
Google has unveiled a new feature in its AI Studio that allows users to build Android apps in minutes, significantly reducing the time and complexity traditionally involved in app development. Announced at Google I/O 2026, this tool uses AI to enable both experienced developers and novices to create apps using Kotlin and Jetpack Compose. While the apps are currently for personal use, Google plans to expand capabilities for broader sharing. This move could democratize app development and enhance app discovery through AI-driven recommendations.
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Google AI Studio Enables Quick Android App Creation
4 developments
© TechCrunch AIxAI's attempt to dismiss the NAACP's Clean Air Act lawsuit failed after a federal judge ruled that its gas turbines are not exempt mobile sources and that plaintiffs have standing. This legal setback confirms that AI infrastructure operators cannot bypass environmental permitting by classifying heavy industrial equipment as temporary or mobile. The ruling forces xAI to face scrutiny over air quality impacts at its Colossus data center, setting a precedent for how large-scale compute facilities are regulated under existing environmental laws.
© TechCrunch AIOpenAI is scaling back its ambitions as investor appetite for massive AI infrastructure bets cools. The company has lowered its fundraising target from $30 billion to $20 billion, with only $11 billion secured so far against a valuation that has dropped from $1.4 trillion. This retreat signals a growing wariness among Wall Street investors regarding the capital intensity of the AI race, forcing even the most dominant players to adjust their financial expectations.
© TechCrunch AINvidia is considering a residual value guarantee for Nscale’s $44.6 billion Anthropic data center in West Virginia, effectively co-signing the construction debt to keep the project alive. This move signals deepening financial entanglement between chipmakers and neocloud providers as investors grow jittery about massive capital expenditures. With Nscale struggling to deploy chips and facing local opposition, Nvidia’s backing aims to secure a major customer for its next-gen Vera Rubin hardware while mitigating risk for lenders. It marks a significant escalation in Nvidia’s financial involvement with neocloud providers beyond standard chip purchases. The arrangement would see Nvidia step in if Nscale defaults on construction payments, helping secure financing for the facility that will house Anthropic’s infrastructure using Nvidia’s Vera Rubin chips. Nscale, which is seeking a $35 billion IPO, has faced delays and local opposition, while Anthropic recently filed for its own public offering amid concerns over future credit ratings. This potential guarantee underscores the industry's reliance on chipmaker balance sheets to sustain multi-billion dollar infrastructure buildouts.
Anthropic is tightening control over Claude Code's autonomous behavior with new environment variables that let you disable 'ultrathink' or cap subagent effort levels. For teams, the introduction of pooled group budgets on the gateway allows shared monthly spending limits across members, a practical fix for enterprise cost management. The release also patches critical bugs where shell commands would hang or crash on exit, stabilizing the developer experience significantly.
This release quietly cements llama.cpp as the universal inference runtime by finally bringing ROCm 10.0 to Linux and Windows alongside CUDA 13.4, effectively closing the hardware gap for AMD users who were previously left behind. The inclusion of native Snapdragon support on Linux marks a significant step toward running local LLMs on ARM-based mobile chips without emulation overhead. While KleidiAI on Apple Silicon is disabled in this build, the broader expansion to diverse accelerators ensures that developers aren't locked into NVIDIA ecosystems anymore.
This release addresses a specific inference artifact where decision prefixes were incorrectly bleeding into output embeddings. By capping shared prefixes at the first output position, llama.cpp ensures that option tokens remain distinct for parent and child tasks. This is a targeted fix for multi-step reasoning or voting workflows rather than a performance boost. It stabilizes complex generation patterns without changing the underlying model architecture.