
OpenAI has announced a massive $750 billion investment in infrastructure by 2030, a 25% increase from previous estimates. The centerpiece of this investment is Project Camellia, a $20 billion data center in Georgia that will cover 1,400 acres and require significant power from Georgia Power. While the exact energy sources for the project are not yet disclosed, regulatory filings suggest a mix of natural gas and renewable energy. This investment reflects OpenAI's commitment to expanding its data processing capabilities, despite facing challenges with its Stargate project.
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OpenAI Launches Project Camellia in Georgia
2 developments
© TechCrunch AIMeta’s consumer agent Muse is rolling out voice calling to US businesses for paid subscribers, targeting the tedious task of customer service navigation. With over 10 million users, Meta is betting that AI’s infinite patience will replace human frustration with phone trees and hold times. The feature leverages improved voice mimicry to interact with receptionists, though many still hang up upon detecting non-human voices. This moves Muse from text-based assistance into active, autonomous execution of real-world tasks, marking a significant step toward mainstream consumer AI utility.
© TechCrunch AINebius is facing the harsh reality of scaling AI infrastructure: even with $40 billion in planned spending and massive prepayments from Microsoft and Meta, physical construction delays are derailing timelines. A key New Jersey site is months behind schedule due to regulatory fines and generator issues, forcing a shift in delivery dates to 2027. This isn't just a logistical hiccup; it signals that the 'neocloud' model of financing builds with customer cash is fragile when third-party operators fail. The market reacted swiftly, dropping shares by 17% after Nebius cut its 2026 revenue forecast, proving that hype cannot override concrete capacity.
© TechCrunch AIGoogle is quietly shifting its search infrastructure by replacing older fast models with Gemini 4 Hydrogen, a tier designed specifically for speed and cost-efficiency rather than raw reasoning power. This model completes tasks 2.5 times faster than its predecessor while beating the more powerful Argon on specific intelligence benchmarks, proving that specialized efficiency can outperform brute force in high-volume workflows. By integrating this into Search's fan-out technique, Google now breaks down complex queries into subqueries with greater precision and speed, delivering richer visual responses without the latency of heavier models. This marks a strategic pivot toward agentic execution layers within consumer search, making AI Mode feel snappier for everyday multi-part questions.
© MIT Technology Review AINvidia has privately assured lawmakers that it can technically implement geotracking for its AI chips, contradicting public industry claims that such measures are infeasible. This admission comes amid a smuggling scandal involving Jensen Huang and Megaspeed, pushing the US government toward mandatory location verification via the Chip Security Act. While current tools like Fleet Intelligence already monitor data center locations, this private confirmation suggests Nvidia possesses the underlying capability to enforce stricter export controls if mandated.
© The Verge AIThe GDC survey reveals a quiet but decisive shift in game development workflows. Forty percent of developers now use generative AI as part of their job, up from 36 percent last year. The adoption is heavily skewed toward free-to-play and mobile studios, where usage hits 58 and 70 percent respectively. While concept art remains niche at 22 percent, code generation and debugging have become standard tools for over half the industry. This data confirms AI has moved from experimental novelty to essential infrastructure in modern game production.
© The AI Daily BriefAnthropic's initial public offering is days away, with analysts debating the company's valuation amidst shifting market chatter and significant compute commitments.