

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Credit: Tesla

Tesla (NASDAQ: TSLA) reported its earnings for the first quarter of 2026 on Wednesday afternoon. Here’s what the company reported compared to what Wall Street analysts expected.

The earnings results come after Tesla reported a massive beat on vehicle deliveries for the second quarter, delivering 489,126 vehicles and building 451,758 cars during the three-month span.

This was a major shock for those on Wall Street as they anticipated somewhere around 400,000 deliveries for the quarter, and showed Tesla still has plenty of demand for its vehicles around the world and in the U.S. despite losing the $7,500 EV Tax Credit last year.

Tesla Q2 2026 Earnings Results

  • Non-GAAP EPS – $0.33 reported vs. $0.53 expected
  • Revenues – $28.236 billion reported vs. $26.4 billion expected
  • Free Cash Flow- -$1.092B
  • Profit -$ 4.751B

Tesla (beat/missed) analyst expectations, so the market response to the company’s quarter is what we will look for next.

Tesla shares closed today down just over 1 percent, trading at $374.01.

In the past, it has been anyone’s guess with what Tesla shares will do after they report earnings. Strong quarters have resulted in sharp drops, while lackluster quarters have seen the stock shoot up considerably.

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Tesla will hold its Q2 2026 Earnings Call in about 90 minutes at 5:30 p.m. on the East Coast. Remarks will be made by CEO Elon Musk and other executives, who will shed some light on the investor questions that we covered earlier this week.

You can stream it below. Additionally, we will be doing our Live Blog on X and Facebook.

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Tesla is about to make parking in busy lots less stressful than ever

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Tesla FSD 14.3 [Credit: TESLARATI)
Tesla FSD 14.3 [Credit: TESLARATI)

Tesla is about to make parking in busy parking lots at businesses and other points of interest less stressful than ever by allowing drivers more control over where they park and how, CEO Elon Musk confirmed on X.

Tesla has been working to improve the parking performance of vehicles utilizing the Full Self-Driving suite, but now it is looking to add more customization, allowing drivers to choose the specific space they park in, but also potentially the orientation the car pulls into the spot:

Musk has reiterated on X twice over the past several weeks that Tesla is working to make things with the FSD suite based more on the driver’s specific preferences and behaviors that were seen in past drives.

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Essentially, it sounds like if you tend to park away from a business to avoid other vehicles, Tesla FSD will soon recognize that preference of yours and start parking further away as well. Additionally, the prospect of assigned parking spaces has been something many owners have voiced concerns about.

Living in a community with assigned parking spaces makes using FSD incredibly difficult as it will rarely park in the correct spot when there are so many to choose from. This is also pertinent in work settings where there are sometimes assigned parking spaces.

The updates to Tesla’s Full Self-Driving suite in terms of listening to driver preferences with parking are also extending to routing. Tesla announced yesterday that with the release of its 2026 Summer Update, it was adding Automatic Navigation and Preferred Routes:

Tesla reveals 2026 Summer Update with crazy fixes to Nav and more

Tesla has always maintained the idea that any human input is bad input, and that, ideally, Tesla Full Self-Driving will always make the right decision. Of course, this is all in theory, but the issue is that so many of Tesla’s interventions have come because it does something that is not necessarily wrong, but perhaps not what the driver would prefer.

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Taking these preferences into account will help Tesla alleviate some of the potentially unnecessary interventions that drivers perform.

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Tesla starts preparing for Optimus in its smartphone app

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Tesla is starting to prepare for the launch of the Optimus robot in its smartphone app, new coding strings show. Elon Musk has referred to Optimus as what will be the greatest-selling product of any kind of all time, and now, Tesla is getting ready for its launch.

Tesla’s smartphone app had several first-time mentions of the Optimus program, according to Tesla App Updates, who intially reported on the appearance. Here’s what they found:

A Dedicated “Robot” Phone Key Authentication

Tesla is working on a Bluetooth Low Energy, or BLE, authentication that is specifically for robots. This does not only apply to Optimus, though, as Robotaxi, which is Tesla’s autonomous ride-hailing platform, might also identify vehicles within the fleet as robots as well.

Tesla shows rapid teardown of Model S and X lines, paving the way for Optimus at Fremont

Essentially, pairing your phone as a key to anything Tesla identifies as a robot to a “whitelist” of authorized devices. Optimus, Robotaxi, or other products that fall into this category will only respond if the device trying to communicate with it is authorized.

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This is a great security feature that will eliminate at least face-value and low-level threats.

Home Data Collection and System Alerts

This appears to be somewhat of a neural network for Optimus within your house. There will be a dedicated screen that asks for consent to collect both video and spatial data while Optimus performs in-home tasks. Everything from vacuuming, washing dishes, dusting, and other activities will be tracked.

There will also be a comprehensive alert system that will track everything from low battery to mechanical issues.

Other Changes

Most of the changes tracked in this particular app update are related to Tesla’s 2026 Summer Update, and include things such as image assets for new features, a preview of the new custom wraps feature, and other unique features.

You can check out our coverage on what is included with the 2026 Summer Update here:

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Tesla reveals 2026 Summer Update with crazy fixes to Nav and more

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