By Krystal Hu

Aug 6 (Reuters) - (Artificial Intelligencer is published every Wednesday. Think your friend or colleague should know about us? Forward this newsletter to them. They can also subscribe here.)

One of the most anticipated AI releases of the year is nearly here: OpenAI’s GPT-5.

Early testers told my colleague Anna Tong that they are impressed with GPT-5’s coding and problem-solving abilities. Still, some whisper that the leap from GPT-4 isn’t as jaw-dropping as the monumental jump from GPT-3 to GPT-4.

The stakes for OpenAI are high. A source told me the company is now seeking to let employees sell shares at a staggering $500 billion valuation — up from $300 billion earlier this year — as it races toward $20 billion in annualized revenue by the end of 2025. Whether GPT-5’s new capabilities will become a catalyst for further growth remains to be seen.

GPT-5 is a hybrid: the result of massive pre-trained architecture combined with new reasoning techniques like test-time compute. It’s a test of whether AI’s progress down the reasoning path can keep pace with our sky-high expectations, and whether OpenAI can maintain its edge as the world’s most-watched AI lab.

In this week’s newsletter, we’re exploring the shifting dynamics in one of the biggest AI battlegrounds: the cloud giants. We’ve got fresh insights straight from earnings season, plus a chart that sheds light on how the AI boom is driving up electricity prices and what developers think of OpenAI’s long-awaited open-weight models.

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A TALE OF THREE AI CLOUDS

Generative AI has been the shot of adrenaline the cloud market didn’t know it needed. Three years ago, enterprise spending on cloud infrastructure hovered around $55 billion per quarter. Now we’re staring down $100 billion in Q2 alone — a leap that would have seemed unthinkable in the era of predictable and stable cloud growth.

For years, the cloud story was all about Amazon’s AMZN.O dominance. But recent earnings reports from the major cloud providers show everybody is getting an AI lift, and AWS’ throne isn’t quite as secure as it once was.

The changing dynamics didn’t go unnoticed in the eyes of investors, as Amazon CEO Andy Jassy defended AWS’ standing in the AI arms race at last week’s earnings call when asked about the perception that it was behind in AI. The company reported Q2 sales up 17.5% to $30.9 billion.

Jassy touted Amazon chip Trainium’s cost and performance advantages, especially for inference, and highlighted AWS’ role in serving models from partners like Anthropic. This week, Amazon also became one of the first cloud providers to serve OpenAI’s new open-weight models.

The rapid adoption of AI is benefiting the entire industry, with more businesses seeking access to advanced models and AI tools through cloud platforms.

Among the giants, the market share dynamics are evolving. Back in the second quarter of 2022, AWS commanded 34% of the global enterprise cloud infrastructure market, with Microsoft MSFT.O at 21% and Google Cloud at 10%, according to Synergy Research Group. Fast forward to this year: AWS has slipped to 30%, Microsoft holds steady at 20%, and Google Cloud has inched up to 13%. The top three still account for a combined 63% of the market, but the distribution of power is slowly changing.

This demand has also created opportunities for a new generation of “neocloud” companies like CoreWeave, which specializes in Nvidia GPU-powered infrastructure.

Do cloud giants need their own in-house AI technology to win the race? The jury might be still out for the long term, but Google’s growth already stands out. With a 32% year-on-year jump in revenue to $13.6 billion in the second quarter, driven by its strength in full-stack AI research from Gemini models to TPU chips, Google Cloud is outpacing its larger rivals.

Microsoft’s Intelligent Cloud segment saw revenue grow 26% year-over-year to nearly $30 billion, as the company continues to benefit from its partnership with OpenAI — though questions remain about how its exclusive access to OpenAI’s models will evolve.

All three tech giants are investing in their own models and custom chips to better control costs and infrastructure. Microsoft and Amazon are trying to play catch-up with self-developed tech in a bid to maintain margins, while hanging tight to external partners such as OpenAI and Anthropic.

Fast growth is spurring investment and more data center buildouts, from signing leases to building infrastructure and securing power. Even tech giants long known for self-funding growth are grappling with the soaring cost of AI. Expect cloud companies to get more creative with financing the cost of such investment, perhaps engaging third-party partners in their data center buildouts.

CHART OF THE WEEK

Average U.S. electricity prices in cities have surged sharply in recent years, climbing from $0.14 to $0.19 per kilowatt-hour since 2021. Among many factors, AI data centers and power-hungry chatbots are driving up demand faster than new plants can be built. The increase in power costs is far outpacing overall inflation, highlighting how the AI boom is straining America’s largest power grid and impacting everyday consumers.

WHAT AI RESEARCHERS ARE READING

OpenAI is finally putting the “open” back in its name. Months after China’s DeepSeek made waves with its open-source model, OpenAI has released its new open-weight models, gpt-oss-120b and gpt-oss-20b—marking its biggest open-weight launch since GPT-2.

These models are built for complex reasoning and agent-like tasks, yet they’re efficient enough to run locally on a high-end laptop. OpenAI has said that the goal is to empower individuals and foster innovation, giving developers, researchers, and enthusiasts more control over their AI tools without restrictive licenses.

Within hours of release, the models soared to the top spot on Hugging Face’s trending models—a clear signal of how eagerly the AI community has been waiting for transparent, powerful models they can run and fine-tune themselves.

Still, some early testers are finding that while the models excel at tough reasoning challenges, they sometimes make mistakes on simpler prompts or “hallucinate” answers. This seems to reflect a focus on advanced reasoning, possibly at the expense of everyday versatility.

(Reporting by Krystal Hu; Editing by Rosalba O'Brien)

((rosalba.obrien@thomsonreuters.com; +1-646-988-3014;))