IBM’s latest Granite 3.0 models are integrated into its WatsonX platform, the company’s AI and data platform that’s designed to help enterprises build, train, tune, and deploy AI models at ...

From a technical perspective, the implementation of domain-specific programming languages should result in a runtime environment that acts as a virtual machine directly invoking machine instructions.

DGCR proposes a novel domain-label-free generalization framework integrating intra-domain variational coupling quantification and cross-domain invariant similarity. This architecture dynamically ...

Analysing Table 2 and Table 3, it can be seen that the test accuracies of Stable-FedADG and FedADG outperform FedAvg significantly in both the LODO setting and the mixed setting, indicating that when ...

This article explores the use of domain-specific Generative AI, models that understand operational constraints, real-world dynamics, and business rules to generate executable strategies, not just ...

Building a domain-specific LLM isn’t cheap. The process involves curating high-quality datasets, securing powerful computing resources and employing experts to fine-tune and validate the model.

Recently, a research team developed an unsupervised domain adaptation (UDA) approach, the dual domain distribution disruption with semantics preservation (DDSP) framework, achieving high-precision ...

Even the selection of processing units can make a solution custom. “Domain-specific computing is already ubiquitous,” says Dave Fick, CEO and cofounder of Mythic. “Modern computers, whether in a ...