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Using integrated modeling solutions to implement model-driven data management and development can help organizations share knowledge effectively and with minimum effort. It will certainly produce ...
Switzerland launched an open-source model called Apertus on Monday as an alternative to proprietary models like OpenAI’s ChatGPT or Anthropic’s Claude, reports SWI as spotted by Engadget. The model’s ...
Even as large language models have been making a splash with ChatGPT and its competitors, another incoming AI wave has been quietly emerging: large database models.
Logical database models should allow their observer to review the model’s content, and in so doing learn about the organization and data within the solution space. Lower veracity data models only ...
In June, Google DeepMind took the wraps off AlphaGenome, its latest machine learning model for biological discovery. While ...
Storing data in multi-model database wards off this problem. As a modern management system, multi-model databases offer an elegant solution to managing diverse and unstructured data. Instead of ...
Recent reports have predicted that publicly available, relevant data necessary for training AI models is expected to run out by 2026. The global AI market is projected to reach $1.8 trillion by ...
One of the most important steps in desiging a database is establishing the data model. Part one of a two-part article describes how to create a logical model.
Most projects benefit from having a data model. Read this article for an overview of the most common types.
Data science leaders can’t put their heads in the sand when it comes to maintaining data science models–the stakes are too high. A survey by Accenture showed that 75% of executives believe their ...
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