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July 8: From BI to AI (, IBM, Meta, Ontotext)

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IBM Expands Observability Capabilities with Acquisition

IBM announced Wednesday that they had acquired, a data observability software provider. looks for issues such as data anomalies, missing or incomplete data, and other problems that come up during the data transformation process. IBM suggests that pairing with IBM Observability by Instana APM and Watson Studio will combine application performance monitoring and data observability into a more complete observability platform spanning a broader spectrum of IT ops. employees will join IBM’s Data and AI group.

Launches and Updates

Meta Debuts Improved Language Translation Model and Dataset

Meta announced Wednesday that their AI researchers had built an AI model, NLLB-200 (No Language Left Behind) that significantly improves the accuracy of machine translation between 200 different languages. Meta also compiled the FLORES-200 dataset to measure NLLB-200’s language performance to ensure high-quality translations. Developers will be able to access both NLLB-200 and FLORES-200, and Meta will award $200,000 in grants for “impactful uses” of NLLB-200; specifically, researchers working in linguistics, machine translation, and language technology, as well as nonprofits translating two or more African languages, are invited to apply.

Ontotext Releases GraphDB 10.0

Ontotext announced GraphDB 10.0, the latest major release of their database engine. Key new features include a new high-availability cluster architecture with higher uptime, zero data loss, better fault tolerance, and better recovery from failures; an improved graph path search algorithm that can run in parallel mode in multicore environments, enabling faster processing on complex searches and the ability to handle more concurrent requests; improved full text search; and a simplified upgrade path requiring no development effort to upgrade from free to standard to enterprise editions of GraphDB.