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US overtakes Chinese supercomputer to take top spot for fastest in the world

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After a semi-annual assessment measuring supercomputer computational speeds, US-built IBM machine “Summit” has toppled two Chinese competitors to take the lead as the fastest of its kind in the world. China’s Tianhe-2 and Sunway TaihuLight spent the last two years at the top of the SuperComputer TOP500 List, but this month Summit pulled ahead of both with a performance of 143.5 quadrillion operations per second, making it 65% more powerful than the next non-US supercomputer on the list. Out of the top ten machines ranked, five are in the United States.

The TOP500 project was established in 1993 to track and rank meaningful statistics for organizations to use in determining their needs with regard to high-performance computing (HPC). The benchmark test used to determine the rankings is called “Linpack”, which requires HPC systems to solve a specific set of linear equations using floating point arithmetic. To help quantify just how powerful the machines in the HPC category are, Summit is 1 million times more powerful than the fastest laptop with 250 petabytes of storage capacity.

Located at the Oak Ridge Leadership Computing Facility (OCLF) in Tennessee, the Summit supercomputer has an architecture purpose-built and optimized by IBM for artificial intelligence. While specialized, access to its technology isn’t exclusive to the machine’s developers. All components are available to any enterprise as part of IBM’s product line.

The top 5 supercomputers in the world. | Credit: TOP500

Summit was funded with part of a $258 million grant from the U.S. Department of Energy to help maintain US leadership in national security, manufacturing, industrial competitiveness, and energy and earth sciences. Summit’s “sister” computer, Sierra, was developed as part of the same Department of Energy commission and takes second place in the TOP500 list. This machine is located at Lawrence Livermore National Laboratory (LLNL) in California, and it boasts a computing speed of just under 95 quadrillion operations per second.

The HPC field overall provides computing power for advanced artificial intelligence along with massive data projects in business, medicine, science, and engineering. A recent competition hosted by the Association for Computing Machinery to recognize achievements in HPC, the Gordon Bell Prize, named five finalists that used Summit for advanced science research. The projects included, among others, an algorithm looking for genetic variations linked to complex traits and conditions such as opioid addiction, an AI simulation of earthquake physics in urban environments, and a deep neural network to identify extreme weather patterns from climate simulations. The winner of the competition will be named later this week at the 2018 International Conference for High Performance Computing, Networking, Storage, and Analysis in Dallas.

Watch the video below for more about Summit’s supercomputer capabilities.

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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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Elon Musk

Tesla Semi finally has an FSD timeline and it’s waiting on the Cybercab

Elon Musk told investors Semi self-driving should start working by early 2027, per today’s earnings.

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During Wednesday’s’ Tesla Q2 earnings call, an analyst asked Elon Musk when Tesla would look at autonomy for the Semi. His answer set a real timeline for the first time, noting that self-driving on the Tesla Semi is expected to start working “around the end of this year or early next year”.

Musk framed the delay as a matter of priority, not capability. Tesla’s self-driving team is currently focused on Model 3, Model Y, and Cybercab, the vehicles that make up the overwhelming majority of Tesla’s fleet. Since Semi trucks on the road remain a small fraction of that total even after the recent Nevada factory ramp, Musk said it made more sense to keep the software team’s attention on what he called “the march of nines of safety” for the higher volume vehicles first. Autonomous Semi development is “taking a bit of a backseat for the next six months or so,” he said, before adding that it “will definitely be working next year and in time for the scale-up to high production of the Tesla Semi.”

Tesla Semi’s official battery capacity leaked by California regulators

The timeline lines up with what’s already been showing up on public roads. In June, a Tesla Semi was spotted in Sunnyvale wearing a full validation rig, the same rooftop sensor array Tesla mounts on vehicles ahead of an FSD milestone.

A second unit was seen near Fremont days later with a matching camera suite and lens washers. Separately, Tesla analyst Nic Cruz Patane posted video this month of the production Semi’s exterior camera array, ten AI4 based units built directly into the truck rather than added later.

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Musk also gave the reason autonomy on the Semi matters in the first place, a persistent shortage of qualified truck drivers. “There is a really serious shortage of truckers,” he said on the call, framing a self-driving Semi as important both for addressing that shortage and for improving safety and comfort for the drivers running the truck today.

The timing also tracks with the Semi’s production reality. Tesla’s Q2 shareholder letter, dropped language promising the Semi would reach volume production this year. Musk pointed to 4680 battery cell output as the near-term constraint on Semi and Cybercab production. A software timeline landing in early 2027 gives Tesla’s autonomy team room to work while the hardware ramp catches up behind it.

It’s worth nothing that this isn’t necessarily a promise the Semi ships driverless next year. Musk’s own language, self-driving “working” by early 2027, describes internal validation catching up to hardware already riding on every production truck, not a public unsupervised rollout.

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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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Elon Musk

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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