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AI dominates China’s elite doctors in cancer diagnosis competition

[Credit: China Daily/Twitter]

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A custom-built AI designed to diagnose brain tumors and predict hematoma expansion dominated some of China’s best doctors in a competition last Saturday in Beijing. The AI, dubbed BioMind, ultimately scored 2:0 against its human competitors, comprised of 15 senior doctors from China’s premier hospitals.

BioMind was developed by a collaboration between a team from the Artificial Intelligence Research Center for Neurological Disorders at the Beijing Tiantan Hospital and researchers from the Capital Medical University. BioMind’s developers opted to feed the AI with data sets featuring tens of thousands of images depicting nervous-system-related diseases, which were retrieved from Tiantan Hospital’s archives stretching over the past decade.

Wang Yongjun, executive vice-president of Tiantan Hospital, stated that this training ultimately enabled the AI to become proficient in diagnosing neurological diseases such as meningioma and glioma with an accuracy rate of over 90%. According to Wang, such rates are comparable to the accuracy of a senior doctor, according to a report from state-owned Xinhua News.

During its the competition on Saturday, BioMind was able to correctly diagnose brain tumors with an accuracy rate of 87% out of a total of 225 cases. The AI was also able to complete its task in 15 minutes. In comparison, the team of 15 elite doctors was able to achieve an accuracy rate of 66% when diagnosing brain tumors, finishing the task in 30 minutes. Apart from this, BioMind was able to make correct predictions in 83% of brain hematoma expansion cases, while its human competition displayed a more conservative 63% accuracy.

Despite the AI’s strong performance against China’s elite doctors on Saturday, however, Cheng Jingliang, a professor of radiology at the First Affiliated Hospital of Zhengzhou University, stated that artificial intelligence systems for the medical field are still well into their infancy. According to Cheng, AI is already being used in hospitals to help doctors read images such as lung scans, but when it comes to giving full diagnoses to patients, artificial intelligence still lags far behind that of senior medical professionals.

In a statement to China Daily, Paul Parizel from the Antwerp University Hospital in Belgium, who served as a member of the jury during last Saturday’s AI vs. human doctors competition, believes that systems such as BioMind would prove to be incredibly valuable when integrated to existing medical practices.

“It will be like a GPS guiding a car. It will make proposals to a doctor and help the doctor diagnose. But it will be the doctor who ultimately decides, as there are a number of factors that a machine cannot take into consideration, such as a patient’s state of health and family situation,” he said.

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The United States initially led the artificial intelligence race, but over the years, China has steadily gained ground in the AI industry. Thanks to a population that is compliant to the application of new technologies, as well as a government that actively pushes AI researchers to push further, China is on track to overtake the United States in the near future. Last January alone, the Chinese government announced plans to build a $2.1 billion technopark in Beijing that is expected to house companies actively involved in AI research and development. The United States does not have a comparable initiative to date. This was confirmed by Jack Clark of Elon Musk-backed OpenAI, who previously stated that the country lacks a central national strategy on artificial intelligence.

“It is confusing that we have this technology of such obvious power and merit and we are not hearing full-throated support, including financial support,” Clark said.

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident

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Credit: Teslarati

Tesla released Full Self-Driving version 14.3.7 yesterday, and after about 90 miles of testing today, it is evident there are some definite fixes from version 14.3.6, which I wrote about last week and called a regression.

Within the first 40 minutes of my drive on v14.3.7, it saved me from getting into an accident with an unaware Dodge Charger driver, and some of the things Tesla seemed to miss in v14.3.6 were definitely improved. All in all, the release so far has some really great performance, and I’m looking forward to testing it further.

For now, here’s everything I noticed with v14.3.7:

Overall Improvement

Just generally speaking from a ride perspective, this was a really great experience. A lot of the hesitancy I experienced on v14.3.6 was gone. There were no instances of brake-stabbing, wheel-jerking, or any uncertain or unconfident movements. It was void of anything that I felt made it timid with v14.3.6.

The one thing I do hope to see down the road is a smaller need to adjust Speed Profiles so often. Because Tesla calls FSD “Supervised,” I’m okay with needing to hit the scroll wheel a few times a drive.

However, I hope that things can be incrementally improved upon with speed. Sometimes it’s too fast; other times it’s too slow. It’s a difficult thing to hone in and refine, but I hope it eventually gets there.

I didn’t notice any significant left lane camping or any behaviors that were completely out of line. I am hopeful that this opinion does not change, but after driving a few days with this version and putting it in a variety of different situations, you are exposed to more behaviors, some of which are not necessarily what I’d prefer.

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The big things to notice, at least in my experience thus far, are that the major issues with previous versions — meaning the braking stabbing and wheel jerking — simply weren’t there. That’s enough to already consider this progress compared to .6.

Manual Signal Override is More Responsive

On .6, I had quite a few issues with FSD ignoring my manually input turn signals. If Tesla wants to call it “Supervised,” then the car should not ignore any input the driver gives. If I touch the accelerator on FSD, the car speeds up.

The car did a great job of obeying my turn signals when I wanted it to change lanes, which is welcome.

Parking Lot Performance

Before .6, I traditionally took over in nearly every parking lot my car entered, because I knew it would not park somewhere that I wanted, and usually, it was just a tad too timid in this setting.

The one bright spot of .6 was how well it handled parking lots. This continued with v14.3.7:

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I’m always really happy to see progress at all, but once parking preferences come to FSD, as long as this performance is still around, that could potentially be the biggest improvement I’ve seen in FSD in the year I’ve been using it personally on a daily basis.

