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Tesla Semi
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What we know about Tesla’s Semi truck as production nears

Musk says “high-volume production” will start this year. Wall Street thinks that’s more like 5,000 to 15,000 trucks.

Rani Molla

Tesla’s long-awaited Semi trucks are back in the spotlight. The Wall Street Journal reports that truck drivers testing prototype models are enthusiastic — and the rest of us may not have to wait much longer. The company is expected to begin producing and shipping the electric freight trucks, which feature driver-assistance technology, from its northern Nevada factory this summer.

Here’s what we know:

How many

CEO Elon Musk said last month that the Semi would enter “high-volume production this year.” The Journal, citing Tigress Financial Partners, estimates Tesla could produce between 5,000 and 15,000 trucks in 2026, eventually ramping up to 50,000 annually.

That’s a long delay from the truck’s 2017 unveiling, when production was originally slated for 2019.

The Journal also reports that trucking companies have secured $195 million in grants for 1,002 Semis through a California nonprofit that funds zero-emissions trucks. That’s roughly double the number of zero-emissions big rigs currently operating in Southern California.

How much

The Journal, citing people familiar with orders, reports that the trucks cost under $300,000, or about twice as much as a regular diesel truck.

Tesla hasn’t confirmed pricing, but it has consistently argued the Semi will be cheaper to operate per mile. In 2017, Musk said operating costs would be $1.26 per mile versus $1.51 for diesel trucks. More recently, he has framed it more broadly, saying it will be “better than a diesel truck.”

How far

The Semi comes in two versions: one with a 325-mile range and another with a 500-mile range, or about double that of some competing electric big rigs.

Tesla says the battery can charge to 60% in 30 minutes. That’s fast for an EV, but still slower than refueling a diesel truck.

A fully loaded Semi can go from 0 to 60 mph in about 20 seconds. One driver told the Journal he was able to haul a 25,000-pound load up a mountain pass with ease.

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FT: Meta considering “tens of billions” in new capital to fund AI

Just days after Google announced a monster $85 billion upsized equity raise, the extremely profitable Meta is seeking to sell “tens of billions of dollars” in stock, according to a new report from the Financial Times.

Meta is planning on spending between $125 billion and $145 billion on AI capital expenditure this year alone.

Shares dropped more than 5% on the news.

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FT: Anthropic staff helping the NSA use Mythos for offensive cyberattacks

Anthropic’s Mythos AI model was deemed too dangerous to release to the public, with the company citing its ability to orchestrate novel cyberattacks.

And that’s just what the National Security Agency is doing, with the help of Anthropic staff embedded at the agency, according to a report from the Financial Times.

Only a small number of companies and US allies have been given access to the advanced model, which means America’s adversaries have not had the chance to shore up their defenses against the AI model’s new offensive capabilities.

The arrangement is especially unusual as the Pentagon has deemed Anthropic’s AI a national security supply chain risk — effectively blacklisting it for defense work — in response to the company’s refusal to allow its technology to be used for any legal application, which could include autonomous killing or mass surveillance. Anthropic is currently suing the US government to fight the determination.

Only a small number of companies and US allies have been given access to the advanced model, which means America’s adversaries have not had the chance to shore up their defenses against the AI model’s new offensive capabilities.

The arrangement is especially unusual as the Pentagon has deemed Anthropic’s AI a national security supply chain risk — effectively blacklisting it for defense work — in response to the company’s refusal to allow its technology to be used for any legal application, which could include autonomous killing or mass surveillance. Anthropic is currently suing the US government to fight the determination.

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Longtime Tesla bear JPMorgan upgraded Tesla and raised its price target to $475 from $145

For more than a decade, JPMorgan was Wall Streets most stubborn Tesla skeptic, anchored by auto analyst Ryan Brinkman’s strict focus on traditional car fundamentals and near-term delivery numbers.

But JPM recently handed coverage of the stock to a new analyst, Rajat Gupta, who is throwing that playbook out the window. In a note Friday, the firm upgraded Tesla to neutral from underweight and raised its price target 228% to $475 from $145. (The analyst consensus on FactSet is $403.) Instead of focusing on the company’s struggling vehicle business, the new analyst is orienting himself more toward Tesla’s idea of the future, now modeling Tesla’s physical AI and robotaxi fleets all the way out to the year 2040.

Here are the main reasons for the capitulation:

  • Looking past the car lot: Gupta argues that Tesla is at the forefront of physical AI, entering uncharted TAMs” and therefore deserves the benefit of the doubt to be valued on LT earnings potential rather than near-term speed bumps.

  • Unmatched vertical integration: Teslas control over everything from battery cells to custom silicon gives it a massive moat. JPM notes this starting point advantage is unmatched at an industrial level scale” and “still somewhat under-appreciated and misunderstood.

  • The AWS flywheel effect: Deploying Optimus robots inside its own factories should not only lower COGS for the base automotive business, but more importantly, help validate the product at an industrial scale.” Gupta called it “a classic flywheel effect, somewhat analogous to AWS and Kiva at AMZN.

For Tesla bulls who have argued for years that this is an AI company and not a carmaker, JPM’s sudden $3.9 trillion valuation model is the ultimate validation.

skynet terminator

Anthropic ponders self-improving AI

Anthropic says Claude already writes 80% of its code. A new post asks what happens when the models can improve themselves — and whether anyone could stop them.

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