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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 v14.3.6 review: a rare regression, but some bright spots

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Credit: Tesla

Tesla released Full Self-Driving version 14.3.6 last week, and after what was potentially one of the best FSD releases in v14.3.5, there has been a bit of a regression. While there are some bright spots, the changes made to v14.3.6 seem to have backtracked some behaviors.

Overall, it is hard to really complain about FSD in any sense; it has revolutionized how I travel literally anywhere. According to my self-driving app, the last time I went a day without using it was 59 days ago.

However, I think it’s also important to recognize when things are just plain bad with FSD. There are times it does truly mind-boggling things, and I’ll dive into those here. Additionally, I only had these issues on local roads, not on highways. Highway operation, generally, is always incredible other than the occasional complaint about speed or left lane camping.

With those things being said, my personal experience may not represent others’ experiences. A handful of people have said they have had a similar experience on v14.3.6, while others have said it is more than normal.

Turning Hesitancy, Inaccuracy

I’ve noticed more inaccuracy turning into multi-lane stretches of road than in any version I can remember. I’ve had at least three instances of FSD turning into a stretch of roadway that has two or more lanes, and not selecting a lane confidently as it has in past versions.

Instead, the car will drive over one of the dashed road lines, and the steering wheel will jerk back and forth before picking the lane. It should be said that it has always picked the correct lane when choosing based on the navigation, but it is still very indecisive. The steering wheel jerking is reminiscent of some of the later versions of v13.

I admit I really hate to see the steering wheel jerking come back. However, I think when Tesla releases v14.3.7, it won’t be present. When there are occurrences of it in FSD versions, it is usually resolved by the following release.

FSD Disregards Manual Turn Signals

This is my biggest bone to pick with FSD other than Navigation issues, but this one seems like it would be such an easy fix.

If Tesla is going to put the word “Supervised” on the end of “Full Self-Driving,” then when I tell the car to do something, it should do it. If I input an increase in speed by pressing the accelerator, the car will immediately respond. It does not disregard my input because it feels it is traveling at the right speed.

FSD should never disobey and turn off turn signals that the driver inputs. Trying to direct the car into the correct lane, I had initiated the left turn signal not once, not twice, but three times, with the car turning it off all three times and continuing in a lane that would end in just one block. The only solution at this point would be to zipper merge.

This goes back to the fact that self-driving’s biggest bottleneck might be rider preference. A zipper merge might have been more than reasonable, might have saved me time that I spent sitting through an additional light cycle, and might be something many drivers would do. I was in no hurry, I traditionally do not try to zipper merge because it feels inconsiderate, and lastly, the car should have just followed my input.

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This caused me to disengage and drive manually the rest of the way home. Sometimes I just do not need FSD to try to pass every car it can at intersections.

Bird Braking is a Thing of the Past

The big complaint with recent versions of Full Self-Driving has been what we’ve coined as “bird braking,” which is when the car will brake suddenly as a bird flies past.

There have been zero issues with this so far in v14.3.6, which is an excellent improvement.

FSD Might Already Be Taking Note of Driver Preferences

Another thing I have noticed over the past few days is that v14.3.6 seems to already be taking my preferences with navigation into account.

This is something that is supposed to be rolling out with the Summer Update, but I have a hunch it’s already present and might have been included in this v14.3.6 build. On Friday, FSD pulled into an entrance to a local convenience store that it had never attempted to go into before.

Typically, I manually pull into this entrance because it avoids heavy cross traffic at the main entrance. FSD has always chosen that congested main entrance.

Additionally, FSD has pulled into my assigned parking spot at my townhouse community on multiple occasions with this release. This is something that used to happen ocassionally, but not consistently.

It also navigated back to the same convenience store last night, drove through crazy cars scrambling to gas pumps, navigated out of the parking lot correctly, drove me home, and, once again, parked in my assigned spot.

