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It’s hard to lose money selling a $200 a month subscription, but OpenAI is doing exactly that

OpenAI is currently losing money on its newest and most expensive subscription, ChatGPT Pro, because people are using it more than the company expected, Sam Altman said in a post on Sunday.

In a series of posts on X, Altman disclosed that he “personally chose the price” because he thought “we would make some money.” Released on December 5, ChatGPT Pro offers unlimited access to the company’s latest models, including a “full” version of the latest OpenAI o1 model that can be used to “think harder and provide even better answers to the hardest questions.”

Years ago, when asked how OpenAI would make money for its investors, Altman joked — or maybe not joked — that they would “build a generally intelligent system, that basically we will ask it to figure out a way to make an investment return for you.” Clearly, they haven’t got the answer yet.

ChatGPT Pro being a money loser is the latest addition to OpenAI’s list of reasons to raise as much capital as possible. Despite being valued at a staggering $157 billion, the company is far from profitable: OpenAI reportedly expected $3.7 billion in revenue by the end of 2024, but also anticipated spending ~$8.7 billion to achieve that revenue, equating to a ~$5 billion loss.

Partly in an effort to attract investors, OpenAI has plans for a corporate restructuring and is said to be raising its subscription prices in the coming years. That would help the company achieve its lofty $100 billion revenue target by 2029, a mammoth sum which, purely in revenue terms, would be more than what Nvidia managed in its fiscal year 2024 and similar to corporate giants like Disney and PepsiCo.

OpenAI
Sherwood News

Go Deeper: What company’s past reveals the future of OpenAI?

In a series of posts on X, Altman disclosed that he “personally chose the price” because he thought “we would make some money.” Released on December 5, ChatGPT Pro offers unlimited access to the company’s latest models, including a “full” version of the latest OpenAI o1 model that can be used to “think harder and provide even better answers to the hardest questions.”

Years ago, when asked how OpenAI would make money for its investors, Altman joked — or maybe not joked — that they would “build a generally intelligent system, that basically we will ask it to figure out a way to make an investment return for you.” Clearly, they haven’t got the answer yet.

ChatGPT Pro being a money loser is the latest addition to OpenAI’s list of reasons to raise as much capital as possible. Despite being valued at a staggering $157 billion, the company is far from profitable: OpenAI reportedly expected $3.7 billion in revenue by the end of 2024, but also anticipated spending ~$8.7 billion to achieve that revenue, equating to a ~$5 billion loss.

Partly in an effort to attract investors, OpenAI has plans for a corporate restructuring and is said to be raising its subscription prices in the coming years. That would help the company achieve its lofty $100 billion revenue target by 2029, a mammoth sum which, purely in revenue terms, would be more than what Nvidia managed in its fiscal year 2024 and similar to corporate giants like Disney and PepsiCo.

OpenAI
Sherwood News

Go Deeper: What company’s past reveals the future of OpenAI?

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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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