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Cyber_Cat
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AI Spree Rivals Sweden's Economy, Optimizes GPUs 2x Faster

Big Tech's investment in artificial intelligence is surging to unprecedented levels, with companies like Alphabet, Amazon, and Meta collectively planning to spend over $630 billion, according to recent earnings calls. This massive expenditure, primarily focused on scaling AI computing, has raised concerns among investors and signals a significant shift in the tech industry's priorities.

During earnings calls this week, major tech firms revealed substantial increases in their capital expenditure (capex) projections. Alphabet announced plans to double its capex in 2026 to nearly $185 billion, while Amazon intends to devote $200 billion to capex, exceeding Wall Street estimates. Meta also reported that its full-year capex would rise to as much as $135 billion. This surge in spending, coupled with Microsoft's growing projections, underscores the industry's commitment to AI. "We've never invested this much on anything before," a source from Fortune stated.

This concentrated investment in AI marks a departure from previous spending patterns, where funds were distributed across various strategic initiatives. The focus on scaling AI computing reflects the growing importance of the technology across different sectors.

In other AI-related developments, researchers from Stanford, Nvidia, and Together AI have developed a new technique called Test-Time Training to Discover (TTT-Discover). This technique can optimize a critical GPU kernel to run twice as fast as those written by human experts, according to VentureBeat. TTT-Discover allows models to continue training during the inference process, updating their weights for specific problems.

Meanwhile, a social network for AI agents called Moltbook gained rapid popularity. Launched on January 28 by Matt Schlicht, Moltbook quickly went viral, attracting over 1.7 million AI agents that published more than 250,000 posts and left over 8.5 million comments, according to MIT Technology Review.

In the realm of AI infrastructure, the need for efficient and secure execution environments is also being addressed. A minimal, secure Python interpreter written in Rust for use by AI, called Monty, is being developed. According to Hacker News, Monty aims to provide a fast and secure way to run Python code generated by LLMs, with startup times measured in microseconds.

These developments highlight the rapid advancements and growing investment in AI, from hardware optimization to social platforms and secure execution environments. As the industry continues to evolve, the impact of these technologies on various sectors is expected to grow.

AI-Assisted Journalism

This article was generated with AI assistance, synthesizing reporting from multiple credible news sources. Our editorial team reviews AI-generated content for accuracy.

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