
Hugging Face has launched a billing integration with Google Cloud Marketplace, allowing organizations to pay for Hub services via their existing GCP invoices. The feature supports Team and Enterprise subscriptions, as well as pay-as-you-go compute resources like Jobs, Inference Endpoints, and GPU Spaces. Admins can link their Hugging Face organization to a Google Cloud project through the Marketplace, with usage metered and reported directly to the GCP billing account. This move simplifies procurement for enterprises already using Google Cloud, removing the need for separate vendor onboarding.
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© Hugging Face BlogIBM is tackling the brittleness of small language models by introducing LLMON, a structured markup language that explicitly separates instructions from data. By using reserved special tokens instead of ambiguous characters like JSON brackets, these new Granite 4.1 preview models drastically reduce indirect prompt injection attacks while maintaining standard performance. This approach forces the model to bind specific constraints to specific data payloads, eliminating the confusion that often leads to hallucinations or security breaches in long contexts.
Hugging Face finally provides a concrete path to adapt the powerful TRELLIS.2 model for specific domains like footwear or furniture, solving the 'generalist' problem in 3D generation. By targeting only the structure and shape DiTs with LoRA adapters while freezing the texture flow, they prevent catastrophic forgetting of material priors—a common pitfall when fine-tuning large generative models. This approach allows practitioners to achieve high geometric accuracy on small datasets (188 samples) without retraining the entire pipeline. It transforms TRELLIS.2 from a demo toy into a usable tool for production-grade 3D asset creation.
© Hugging Face BlogTether AI Research has released BotPsy, an 0.8B-parameter model built on Qwen3.5 that specializes in tool-use and agentic workflows for on-device deployment. It achieves state-of-the-art performance in its size class, outperforming larger models like Qwen3.5-2B-Think on benchmarks such as BFCL v4 and ACEBench while maintaining strict privacy by keeping data local. The model is designed to handle routine tasks like calendar management and web search without relying on expensive cloud APIs, offering a viable path for private, self-hosted personal assistants. With open weights under Apache 2.0 and GGUF support, it provides immediate utility for developers building lightweight, autonomous agents.
© 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.
© 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.
© TechCrunch AIUnited Airlines is actively blocking third-party AI agents from accessing its booking systems, marking a significant shift in how legacy infrastructure handles autonomous software. The airline cites cybersecurity risks from shared credentials and potential violations of federal aviation rules requiring human check-ins. This move aligns with similar warnings from major banks like Bank of America, signaling that critical industries are drawing hard lines around where human oversight is legally required. It effectively kills the dream of fully autonomous travel booking for now, forcing a re-evaluation of agent integration in regulated sectors.