Remove use-case streaming-applications
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Machine learning model serving architectures

Xebia

In this blog we will discuss the most common serving architectures 1 ; batch predicting, on-demand synchronous serving and streaming serving. A prediction is as stale as the input data and model used to compute it. A higher ingestion frequency means more time sensitive use cases can be addressed.

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The use cases for a private wireless networks are many and increasing

CIO

Whether an enterprise’s use cases demand 4G LTE connectivity or the unprecedented speed and low latency of 5G, private wireless networks are helping keep devices, networks, and people connected and able to share and access data in real or near-real time. “We Their new private 5G network completely eliminated that issue.”

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Inferencing holds the clues to AI puzzles

CIO

As with many data-hungry workloads, the instinct is to offload LLM applications into a public cloud, whose strengths include speedy time-to-market and scalability. Data-obsessed individuals such as Sherlock Holmes knew full well the importance of inferencing in making predictions, or in his case, solving mysteries.

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Decoding Salesforce’s plausible $11 billion bid to acquire Informatica

CIO

Salesforce’s reported bid to acquire enterprise data management vendor Informatica could mean consolidation for the integration platform-as-a-service (iPaaS) market and a new revenue stream for Salesforce, according to analysts. This challenge requires tools with capabilities outside of what MuleSoft and Tableau can offer,” Park explained.

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Streaming data processing platform RisingWave lands $36M to launch a cloud service

TechCrunch

RisingWave Labs , a company developing a platform for data stream processing, today announced that it raised $36 million in a Series A funding round led by Yunqi Partners, undisclosed corporate investors and angel investors. Stream processing apps react to events from streams, for example triggering an action or updating a statistic.

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Unlocking the Power of AI with a Real-Time Data Strategy

CIO

To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making. It’s streaming data that’s collected, processed, and analyzed on a continuous basis.

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The New Way Companies are Harnessing Data at the Edge for Value Added in Real-Time

CIO

Imagine an airport that uses computer vision to track errant luggage in real time, or a commercial kitchen able to detect refrigeration conditions and prevent spoilage. In each case, they are taking strategic advantage of data generated at the edge, using artificial intelligence and cloud architecture.

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