WEKA

🌎 The global memory shortage is changing how organizations build and scale #AIInfrastructure — and customers can’t afford to wait 6–12 months for hardware to arrive. The partners winning right now are helping customers get more out of the infrastructure they already own. Join Val Bercovici next week for a conversation on how software-defined architecture can unlock memory-class performance, improve AI throughput, lower cost per usable terabyte, and keep AI projects moving despite ongoing HBM, DRAM, and NVMe constraints. 🗓️ https://weka.ly/4tIC9pz

🚀 From skyrocketing token costs to global memory shortages and the rise of agentic AI, the industry is hitting a new reality: scaling inference efficiently now matters more than simply adding more GPUs. At #HumanX, WEKA's Val Bercovici joined industry leaders to discuss token ROI, the AI memory wall, and why infrastructure efficiency is becoming critical for AI at scale. 🎥 Check out the full conversation: https://weka.ly/3PD1cvY

🏭 Powering AI workloads in manufacturing only works if infrastructure can keep up with the speed of production without sacrificing quality. Our latest solution brief explores how NeuralMesh delivers ultra-low latency, real-time GPU saturation, and fully automated quality control to help manufacturers accelerate workloads across predictive maintenance, defect detection, robotics, aerospace, automotive, and industrial manufacturing workflows. For organizations looking to move faster, improve accuracy, and get more value from their #AIInfrastructure without bottlenecks slowing production down, NeuralMesh delivers the performance and efficiency modern manufacturing demands. 🔗 Take a closer look: https://weka.ly/4drBvrH

📌 ICYMI: AI clouds need more than just performance at scale. They need the flexibility to support both dedicated and shared infrastructure models efficiently. WEKA’s Phil Curran breaks down how NeuralMesh multitenancy helps AI cloud providers support physically isolated dedicated tenants and logically isolated shared infrastructure — all on a single platform. 👉 Take a look: https://weka.ly/4twJDM1

The organizations that win the next phase of AI won’t be the ones with the most GPUs. They’ll be the ones that maximize token efficiency and optimize memory architecture. In this article, WEKA's Val Bercovici explains why memory — not compute alone — is becoming the defining challenge for AI inference at scale. Take a closer look and learn how WEKA’s Augmented Memory Grid enables organizations to unlock up to 6.5x more tokens from the same infrastructure 👇

🌐 The global AI memory shortage isn't going anywhere, and It’s already reshaping how organizations build and scale #AIInfrastructure. In this Forbes article, WEKA CEO Liran Zvibel explains why the industry’s growing demand for inference is colliding with limited memory supply and why simply stockpiling more hardware isn’t a sustainable answer. The real opportunity now is optimization: extending GPU memory, improving utilization, and getting more performance from the infrastructure already deployed. 🔗 Get the full story: https://weka.ly/4wsQHMu

🇩🇪 We’re heading to ISC High Performance 2026 to showcase how NeuralMesh powers simulation, AI training, inference, and automation together on a single platform built for accelerated compute. If you’re attending the show, stop by to see how organizations are scaling AI and HPC workloads with the performance, efficiency, and sovereignty modern infrastructure demands. 👋 See you in Hamburg: https://weka.ly/48Xhd6H #ISC26

The AI conversation is shifting from simply acquiring more GPUs to getting more value out of the ones already deployed. As VentureBeat highlights, inference introduces “a memory tax that crushes unit economics as concurrency rises” — and that’s exactly the challenge WEKA’s Augmented Memory Grid was built to solve. First launched last year and available today, Augmented Memory Grid delivers up to 6.5x more tokens per GPU while significantly lowering cost per token for AI inference workloads. 🔗 Read the full article: https://weka.ly/4eNATxD

🎉 Still thinking about how incredible MTX - Milipol TechX in Singapore was! More than 21,000 attendees from 89 countries came together to explore the future of public safety, AI, and mission critical technology. A huge thank you to everyone who connected with the WEKA team along the way. The conversations, energy, and collaboration made this event one to remember. #MilipolTechX

💬 In a recent interview with Globes, WEKA CEO Liran Zvibel explains why the “memory wall” is becoming one of the biggest constraints in AI, especially as agentic workloads and autonomous coding tools drive massive increases in token consumption and context requirements. The conversation explores why memory architecture is now critical to AI performance, how WEKA helps reduce latency and expand accessible memory for GPUs, and why the next phase of #AIInfrastructure will be defined by efficiency as much as scale. 🔗 https://weka.ly/3QXoNbb