Dreamscale Labs (YC F26) launched a real-time cloud inference platform for robotics that serves frontier physical AI models over the cloud with ultra-low latency. The listing specifies “YC F26” for the company. Users can run large SOTA models via on-demand cloud inference instead of buying expensive GPUs, and the page frames this as an alternative to on-prem hardware.
Agent37 launched low-cost sandboxes for running AI agents and says they run at under 10% of most sandbox providers’ costs. New customers average $0.37/month per sandbox, and the infrastructure cost for free-tier sandboxes is about $0.05 to $0.10 per user per month. The company is now offering a free plan, with over 90% of new signups using it.
Ray Serve LLM Deep Learning Containers were used on Amazon EKS to deploy a single large language model split across two GPU nodes, with one node handling prefill and the other handling decode behind one OpenAI-compatible endpoint.
NVIDIA announced at the OCP Global Summit a set of open architecture contributions and software components to help standardize AI factory infrastructure across compute, networking, power, and cooling. The update includes MGX 1.2 support for rack deployments up to 250kW. As a result, operators and partners can build and scale AI factories using shared specifications and DSX AI Factory open software instead of relying on proprietary designs.
Microsoft will scale its in-house Maia inference chips across Azure starting in 2027 to reduce reliance on Nvidia. The Maia 300 is scheduled for first production deployments in 2027, with Microsoft seeking capacity for more than 300,000 chips for that year. Microsoft is shifting AI inference for its own products onto Maia 300 hardware and expanding Maia use for model serving while waiting for independent benchmarks.
Apple cut supplier component orders for iPhone 18 Pro and iPhone 18 Pro Max, with Nikkei Asia saying the October orders are at least 15% below what Apple originally requested. The iPhone 18 Pro starts at $1,199 and the iPhone 18 Pro Max at $1,299, each $100 more than the iPhone 17 Pro models they replaced. As memory-chip costs rise due to AI-driven demand, Apple shifts shipments toward premium models and delays the standard iPhone 18 to spring 2027.
Amazon is reportedly in talks to acquire Decart for about $7B, following Anthropic’s exit from a roughly $6B deal in September after due diligence. The proposed price is about 75% above Decart’s nearly $4B valuation in May. If talks proceed, ownership likely shifts to Amazon and the question becomes whether Decart’s chip-neutral software continues to work across rival hardware.
PC shipments fell more than 20% in Q3 2026 as AI-related memory and storage shortages drove up component prices and demand faded after earlier pre-orders. Shipments dropped 21.2% year-on-year to 58.1 million units worldwide in Q3 2026. The market lost momentum, inventory built up from the first-half pull-in, and forecasts point to further declines in Q4 2026 and 2027.
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Anthropic reportedly reached a deal to lease computing power from SpaceX. The reported total value is up to $45 billion. As a result, Anthropic can secure more compute while the broader market shifts toward partnerships with competitors and funding-backed access to capacity.
The Austrian IT industry associations UBIT and VÖSI launched the Austrian Cloud Atlas, an interactive map of Austria’s data centers and digital infrastructure providers. It launched with 35 data centers, with most in Vienna and around Linz. The atlas is based on voluntary submissions, can be expanded continuously, and lets users filter and compare providers by attributes including “AI readiness,” connectivity, and resilience tier.
Nuvacore, a Sequoia-backed startup, is reportedly raising money at a roughly $2.5B valuation despite having no product yet. Investors would be asked to price its general-purpose CPU approach, with Reuters adding that the round had not closed and the amount and terms could change. The push is meant to accelerate AI data-centre demand for CPUs, with a first WarpCore benchmark expected to determine whether this CPU-first plan works.
European tech funding rebounded in September, with the largest deals listed by Tech.eu accounting for most of the month’s total. September funding reached €15.8 billion across 300 deals, up from €3.2 billion across 165 deals in August. The mix shifted with cloud taking the top-funded sector (€5.5 billion) instead of AI, while the biggest rounds drove 70.8% of funding.
Microsoft launched Maia 300, its next-generation AI inference platform for long-context reasoning, low-latency conversation, and agents on Azure. It is built around 8 HBM4 stacks and 96-accelerator racks, with a claim of 40% more tokens per megawatt. Production is set to start in 2027 and Maia 300 is intended to become the main inference system for Microsoft’s products as Azure scales to multi-gigawatt deployments.
llm-d’s distributed inference framework coordinates clusters of model servers so large LLM inference can handle many concurrent requests, reuse shared prompt context, and manage overload. In a demo, prefix-aware routing captured 97% of the available cache reuse in the tested workload. As a result, redundant prefill work drops and traffic is paced and routed more efficiently across servers, including when requests arrive in bursts from AI agents.
Minions aggregates idle Apple Silicon GPUs from macOS devices into a dynamic, distributed virtual GPU cloud for large-scale machine learning inference. The paper reports that idle macOS devices can be transformed into a practical distributed GPU inference platform when centralized GPU resources are constrained. As a result, teams can run GPU inference workloads with fault tolerance and better elasticity without buying more GPU hardware.
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