As previously stated, this release just seems to have a few things that need to be brought to Tesla’s attention, and also to make others who use FSD aware of some things that I’ve experienced. I look forward to the next release that will remedy these issues, just as Tesla has always done in the past.

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Musk’s massive Terafab project will get final location soon

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Credit: SpaceX

Elon Musk’s massive Terafab project, which will be the first true conglomeration between each of his major entities, is set to get its final location soon, the CEO said on Tesla’s recent earnings call.

“The Terafab, we expect to announce a location soon, and provide more details about our plans in that regard. We’ll leave that to the product, the launch announcement rather than try to squeeze it into an earnings call,” Musk said last Wednesday.

Tesla Terafab set for launch: Inside the $20B AI chip factory that will reshape the auto industry

Terafab was announced by Musk back in March and was essentially a massive, vertically integrated semiconductor manufacturing project that would provide all the chips the three companies needed for their AI initiatives without needing third-party companies.

The plant will produce over 1 terawatt of AI compute each year, and will help back up projects like Optimus, Full Self-Driving, and other AI-based projects that Musk’s companies are working on.

In April, less than a month after the project was launched, Intel announced it would join the project, contributing manufacturing expertise and consulting to Terafab as a whole. Intel is one of three chip manufacturers that produce sub-5 nanometer chips at scale. TSMC and Samsung are the other two.

However, there was no true indication of where Terafab would end up, but most believe it will likely be somewhere in Texas. Business Insider has reported that SpaceX plans to build out Terafab in Grimes County, Texas, but this is unconfirmed.

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Musk confirmed recently that it would not be on Giga Texas property, as it is simply too large.

Terafab holds much of Musk’s grand ambitions for the future within its construct. It holds so much responsibility for the future and the biggest projects that Musk’s companies can imagine.

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“I think this is a very big announcement and it deserves to have its own day in the spotlight and not be squeezed into an earnings call,” he said. “I do think Terafab is going to be an amazing initiative and a necessary one, and one without which we will be constrained in our ability to scale Optimus production, because we simply won’t have enough AI chips.”

He continued by stating that Terafab is necessary for scaling Optimus, which Musk said could be the biggest product of any kind of all time. “It’s crucial to solve that, and we’ll have to solve memory, logic, and packaging in order to scale Optimus.”

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Elon Musk reveals SpaceX performed secret Starship test on Flight 13

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Credit: SpaceX

SpaceX performed a secret test on a specific portion of Starship with its recent 13th test flight last week, CEO Elon Musk revealed.

Starship’s 13th test flight took place last Friday, and in many aspects, it was one of the most overwhelmingly successful launches in the project’s history.

All of the mission objectives were met without incident, both the Super Heavy Booster and Ship managed to perform safe splashdowns in the Gulf of America and the Indian Ocean, respectively, and the deployment of Starlink satellites came and went without any complications.

However, there was more on the agenda for SpaceX with Flight 13. Musk revealed an internal test of the ship’s heat shield tiles, as the space exploration company wanted to push them to the limits after previous issues.

Many noticed that Starship’s initial launch seemed to be more accelerated than normal, and that was not a mistake. Musk revealed that SpaceX decided to give Flight 13 an intentionally aggressive acceleration rate in an effort to test how well the tiles would remain attached to the ship:

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SpaceX had issues with some of the heat shield tiles remaining attached early on in the Starship program. The first six test flights presented some kind of anomaly with them, so the company’s big focus with them was to figure out a way to keep them intact through the duration of the flight.

Things truly improved as Flight 10 showed that ceramic tiles generally stayed attached to the ship far better due to refined attachment, as SpaceX utilized pins instead of adhesives. Flights 10 through 13 truly showed some clear progress with the heat shield tiles, and this latest test seems to be where some real progress was noticed, especially by Musk.

The 13th Starship launch last Friday was the second with Starship V3, SpaceX’s latest and greatest iteration of the spacecraft. Goals and ambitions are getting even grander as the project continues to progress. Musk has already hinted that SpaceX will likely try to catch Starship with Flight 14.

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