Full Self-Driving Averts Disaster

A Dodge Charger changed into my lane without checking if I was there, running me off the road. FSD made the initial avoidance maneuver; I grabbed the wheel out of instinct, looked in my side mirror to ensure I had nobody following closely behind, hit the brake, and straightened the car back up to avoid a curb:

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There have been quite a few responses to this video stating that I should never have grabbed the wheel. To be honest, I really wish I had not done so, because I do believe FSD would have avoided any sort of collision with anything, including the car or the curb.

However, this was the first time I had ever been this close to being hit while using FSD. My natural reaction was to take over. I think if I had had something like this happen before, my reaction might have been different.

Hitting the brake avoided hitting the curb, while FSD swerved to avoid the car. My concern after the car was clear of my front end was the curb. All in all, I’m really happy with how things turned out, and I think anyone could be a critic of how I handled it. I only had a split second to really make a decision, and thankfully, any damage was avoided.

It is clear FSD managed to avoid the car coming down before I was able to. I truly credit FSD for avoiding the collision.

What Needs to Improve

Better Recognition of Potholes, Uneven Roads, Sharp Changes in Roadway/Bumps

On Friday, my Fianceè and I were in the car, and FSD was driving us. We crossed over a roadway that has a traffic light, and FSD was traveling at 40 MPH on Standard, 5 MPH over the speed limit. Everything was more than reasonable.

However, the road we were crossing at the light has a major bump both as you start and finish crossing it. Without a speed reduction, your car can go airborne. The Tesla did just this on Friday on v14.3.6; it was an uncomfortable bounce that pretty much confirmed I would not ever let FSD go over again unless we were sitting at that intersection when there is a red light.

I even tried scrolling down into Sloth quickly, but I ended up just taking over:

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A few people have said it remains related to the vision-based approach and its difficulty comprehending 3D. This is a huge issue because this can cause serious damage at certain speeds.

Navigation

Nothing new here. I still turn off “Online Routing” quite frequently to get the car to take logical routes from time to time.

Auto Wipers

Auto Wipers are just plain bad. I really hope Tesla just uses a rain sensor. I thought they had improved at one point, but I still get dry wipes, Speed 4 on a drizzle, and Speed 2 on a steady rain. In reality, these should be switched.

You can watch our full review of Tesla Full Self-Driving v14.3.7 below:

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SpaceX’s biggest test yet arrives this week and it’s not a rocket launch

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SpaceX will report second quarter results after the market closes on Tuesday, August 4, marking the first time the company has opened its books to the public since its record IPO in June. Management will host a live audio only webcast at 4:30 p.m. ET, streamed on X, with no dial in option.

The debut carries more weight than a typical first quarter as a public company. Two trading days after the release, on August 6, the first tranche of SpaceX’s lockup expires, freeing roughly 911.5 million insider and employee shares, worth well over $100 billion at current prices and the largest such release in Wall Street history. A second, larger tranche tied to the stock trading 30 percent above its $135 IPO price never triggered, since shares have spent most of July trading below that price.

Wall Street’s models point to revenue near $6.9 billion for the quarter, up sharply from the $4.69 billion SpaceX reported in the first quarter, with a narrower per share loss than the $1.27 posted three months earlier, according to estimates compiled by Motley Fool. Those numbers will be the first look at how SpaceX’s three segments, Starlink, launch and AI, are performing independently.

SpaceX scores another massive Pentagon deal to support military satellites

Investors heading into the call have a specific list of questions. How many net new Starlink subscribers did SpaceX add after ending March with 10.3 million, and is average revenue per user holding up as the service expands into lower income markets. How much of the AI segment’s revenue reflects contract signings with Anthropic, Google and Reflection AI this year, deals that combined could annualize to nearly $28 billion if fully ramped. Whether capital expenditures, which nearly doubled in the AI segment alone between 2024 and 2025, are still accelerating or starting to plateau. And whether management offers any forward guidance at all, something SpaceX has never done publicly.

The report will also land days after Elon Musk publicly denied a Wall Street Journal report describing internal planning to separate Tesla’s China business ahead of a potential Tesla-SpaceX merger. Whether Musk or SpaceX executives address that speculation on the call, even indirectly, maybe something investors will be listening for on Tuesday.

As Teslarati reported after Musk’s own warning to short sellers last week, the CEO has made clear he expects skeptics to be proven wrong over time. Tuesday will be the first chance for the numbers themselves to make that case.

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SpaceX’s Starship just got filmed by its own cargo

SpaceX released new footage of Starship in space captured by the Starlink satellites it deployed.

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SpaceX released a new video Friday evening showing Starship from an angle showcased by its own Starlink satellites, watching the rocket drift away in orbit.

The 65 second clip, posted on X, stitches together footage from four cameras mounted on a single Starlink V3 satellite. It opens with a close view of Starship’s 171 foot upper stage, still catching sunlight, then pulls back as the two spacecraft separate.

The footage comes from Starship’s 13th flight test, which launched July 24 from Starbase after a scrubbed attempt and an abort caused by an engine issue the week before. When Flight 13 finally flew, it carried the first batch of functional Starlink V3 satellites Starship has ever deployed, twenty of them, with six equipped with cameras meant to scan the ship’s heat shield during reentry.

Flight 13 checked most of its boxes. Starship deployed all 20 satellites, relit a Raptor engine in space, and splashed down softly in the Indian Ocean off Western Australia. Musk’s longer term plan calls for a Starlink V3 constellation of 100,000 satellites, according to a recent FCC filing, with Starship as the only vehicle capable of launching them at the volume that requires. Each Starship flight is designed to carry up to 60 V3 satellites once the vehicle reaches routine service, well beyond what Falcon 9 can carry in a single mission.

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Starship is next expected to fly with an attempt at catching the ship itself with the launch tower’s mechanical arms, a maneuver SpaceX has so far reserved for the Super Heavy booster.

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