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Chime’s Nasdaq Debut: A 37% Leap in the Fintech Arena

Chime set to debut on Nasdaq

On June 12, 2025, Chime had a groundbreaking debut on Nasdaq, where its shares surged by an impressive 37%. Initially priced above the expected range at $27, the shares closed the day at $37.11, setting a new market cap of $13.5 billion. From a valuation of $25 billion in its last venture round, this IPO marks a recalibration for Chime amidst evolving market dynamics.

The offering raised roughly $700 million, with an additional $165 million from existing shareholders. Despite the lower valuation, CEO Chris Britt highlights Chime’s commitment to serving Americans earning $100,000 or less, often overlooked by traditional banks. “We help our members avoid fees, access liquidity, and build savings,” Britt stated confidently.

Chime’s strong revenue momentum, with $518.7 million reported last quarter and a revenue increase by 32% year-over-year, underscores its growth potential. The company also achieved $25 million in adjusted profitability, improving its profit margin by 40 points over the past two years.

Chime now stands among fintech giants like eToro and Circle, rekindling investor interest in fintech IPOs. The future looks promising as other players like Klarna and Bullish eye public offerings.

For further insights into fintech innovation and investment opportunities, explore European Banking Evolution: Cyprus as a Catalyst for Regulatory Innovation and discover how Cyprus continues to play a pivotal role in financial advancements.

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

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.

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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