Category: Computing & data (Page 12 of 94)

DataStax, a AI platform, announced the enhancement of its GitHub Copilot extension with its AI Platform-as-a-Service (AI PaaS) solution. This extension makes it easier for developers to directly interact with DataStax Langflow and their Astra DB databases’ vector, tabular, and streaming data right from their IDE (integrated development environment) through the DataStax GitHub Copilot Extension. 

As generative AI adoption accelerates, developers are seeking tools that not only enhance productivity but also simplify complex workflows, enabling them to keep pace with innovation. New features include:

• Database Creation: Developers can create databases (vector or serverless), in the user’s preferred cloud provider and region, in Astra DB directly through GitHub Copilot.
• Flow creation: The Copilot Extension can build Langflow flows using simple English conversational prompts, provide direct links to the flows, and generate API calls to Langflow application endpoints in VSCode.
• Expanded Capabilities: Copilot answers questions about databases and helps troubleshoot queries. These new features address challenges developers face by bringing low-code and traditional developers together, enabling a broader range of experience levels to leverage powerful AI tools within the familiar VS Code environment. This reduces the time to production, especially for teams that need to deliver quickly in competitive environments.

https://www.datastax.com/blog/astra-db-extension-github-copilot-updates

Semantic Web Company and Ontotext today announced the two companies have merged to become Graph AI provider, Graphwise. Semantic Web Company brings expertise in knowledge engineering, semantic AI and intelligent document processing, while Ontotext brings a versatile graph database engine and AI models for linking and unifying information.

Combining Ontotext GraphDB’s data management capabilities with PoolParty, knowledge and content management offerings from Semantic Web Company, Graphwise has created a comprehensive knowledge graph management platform, which includes complete multi-modal data support – unstructured, semi-structured and structured data. The Graphwise Platform, will enable customers to benefit from: 

• Sophisticated, accurate and reliable AI applications that leverage the power of knowledge graphs for applications like Graph RAG, NLP, recommendation systems, and predictive analysis. 
• Support unstructured and semi-structured data management into data fabric processes. 
• The ability to scale effortlessly, while ensuring data remains well-structured and classified. This enables businesses to build AI systems capable of navigating vast networks of interconnected information without sacrificing accuracy or performance. 
• Enhanced flexibility in designing models by providing the tools necessary in one platform to simplify architectural decisions.
• A combined partner ecosystem and a broader market which creates more opportunities, including significantly larger project volumes. 

https://graphwise.ai

MongoDB, Inc. released MongoDB 8.0, providing performance improvements, reduced scaling costs, and additional scalability, resilience, and data security capabilities. MongoDB 8.0 is available on AWS, Google Cloud, and Microsoft Azure through MongoDB Atlas, on MongoDB Enterprise Advanced for on-premises and hybrid deployments, and as a free download with MongoDB Community Edition. Capabilities: 

• Optimized performance for a wide variety of applications. 
  Architectural optimizations reduced memory usage and query times, has more efficient batch processing capabilities, and handles higher volumes of time series data.
• Encryption that unlocks new use cases.
• Queryable Encryption allows customers to encrypt sensitive application data, store it securely and run expressive queries on the encrypted data for processing.
• Faster horizontal scaling for high availability.
• Sharding improvements in MongoDB 8.0 distribute data across shards faster without the need for additional configuration. 
• Resilience for unexpected application demand. 
• The ability to set a default maximum time limit for running queries, to reject recurring types of problematic queries, and to set query settings to persist through events like database restarts. 
• Reduced costs and increased scale for vector applications.
• With vector quantization, customers can build a wide range of search and AI applications at higher scale and lower cost.

https://www.mongodb.com/products/updates/version-release