Question Our assessment; Is Nvidia technically ahead in AI networking? We believe it is materially ahead and stands alone at ...

Latest release leverages sparse neural networks to improve performance and enable more efficient edge AI on PolarFire® FPGAs ...

Oslo-based Iris (stylised as Iris.ai) provides what it calls a “semantic-enriched knowledge foundation” for enterprise software stacks building agentic AI services. To clarify, Iris builds ...

Enterprise AI is at an inflection point. What began with centralized, cloud-scale large language models (LLMs) is moving ...

Human cumulative culture depends on our ability to innovate. While most research emphasizes how social learning spreads and preserves innovations, the cognitive processes that generate them remain ...

Abstract: In the future network, delivering AI models from the edge to terminals is crucial for low-latency, privacy-preserving applications. However, this process poses significant challenges in ...

The understanding and generating AI agents are differentiated by a role prompt. The understanding AI agent takes the original data, channel sensing data, and task requirements as input, and outputs ...

Abstract: This paper proposes a model pruning named MPSS for semantic image segmentation networks, so that semantic image segmentation models can be deployed into embedded devices. Most existing model ...

Researchers have coined a new way to trick artificial intelligence (AI) chatbots into generating malicious outputs. AI security startup NeuralTrust calls it "semantic chaining," and it requires just a ...

What if the next big leap in artificial intelligence wasn’t about generating text or images but about truly understanding the world around us? The AI Grid outlines how a new model called VLJ ...

We introduce a geometric semantic model designed to capture fine-grained semantic representations in a multidimensional space. Building on this model, we develop a novel annotation framework that ...