The advancement of natural language processing (NLP) capabilities has been to a large extent, dependent on developing large language models (LLMs). Although these models deliver high performance, they also pose challenges due to their need for immense computational resources and related costs, making them hard to scale up without incurring substantial expenses.
These challenges, therefore, create…
Snowflake recently introduced the Polaris Catalog, a new open-source catalog for Apache Iceberg designed to boost data interoperability across multiple engines and cloud services. The release illustrates Snowflake's commitment to granting businesses more control, flexibility, and security in their data management.
The data sector has grown increasingly fond of open-source file and table formats due to…
In the rapidly evolving Artificial Intelligence (AI) industry, key players, including Snowflake, Anthropic AI, Databricks, and Mistral AI, continue to introduce innovative updates, further demonstrating their critical roles in the AI and data sector.
Snowflake, renowned for its robust Data Cloud platform, has admirably integrated AI into its platform with its latest release, Snowflake Cortex. Introduced…
Integrating multiple generative foundation models provides an efficient way of generating outputs across various modalities, such as text, speech, and images, by leveraging each model's specific capabilities. However, the success of this integration highly depends on the alignment of data across modalities and the utilization of unimodal representations in cross-domain generative tasks.
To tackle this challenge,…
Keras, a popular machine learning tool known for its high-level abstractions and user-friendliness, faces challenges surrounding the cost of training large models, the complexity of preprocessing and metrics, and improving training performance. In response to these challenges, researchers from the Keras Team at Google have introduced KerasCV and KerasNLP. These extensions of the Keras API…
