📹 Eddie Ramirez speaks to TechArena.ai at the Chiplet Summit to share more details on the first public specification of the Chiplet System Architecture, which now has more than 60 companies engaged. As a growing number of organizations turn to chiplets to meet the performance and power consumption demands of AI, CSA empowers designers with a shared understanding of how to define and connect chiplets into composable SoCs. This has game-changing implications for the development and deployment of Arm-based custom silicon solutions that meet the performance and efficiency requirements of the AI era: https://okt.to/W0yP8C
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I’ve written before about the potential for chiplets to transform compute in the AI era, so at this year’s Chiplet Summit, the TechArena team was thrilled to hear from Arm's Eddie Ramirez, VP of Go-To-Market, Infrastructure Business, about their new Chiplet Standard Architecture Specification. This standard is a big step towards ensuring interoperability between chiplets, streamlining industry collaboration to deliver next-gen SoCs tailored to unique AI workloads. Check out the interview with Eddie here: https://hubs.ly/Q034mNJ20 #ChipletSummit2025 #Chiplets #Arm
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Discover how the Stable Diffusion model revolutionizes text-to-image generation using a sophisticated latent diffusion approach and U-Net architecture. Learn about its forward and reverse diffusion processes, conditioning on text prompts, and versatile applications in AI-driven image creation. Read the full article here: https://lnkd.in/ghuZXjHz #generativeai #stablediffusion
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The first public specification of the Chiplet System Architecture (CSA) is now available, unlocking new paths to silicon innovation that meets the compute demands of AI across all markets. With over 60 leading players within the tech industry engaged, this forms the foundation for an Arm-based chiplet ecosystem with flexible, accessible and cost-effective SoCs.
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The first public specification of the Chiplet System Architecture (CSA) is now available, unlocking new paths to silicon innovation that meets the compute demands of AI across all markets. With over 60 leading players within the tech industry engaged, this forms the foundation for an Arm-based chiplet ecosystem with flexible, accessible and cost-effective SoCs.
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Senior Global Events Manager: A proactive self-starter with 15 years of experience in global event management spanning across in-person, virtual and hybrid events.
The first public specification of the Chiplet System Architecture (CSA) is now available, unlocking new paths to silicon innovation that meets the compute demands of AI across all markets. With over 60 leading players within the tech industry engaged, this forms the foundation for an Arm-based chiplet ecosystem with flexible, accessible and cost-effective SoCs.
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"Janus-Pro is a novel autoregressive framework that unifies multimodal understanding and generation. It addresses the limitations of previous approaches by decoupling visual encoding into separate pathways, while still utilizing a single, unified transformer architecture for processing. The decoupling not only alleviates the conflict between the visual encoder’s roles in understanding and generation, but also enhances the framework’s flexibility. Janus-Pro surpasses previous unified model and matches or exceeds the performance of task-specific models. The simplicity, high flexibility, and effectiveness of Janus-Pro make it a strong candidate for next-generation unified multimodal models." https://lnkd.in/gYUBiSas
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The first public specification of the Chiplet System Architecture (CSA) is now available, unlocking new paths to silicon innovation that meets the compute demands of AI across all markets. With over 60 leading players within the tech industry engaged, this forms the foundation for an Arm-based chiplet ecosystem with flexible, accessible and cost-effective SoCs.
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Machine Learning Engineer | Deep Learning & NLP Specialist | AI & Robotics Innovator | Kaggle Expert | GenAI & Intelligent Automation | Physicist & Writer | Computer Vision, Medical Imaging, & Research Specialist
Proposed a new model architecture called MobileNets based on depthwise separable convolutions. We investigated some of the important design decisions leading to an efficient model. We then demonstrated how to build smaller and faster MobileNets using width multiplier and resolution multiplier by trading off a reasonable amount of accuracy to reduce size and latency. We then compared different MobileNets to popular models demonstrating superior size, speed and accuracy characteristics. We concluded by demonstrating MobileNet’s effectiveness when applied to a wide variety of tasks. As a next step to help adoption and exploration of MobileNets, we plan on releasing models in Tensor Flow.
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What if we told you that you can switch between AI models in milliseconds? ⚡️ With our unique RDU chip architecture, the SN40L, you can do so with ease. SambaNova Fast API also includes free rate-limited token credits, so you can get started right away. Learn more 👉 https://lnkd.in/g9W_Bnjv #FastAI #LLM #API
