This Week in AI: OpenAI projects $44B losses; Meta AI expands

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A recent report from The Information took a look at OpenAI’s financial projections, revealing that the company isn’t expected to be profitable until 2029 when it’s expected to generate $100 billion in revenue. Until then, OpenAI anticipates steep losses year over year, cumulatively amounting to $44 billion between 2023 and 2028, with an anticipated peak loss of $14 billion in 2026.

The company’s most significant expense is computing power—the infrastructure required to train and run its artificial intelligence (AI) models. Spending in this area alone is projected to reach $9.5 billion annually by 2026; these costs can be divided into high-performance computing resources (computer chips), energy consumption (electricity), data storage and continuous algorithm development.

The report also says that OpenAI allegedly presents investors with an alternative projection showing that the company is profitable in 2026 when you strip out expenses like the cost of training its models.

While it’s definitely a positive sign that analysts see profitability in OpenAI’s future—especially amid widespread concerns about when leaders in the AI space would begin turning a profit—it also raises the critical question: Will OpenAI make it to 2029 without significant financial restructuring? It is no secret that the company has a substantial cash burn, and this new report underscores the scale of its expenditures.

Even though OpenAI recently raised over $6 billion at a $157 billion valuation, that’s a fraction of the projected $44 billion it has to spend before reaching profitability. Unless the company alters its business model, discovers innovative ways to reduce operational costs, or secures additional funding, OpenAI will likely need to raise capital at least once more before turning a profit in five years.

John Hopfield and Geoffrey Hinton win Nobel Prize

Two scientists, John Hopfield and Geoffrey Hinton, have been awarded the Nobel Prize in Physics for their contributions to machine learning.

Hopfield developed a neural network capable of storing and reconstructing patterns, offering insights into how the human brain recalls memories when provided with partial information; his work modeled associative memory, bridging the gap between neuroscience and computational models.

Years later, Hinton created the Boltzmann machine, a type of neural network that uses random decision-making to learn internal data representations; this innovation enhanced the network’s ability to recognize complex patterns and improve future decision-making. Hinton, who left his research role at Google (NASDAQ: GOOGL) in 2023 due to concerns about AI’s potential risks to humanity, has been a vocal advocate for ethical considerations in AI development.

This year’s physics laureates’ breakthroughs stand on the foundations of physical science. They have showed a completely new way for us to use computers to aid and to guide us to tackle many of the
challenges our society face.

Thanks to their work humanity now has a new item in… pic.twitter.com/0sGCbEoMsS

— The Nobel Prize (@NobelPrize) October 8, 2024

Although computer-driven, both networks used and were inspired by physics and physics problems. Hopfield says that he did not imagine the work would be useful in machine learning but acknowledges that there are natural crossovers between biology, physics and AI.

The fact that the Royal Swedish Academy of Sciences—the entity that awards the Nobel Prize in Physics—decided to tie this year’s prize to machine learning and AI reflects the current climate of innovation and shows that there is still a lot of global attention on artificial intelligence. Although consumer-facing AI technologies like chatbots have dominated recent headlines, scientific advances in AI often have a more profound impact on the world.

Meta AI expands to 6 new countries

Meta (NASDAQ: META) has announced that it will launch Meta AI in six new countries: the Philippines, Bolivia, Guatemala, Paraguay, the United Kingdom and Brazil—the two nations where it previously suspended AI operations due to data and privacy concerns.

Users in these countries will now have access to Meta AI through Facebook, Instagram, WhatsApp, Messenger apps, the Meta.ai website and the Ray-Ban Meta Glasses. Meta AI is an assistant that handles text and voice queries and analyzes images, effectively offering functionalities similar to those of other advanced AI chatbots on the market.

Previously, Meta faced significant obstacles in launching its AI services in the U.K. and Brazil due to concerns from each country’s data privacy watchdog. However, the company has found a data privacy loophole by asserting that Meta AI constitutes a “legitimate interest” in business operations. This allows Meta to justify its use of consumer data without their consent because they claim it is necessary for fulfilling its business objectives; in particular, Meta claims this data will help its AI better reflect the diversity of the population, which is crucial to its commercial operations.

For a while, I was unsure how companies like Meta would proceed in data privacy-focused countries like the U.K.. I wondered if the regulations would be considered too prohibitive and that AI service providers would opt out of operating there altogether for that reason. However, with Meta finding a way to resume operations in both the U.K. and Brazil—countries where they previously halted services due to privacy issues—it’s clear that companies will find workarounds or compromises to maintain their global presence. They’d be leaving too much revenue and, most importantly for large language models, invaluable training data on the table if they chose not to operate worldwide.

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Watch: Demonstrating the potential of blockchain’s fusion with AI