Dnotitia Releases DNA 3.0 Language Model Family on Hugging Face
Dnotitia Inc. announced in a press release the release of DNA 3.0, a family of enterprise AI language models now available on Hugging Face. The models are built on the Qwen 3.5 and 3.6 large language models from Alibaba Cloud, with Dnotitia applying its own post-training and tuning to adapt them for organizational use.
DNA 3.0 has been designed to deliver consistent responses aligned with enterprise data, workflows, and service policies. The models incorporate persona training to reflect company-specific context and product information. Dnotitia also reduced language-mixing issues and response constraints to improve usability in Korean-language enterprise environments.
The DNA 3.0 lineup includes models ranging from 0.8 billion to 122 billion parameters, including Mixture of Experts architectures such as 35B-A3B and 122B-A10B. These architectures activate selected expert modules for each query to balance performance and computational efficiency.
DNA 3.0 is integrated into Seahorse Cloud, Dnotitia’s AI data platform, which transforms enterprise documents and unstructured data into knowledge assets. This integration supports semantic search, context-aware answer generation, and AI agent workflows based on enterprise information.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Enterprise AI Brief or Daily AI Brief.
Also, consider following us on social media:
More from Enterprise
Oct 16 BOC Group Adds AI Assistant to ADOIT 21 Oct 16 Huawei Brings Upgraded Stellar Network Solution to Europe Oct 16 Element to Manage Waymo's Toronto Fleet for 2028 Launch Oct 16 CTM and Huawei Plan AI Network Security Upgrades in Macao Oct 16 Huawei and 14 partners form Global AI CITY allianceEnterprise AI Brief
Weekly report on AI business applications, enterprise software releases, automation tools, and industry implementations.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
Dnotitia Begins Testing VDPU ASIC Samples
Nuix Introduces Governed Generative AI Framework
Illumina Launches BioInsight Platform for Genomic Research
Dun & Bradstreet Adds AI Credit Analysis Tools to Finance Analytics
IFM and Inception42 Launch Jais 3 Arabic AI Models
Daily AI Brief: the AI news that matters, in your inbox.