PepsiCo Beats Revenue Estimates Despite North America Slowdown

PepsiCo topped Wall Street’s second-quarter revenue expectations on Thursday, helped by resilient demand for zero-sugar sodas in several of its core markets.

Revenue Growth Outpaces Estimates

The beverage and snacks company reported quarterly revenue of $24.18 billion, up 6.4% from a year earlier and ahead of analysts’ estimate of $23.95 billion, according to LSEG. Core earnings per share rose to $2.20 from $2.12 a year earlier.

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Inflation Continues To Weigh On North America

PepsiCo said pressure on household budgets continued to weigh on its North American business. Organic sales in the company’s North America foods division fell about 2% in the quarter as consumers traded down, bought less or shifted to lower-priced alternatives.

The company has responded by lowering prices on brands including Lay’s and Doritos in North America while expanding smaller pack sizes and lower-cost options.

“Results were tempered in the quarter as US food and beverage category performance moderated with consumer budgets tightening due to rising inflationary pressures,” CEO Ramon Laguarta said in prepared remarks.

Full-Year Outlook Unchanged

PepsiCo maintained its fiscal 2026 guidance, continuing to expect organic revenue growth of 2% to 4% and core constant-currency earnings per share growth of 4% to 6%. Shares rose about 1% in premarket trading.

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Mirendil Signs $100 Million Google Cloud Deal To Advance Self-Improving AI

by News Editor

August 6, 2026

AI startup Mirendil has signed a multi-year agreement worth more than $100 million with Google Cloud to secure computing infrastructure for its self-improving AI research.

The partnership reflects growing competition among AI companies to lock in access to high-performance computing, while cloud providers race to attract promising startups developing next-generation AI models.

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Backing The Next Stage Of AI Research

Mirendil plans to use Google’s Tensor Processing Units (TPUs), Nvidia GPUs and managed training infrastructure to develop AI systems capable of improving their own performance over time.

Known as recursive self-improvement, the concept focuses on building AI that can refine its knowledge and capabilities with minimal human intervention. The technology is attracting growing interest across the industry, with several startups and leading AI labs exploring similar approaches.

According to co-founder and Chief Executive Behnam Neyshabur, the long-term goal is to develop AI that can automate scientific research and accelerate discoveries in fields such as medicine, biology and materials science.

Compute Capacity Becomes A Strategic Asset

Training increasingly advanced AI models requires enormous computing resources, making long-term infrastructure agreements a critical competitive advantage.

Mirendil said Google’s combination of TPUs and GPUs allows workloads to be matched with the most suitable hardware, improving efficiency while reducing costs for customers.

For Google Cloud, the agreement strengthens its position in the race to provide infrastructure for frontier AI developers, while giving the company exposure to one of the industry’s emerging approaches to next-generation artificial intelligence.

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