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US ranks 9th in list of countries ready for an AI-enhanced workforce

[Credit: Quartz]

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A new study published by Switzerland-based ABB Group has determined that the United States is lacking in terms of AI and automation readiness, at least when compared to other developed nations. Among a list of 25 countries, the US ranked 9th overall, almost dropping out of the study’s Top 10 list despite being an early adopter of artificial intelligence.

ABB opted to rank the different countries in its study using its Automation Readiness Index, which determines which nations are putting in the effort to ensure that its workforce is prepared for an AI-powered, automated future. The countries that were part of the study were evaluated according to three main categories — innovation environment, school policies, and public workforce development. While the United States scored well in the first category, it lagged in school policies and workforce development. South Korea, Singapore, Germany, Japan and Canada rounded up the Top 5 of the ABB’s rankings.

As noted in a report from The Next Web, a good reason behind the United States’ poor rankings in the ABB study could be due to the country’s outdated school system and its sluggish regulatory environment. So far, America still adopts a rather traditional approach to teaching, emphasizing rote memory and theoretical knowledge at times and hammering the notion that the path towards success is attained exclusively through a college degree.

In contrast, several of the countries in the Automation Readiness Index’s Top 5 — Japan, South Korea, and Singapore, specifically — have all adapted their school curriculum for emerging technologies, teaching in-demand skills and prioritizing STEM since early education. Thus, while American students are still memorizing dates and learning how to type, their counterparts in Japan would already be learning about computer science and dabbling in robotics. Germany is adopting a similar strategy too, allowing students to serve in apprenticeships straight out of high school.

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In a statement to the Los Angeles Times, Susan Lund, a labor economist at global consulting firm McKinsey, noted that with the advent of AI and workplace automation, not everyone needs to have a college degree to thrive.

“Not everyone needs a four-year college degree. We could do a lot to build more career pathways. Even just skill-credentialing to enable people to get a basic, entry-level job,” she said.

As for automation readiness, Lorenzo Fioramonti, professor of political economy at the University of Pretoria in South Africa, noted in a statement that the workforce of tomorrow would have to be adaptable, considering the quick improvements in the AI and automation industry.

“The major difference with the past is that today’s automation technologies are highly intelligent and able to learn,” he said.

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While AI is used for technologies like weapons and surveillance systems, artificial intelligence and machine learning are already being integrated into everyday life. AR filters in social media, automatic translators in Google, and captioning algorithms in YouTube, for example, all utilize AI and machine learning. Unfortunately for the United States, it appears like it would be a while before it starts producing workers that are fully trained to thrive in the AI revolution.

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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SpaceX reveals Starship Flight 13 launch date

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SpaceX Starship V3 flight 12
SpaceX Starship V3 flight 12 (Credit: SpaceX)

SpaceX is preparing for the 13th integrated flight test of its Starship system, with a targeted launch as early as Thursday, July 16. The 90-minute launch window opens at 5:45 p.m. CT from Starbase in South Texas.

This comes roughly seven weeks after Flight 12 on May 22, underscoring the company’s accelerating pace in its rapid development campaign. The mission will use the latest Starship and Super Heavy V3 vehicles equipped with Raptor 3 engines. Booster 20 will attempt a controlled boostback burn, followed by a splashdown in the Gulf of Mexico, while Ship 40 will follow a suborbital trajectory.

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Key objectives for Flight 13 will include demonstrating reliable stage separation, engine performance under various conditions, and controlled reentry.

A major milestone for Flight 13 is the first deployment of 20 next-generation Starlink V3 satellites. These satellites feature advanced laser links for inter-satellite communication, deployable solar arrays, and onboard cameras, six of which will capture imagery of Starship’s heat shield during flight.

Several heat shield tiles on Ship 40 will be painted white to serve as imaging targets, while additional experiments test upgraded tiles on aft flaps, modified attachments on the aft skirt, and load-sensing tiles to measure stresses. The upper stage will also attempt a single Raptor engine relight in space before a targeted splashdown in the Indian Ocean.

These tests build directly on lessons from Flight 12, which introduced the V3 configuration but encountered issues including a booster flip anomaly during boostback and an engine-out event on the ship. Hardware and software modifications on Booster 20 and Ship 40 aim to improve engine relight reliability, startup sequencing, and overall robustness.

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The short interval between Flights 12 and 13 highlights SpaceX’s iterative approach. Elon Musk has repeatedly emphasized that Starship launches will become “incredibly common” in the coming years.

The company envisions scaling to rates as high as one launch per hour within 4-5 years, potentially enabling thousands of flights annually. Such cadence is essential for Starship’s goals: establishing orbital refueling for lunar and Mars missions, deploying massive satellite constellations, and making life multiplanetary.

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With each flight, Starship edges closer to full reusability and operational maturity. Success on July 16 would mark another step toward routine access to space and the ambitious vision of humanity becoming a spacefaring civilization.

