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Apple Faces Uncertainty Over Tariff Costs Amid Mixed Q2 Performance

Apple Inc.’s latest financial report reveals a mixed bag of results. While the Cupertino giant surpassed Wall Street’s earnings expectations for its second fiscal quarter, there are significant concerns about future tariff costs beyond June 2025.

Apple‘s shares dipped by up to 4% during after-hours trading, even as the company reported an EPS of $1.65, beating the $1.63 estimate by LSEG. According to recent reports, even other tech giants like Meta and Microsoft are facing similar market dynamics. Apple’s revenue hit $95.4 billion, surpassing forecasts, with strong iPhone and Mac sales driving this growth.

However, Tim Cook, CEO of Apple, highlighted the ‘limited impact’ of current tariffs due to a robust supply chain. The company is projecting low to mid-single-digit growth for the next quarter, potentially mitigating these concerns by sourcing more from India and Vietnam, regions with lower tariff rates. But uncertainty looms, with Cook admitting, ‘It’s very difficult to predict beyond June because I’m not sure what will happen with tariffs.’

Despite these challenges, Apple authorized up to $100 billion in share repurchases and announced a 4% hike in dividends. While the Services division’s revenue growth slowed somewhat, it still pulled in an impressive $26.65 billion. More details on shifting market landscapes can be found in how China’s trade policies are affecting global markets.

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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