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Xiaomi shares closed down 5.5% on news of a fatal car crash involving one of its “smart-driving” EVs

Shares in Xiaomi dropped on Tuesday after a statement on Weibo from the Chinese tech giant, which also makes smartphones and other consumer electronics, confirmed that the SU7 electric vehicle’s advanced driver assistance mode was enabled before a crash on Saturday night. Per local media reports, three people lost their lives.

News of the fatalities comes just one week after Xiaomi confirmed that it had raised $5.5 billion from share sales, with an eye to expand its burgeoning EV division. BYD, one of Xiaomi’s biggest rivals in the space, had raised $5.6 billion in its own bumper share offering only weeks earlier.

Though the company warns customers to remain vigilant when deploying the tech, with reminders that its “smart-driving” assistance system does not mean “self-driving,” the crash on an eastern Chinese highway is just another example to point to for skeptics of smart and autonomous vehicles. Tesla’s “full self-driving” system, for example, came under scrutiny from the National Highway Traffic Safety Administration in October last year after a spate of crashes — including one fatal accident involving a pedestrian — reported across its autonomous fleet.

News of the fatalities comes just one week after Xiaomi confirmed that it had raised $5.5 billion from share sales, with an eye to expand its burgeoning EV division. BYD, one of Xiaomi’s biggest rivals in the space, had raised $5.6 billion in its own bumper share offering only weeks earlier.

Though the company warns customers to remain vigilant when deploying the tech, with reminders that its “smart-driving” assistance system does not mean “self-driving,” the crash on an eastern Chinese highway is just another example to point to for skeptics of smart and autonomous vehicles. Tesla’s “full self-driving” system, for example, came under scrutiny from the National Highway Traffic Safety Administration in October last year after a spate of crashes — including one fatal accident involving a pedestrian — reported across its autonomous fleet.

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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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