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

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Credit: Tesla

Tesla shared a striking video showcasing the decommissioning of the original Model S and Model X assembly line at its Fremont Factory in Northern California. Completed in just 46 days, the teardown involved heavy machinery dismantling concrete pits, removing robotic arms and conveyors, and clearing the space for new production.

The post, captioned “End of an era,” captured both the end of a historic chapter and Tesla’s aggressive pivot toward its next major initiative, Optimus.

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The decision to retire the Model S and Model X originated during Tesla’s Q4 2025 Earnings Call in late January 2026. CEO Elon Musk announced that production of the company’s flagship sedan and SUV would wind down by the end of Q2 2026, describing it as bringing the programs to an “honorable discharge.”

Custom orders ceased around early April 2026, with the final vehicles rolling off the line in early May. A special signature delivery ceremony on May 20 marked the emotional close for these vehicles, which had defined Tesla’s early success and luxury EV segment since the Model S launch in 2012.

The primary reason for tearing down the lines was to repurpose the valuable factory floor space for high-volume production of Tesla’s Optimus humanoid robot. Musk had indicated on Earnings Calls that the Fremont S/X line would be replaced by a dedicated Optimus manufacturing line targeting a capacity of one million units per year.

Elon Musk outlines Tesla Optimus production expectations

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This move aligns with Tesla’s broader strategic shift from traditional vehicle manufacturing toward robotics and artificial intelligence, leveraging the company’s expertise in autonomy, AI training, and high-volume production.

Optimus, Tesla’s general-purpose humanoid robot, is designed to perform repetitive or dangerous tasks in factories, warehouses, and eventually homes. Powered by Tesla’s AI and Neural Networks, it aims to be a versatile, affordable platform. Production of Optimus Gen 3 is already underway in limited form at Fremont, with full-scale output on the converted line expected to begin in late July or August.

Tesla is targeting rapid scaling, with internal ambitions pointing toward tens or even hundreds of thousands of units annually by the end of 2026.

Longer-term, Tesla is constructing a much larger second-generation Optimus facility at Giga Texas, with potential capacity reaching millions of units per year. The company views Optimus as a transformative product that could eventually surpass its automotive business in scale and value, enabling widespread deployment of useful robots across industries. CEO Elon Musk has even predicted it would be the most popular product of all-time.

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As one era closes at Fremont, another is rapidly taking shape.

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Elon Musk admits he was ‘clearly wrong’ about Anthropic

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Ministério Das Comunicações, CC BY 2.0 , via Wikimedia Commons

Elon Musk posted a candid admission on his social media platform X on June 9, declaring that he had been “clearly wrong” about Anthropic. The statement marked a notable reversal from his earlier skepticism toward the AI company.

In September, Musk had written, “Winning was never in the set of possible outcomes for Anthropic,” reflecting his view at the time that the startup had lacked the foundation or even the trajectory to succeed in what is an incredibly intense race for advanced artificial intelligence.

Musk’s latest post came amid discussion of Anthropic’s reliance on external compute resources. He praised the company’s progress, stating that Anthropic is “obviously currently the leader in AI” and that “no company has released a model as good as Mythos/Fable,” with expectations of a strong follow-up in Mythos 2.

The tone shifted dramatically from dismissal to acknowledgement of superior performance.

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The context of Musk’s comments added significance. Anthropic has been operating under a recent compute deal with SpaceXAI, Musk’s AI infrastructure-focused venture. The pair entered a short-term GPU lease agreement initiated in May, providing Anthropic access to critical computing power for training and deploying its frontier models.

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SpaceXAI signs agreement with Anthropic for massive AI supercomputer access

Some observers had speculated that Musk could leverage this dependency to disadvantage a rival. Musk directly addressed the possibility, writing, “I would never cut them off in a way that hurt them badly, even as a competitor. That’s not my style.”

To support his commitment to ethical competition, Musk referenced concrete examples from his other companies. Tesla famously open-sourced its entire portfolio of electric vehicle patents in 2014. The move was designed to accelerate the global adoption of sustainable transportation technology rather than protect proprietary advantages.

Tesla also made its Supercharger network available to competing electric vehicle manufacturers, transforming what could have remained an exclusive charging ecosystem into a shared infrastructure that benefits the broader industry and reduces barriers for EV adoption.

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Musk further pointed to SpaceX’s practices, noting that the company launches satellites for competing commercial systems “with no increase in price or use of unfair terms.” He extended the principle to his social platform, observing that “even my worst enemies attack me on this platform,” underscoring preference for open discourse over retaliation.

These examples have illustrated Musk’s long-standing philosophy that long-term technological progress is best served by open competition and infrastructure sharing rather than leveraging market power to stifle rivals. In the fast-evolving AI sector, where compute resources and model capabilities determine leadership, Musk’s stance suggests a willingness to compete on innovation and performance alone.

Musk’s admission arrives as SpaceXAI itself advances its own frontier models while maintaining business relationships across the ecosystem. By publicly correcting his earlier assessment and reaffirming principles of fair play, Musk highlights a model of competition that prioritizes advancement of the field over short-term tactical advantages.

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