📱 Apple's foldable iPhone faces engineering issues
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📱 Apple's foldable iPhone faces engineering issues
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🏭 Intel joins Elon Musk's $25B Terafab AI chip project
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🤖 Meta to open-source new AI models
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🏆 Meta employees compete on internal AI usage leaderboard
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📱 Apple's foldable iPhone faces engineering issues
Apple’s foldable iPhone has encountered more engineering challenges than anticipated during early test production, which could delay the first customer shipments by several months.
The problems surfaced during production verification testing — the fourth of six required stages a product must clear before mass production — and component suppliers have already been notified of the schedule adjustments.
Apple had been aiming to launch the device in fall 2026 alongside the iPhone 18 series, but the timeline could now slip into 2027, with April and early May expected to be critical for further testing.
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🏭 Intel joins Elon Musk's $25B Terafab AI chip project
Intel has officially joined Elon Musk’s Terafab project, a $20–25 billion semiconductor manufacturing complex planned for Austin, Texas, alongside Tesla, SpaceX, and xAI.
The facility is designed to produce chips at massive scale, targeting an annual compute capacity of 1 terawatt, including edge-inference processors for Tesla’s Full Self-Driving systems and radiation-hardened chips for SpaceX satellites and xAI infrastructure.
Intel CEO Lip-Bu Tan hosted Elon Musk at Intel facilities prior to the announcement, with the company contributing its advanced process technology, high-volume fabrication expertise, and packaging capabilities to the project.
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🤖 Meta to open-source new AI models
Meta plans to release open-source versions of its next-generation AI models, which are derived from two proprietary frontier models internally codenamed Avocado and Mango, both expected to launch later this year.
The open-source editions will not include every feature found in the closed-source models, potentially featuring reduced neural network complexity, smaller parameter counts, or skipping certain post-training steps.
AI safety is reportedly one of the main reasons Meta will withhold select capabilities, and the company does not expect its upcoming models to outperform competitors such as Anthropic and OpenAI across the board.
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🏆 Meta employees compete on internal AI usage leaderboard
Meta maintains an internal leaderboard called “Claudeonomics” that ranks employees based on AI token consumption, tracking usage across more than 85,000 workers on the company intranet.
In a single 30-day period, employees consumed a total of 60 trillion tokens, with the top user averaging 281 billion tokens — though some reportedly leave AI agents running for hours simply to boost their scores.
Despite Silicon Valley’s growing emphasis on “tokenmaxxing” as a productivity metric, there is still no clear evidence that higher token consumption translates into meaningful business results or revenue growth.
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