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inference infrastructure

30 articles about inference infrastructure in AI news

Meta Expands Broadcom Partnership for Next-Gen AI Infrastructure

Meta is expanding its partnership with semiconductor giant Broadcom to co-develop its next-generation AI infrastructure. This move signals a continued, long-term commitment to custom silicon for AI training and inference.

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Perplexity Claims 3x Blackwell Inference Throughput for 70B Models

Perplexity AI claims 3x inference throughput for 70B models on Nvidia Blackwell GPUs via FP4 and custom scheduling. The gain exceeds Nvidia's own 2x marketing claim.

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mlx-vlm v0.5.0 Adds Continuous Batching, Distributed Inference for Apple Silicon

mlx-vlm v0.5.0 adds continuous batching, speculative decoding, and distributed inference for Apple Silicon. The release supports Qwen3.5, Kimi K2.5, Gemma 4 video, and new models with 21 contributors.

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GUC, Wiwynn Partner on Silicon-to-System AI Infrastructure for Hyperscalers

GUC and Wiwynn partner on silicon-to-system AI infrastructure, integrating SoC design, optical I/O, and liquid cooling for hyperscalers.

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OpenAI Claims 10GW AI Infrastructure Capacity Ahead of 2029 Target

OpenAI claims 10GW AI infrastructure capacity secured, adding 3GW in 90 days, ahead of 2029 target.

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AI Inference Costs Drop 5-10x Yearly: @kimmonismus Challenges Forbes

@kimmonismus claims AI inference costs drop 5-10x yearly, challenging Forbes' static compute cost narrative. This deflation rate implies rapid TCO reduction for enterprise deployments.

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PayPal Cuts LLM Inference Cost 50% with EAGLE3 Speculative Decoding on H100

PayPal engineers applied EAGLE3 speculative decoding to their fine-tuned 8B-parameter commerce agent, achieving up to 49% higher throughput and 33% lower latency. This allowed a single H100 GPU to match the performance of two H100s running NVIDIA NIM, cutting inference hardware cost by 50%.

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Sam Altman: AI inference costs dropped 1000x from o1 to GPT-5.4

Sam Altman stated AI inference costs for solving a fixed hard problem dropped ~1000x from o1 to GPT-5.4 in ~16 months, crediting cross-layer engineering optimizations, not a single breakthrough.

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Bull Delivers HPC Infrastructure to Power Mimer AI Factory

Bull, a subsidiary of Atos, has supplied the core HPC infrastructure for Mimer's new AI factory. This facility is dedicated to training and developing large language models for the European market.

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CoreWeave & Google Raise $6.7B in Junk Bonds for AI Infrastructure

Google and GPU cloud provider CoreWeave have jointly raised $6.7 billion through a junk bond offering, with Google taking $5.7 billion. The capital is earmarked for a significant build-out of AI data center infrastructure.

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Prefill-as-a-Service Paper Claims to Decouple LLM Inference Bottleneck

A research paper proposes a 'Prefill-as-a-Service' architecture to separate the heavy prefill computation from the lighter decoding phase in LLM inference. This could enable new deployment models where resource-constrained devices handle only the decoding step.

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Meta to Cut 8,000 Jobs in May, Redirecting Capital to AI Infrastructure

Meta is reportedly planning to lay off 8,000 employees in May, the first round of major cuts this year. The move signals a capital shift from general operations to concentrated investment in AI infrastructure like chips and data centers.

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DOE Seeks Input on AI Infrastructure for Federal Lands

The U.S. Department of Energy has published a Request for Information (RFI) to solicit input on developing AI and high-performance computing infrastructure on DOE-owned lands. This marks a significant step in the federal government's strategy to directly address the national AI compute shortage.

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Nvidia: Cost Per Token Is the Only AI Infrastructure Metric That Matters

Nvidia asserts that total cost of ownership for AI infrastructure must be measured in cost per delivered token, not raw compute metrics. This shift is critical for scaling profitable agentic AI applications.

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Intel & Google Announce Multiyear AI & Cloud Infrastructure Partnership

Intel and Google have announced a multiyear strategic collaboration to advance AI and cloud infrastructure, focusing on optimizing Google Cloud for Intel's Xeon processors, Gaudi AI accelerators, and future chips.

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Cursor AI Claims 1.84x Faster MoE Inference on NVIDIA Blackwell GPUs

Cursor AI announced a rebuilt inference engine for Mixture-of-Experts models on NVIDIA's new Blackwell GPUs, resulting in a claimed 1.84x speedup and improved output accuracy.

