Data management in 2024. Open data formats and a common language for a sixth data platform
What data management in 2024 and beyond will look like hangs on one question. Can open data formats lead to a best-of-breed data management platform? It will take Interoperability across clouds and formats, as well as on the semantics and governance layer. By George Anadiotis Sixth Platform. Atlas. Debezium. DCAT. Egeria. Nessie. Mesh. Paimon. Transmogrification. This […]
Read More →LinkedIn’s feed evolution: more granular and powerful machine learning, humans still in the loop
LinkedIn’s feed has come a long way since the early days of assembling the machine learning infrastructure that powers it. Recently, a major update to this infrastructure was released. We caught up with the people behind it to discuss how the principle of being people-centric translates to technical terms and implementation. How do data and […]
Read More →Striim brings cloud-modernization tool to AWS
Can real-time technology help companies save during economic hardship? Alok Pareek thinks it can. Pareek is the cofounder and executive VP of products at Striim, a vendor whose goal and motto is to, “help companies make data useful the instant it’s born”.
Read More →Red Hat and IBM team up to enhance AIops with an open-source project
AIops is what you get when you combine big data and machine learning to automate IT operations processes, including event correlation, anomaly detection and causality determination. At least, that’s how Gartner defines it.
Read More →How efficient code increases sustainability in the enterprise
Everything counts in large amounts. You don’t have to be Google, or build large AI models, to benefit from writing efficient code. But how do you measure that?
Read More →JupiterOne scores $70M series C funding, achieves unicorn status
Cloud security solutions are experiencing increased "growth and adoption." Cybersecurity platform JupiterOne is using graphs to capitalize on this.
Read More →SageMaker Serverless Inference illustrates Amazon’s philosophy for ML workloads
Amazon just unveiled Serverless Inference, a new option for SageMaker, its fully managed machine learning (ML) service. The goal for Amazon SageMaker Serverless Inference is to serve use cases with intermittent or infrequent traffic patterns, lowering total cost of ownership (TCO) and making the service easier to use.
Read More →Faros AI raises $16M to shine a light on developer productivity, launches free open source platform
What if what you think you know about developer productivity and the value of software is off the mark, and that is hurting the quality of your software, the operation of your organization, as well as your bottom line?
Read More →The rise of first-mile observability: Calyptia enables enterprises to log all the things
Cloud-native is the name of the game for application development. The creators of the Fluent Bit and Fluentd are launching an offering aimed at the enterprise
Read More →Reducing cloud waste by optimizing Kubernetes with machine learning
Applications are proliferating, cloud complexity is exploding, and Kubernetes is prevailing as the foundation for application deployment in the cloud. That sounds like an optimization task ripe for machine learning, and StormForge is acting up on that.
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