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McKinsey: AI Infrastructure Value Creation Outpaces Business Capture

McKinsey's latest analysis indicates the pace of value creation from AI infrastructure is exceeding the rate at which most businesses are capturing it, highlighting a growing implementation deficit.

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Nvidia Claims MLPerf Inference v6.0 Records with 288-GPU Blackwell Ultra Systems, Highlights 2.7x Software Gains

MLCommons released MLPerf Inference v6.0 results, introducing multimodal and video model tests. Nvidia set records using 288-GPU Blackwell Ultra systems and achieved a 2.7x performance jump on DeepSeek-R1 via software optimizations alone.

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Google's AI Infrastructure Strategy: What Retail Leaders Should Watch in 2026

Google's evolving AI infrastructure and compute strategy, including data center investments and model compression techniques, will directly impact how retail brands deploy and scale AI applications by 2026. The company's focus on efficiency and real-time capabilities signals a shift toward more accessible, powerful retail AI tools.

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Inference Beauty Today Announces Global Platform Expansion, Powering Personalized Beauty Discovery for 100+ Retailers and Brands

Inference Beauty Today has expanded its AI-powered personalized beauty discovery platform globally, now serving over 100 retailers and brands across five markets. This signals the maturation of specialized, third-party AI recommendation engines in the beauty and personal care sector.

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Oracle Cuts 20% of Workforce to Fund AI Infrastructure Push, Shifting from Labor to Compute

Oracle is laying off 20% of its workforce to redirect capital toward massive AI infrastructure investments. The move signals a strategic pivot from traditional workforce costs to data center and compute spending.

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Meta's Adaptive Ranking Model: A Technical Breakthrough for Efficient LLM-Scale Inference

Meta has developed a novel Adaptive Ranking Model (ARM) architecture designed to drastically reduce the computational cost of serving large-scale ranking models for ads. This represents a core infrastructure breakthrough for deploying LLM-scale models in production at massive scale.

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Data Center Construction Boom Drives Electrician Salaries to $260k, Fueled by AI Infrastructure Demand

Mike Rowe reports data center electricians earning $260,000/year without degrees as 25.3 GW of capacity is under construction in the Americas, with 89% pre-committed. The AI infrastructure buildout is creating a high-wage, skilled trades bottleneck.

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Fractal Emphasizes LLM Inference Efficiency as Generative AI Moves to Production

AI consultancy Fractal highlights the critical shift from generative AI experimentation to production deployment, where inference efficiency—cost, latency, and scalability—becomes the primary business constraint. This marks a maturation phase where operational metrics trump model novelty.

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arXiv Survey Maps KV Cache Optimization Landscape: 5 Strategies for Million-Token LLM Inference

A comprehensive arXiv review categorizes five principal KV cache optimization techniques—eviction, compression, hybrid memory, novel attention, and combinations—to address the linear memory scaling bottleneck in long-context LLM inference. The analysis finds no single dominant solution, with optimal strategy depending on context length, hardware, and workload.

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Groq's LPU Inference Engine Demonstrates 500+ Token/s Performance on Llama 3.1 70B

Groq's Language Processing Unit (LPU) inference engine achieves over 500 tokens/second on Meta's Llama 3.1 70B model, demonstrating significant performance gains for large language model inference.

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Why Companies End Up Using Triton Inference Server: A Simple Case Study

A case study explains the common journey from a simple ML experiment to a production system requiring a robust inference server like NVIDIA's Triton, highlighting its role in managing multi-model, multi-framework deployments at scale.

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Axiom Secures $200M Series A at $1.6B+ Valuation, Signaling Major Shift in AI Infrastructure

AI infrastructure startup Axiom has raised $200 million in Series A funding at a valuation exceeding $1.6 billion. The round was led by Paradigm and Standard Crypto, with participation from Robot Ventures and other investors. This massive early-stage investment highlights growing investor confidence in next-generation AI development platforms.

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IonRouter Emerges as Cost-Efficient Challenger to OpenAI's Inference Dominance

YC-backed Cumulus Labs launches IonRouter, a high-throughput inference API that promises to slash AI deployment costs by optimizing for Nvidia's Grace Hopper architecture. The service offers OpenAI-compatible endpoints while enabling teams to run open-source or fine-tuned models without cold starts.

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Nscale's $2 Billion Bet: How a UK AI Infrastructure Startup Became Europe's New Tech Titan

UK-based AI infrastructure company Nscale has secured a massive $2 billion Series C round, valuing it at $14.6 billion. The funding will accelerate global deployment of vertically integrated AI data centers, with former Meta executives Sheryl Sandberg and Nick Clegg joining the board.

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