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Pliops lands $100M for chips that accelerate analytics in data centers

TechCrunch

Part of the problem is that data-intensive workloads require substantial resources, and that adding the necessary compute and storage infrastructure is often expensive. Adding more infrastructure often proves to be cost prohibitive and hard to manage. Thirty-six percent cited controlling costs as their top challenge. . ”

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10 ways AI can make IT more productive

CIO

Scale more efficiently AI can automate an array of routine tasks, ensuring consistent operations across the entire IT infrastructure, says Alok Shankar, AI engineering manager at Oracle Health. This scalability allows you to expand your business without needing a proportionally larger IT team.”

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How AWS sales uses Amazon Q Business for customer engagement

AWS Machine Learning - AI

With Amazon Q Business, we no longer need to manage each of the infrastructure components required to deliver a secure, scalable conversational assistantinstead, we can focus on the data, insights, and experience that benefit our salesforce and help them make our customers successful on AWS.

AWS 109
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Scaling Kafka at Honeycomb

Honeycomb

When you send telemetry into Honeycomb, our infrastructure needs to buffer your data before processing it in our “retriever” columnar storage database. Using Apache Kafka to buffer the data between ingest and storage benefits both our customers by way of durability/reliability and our engineering teams in terms of operability.

Storage 145
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Netflix at AWS re:Invent 2019

Netflix Tech

4:45pm-5:45pm NFX 202 A day in the life of a Netflix Engineer Dave Hahn , SRE Engineering Manager Abstract : Netflix is a large, ever-changing ecosystem serving millions of customers across the globe through cloud-based systems and a globally distributed CDN. Thursday?—?December

AWS 15
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Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

AWS Machine Learning - AI

Scalability and performance – The EMR Serverless integration automatically scales the compute resources up or down based on your workload’s demands, making sure you always have the necessary processing power to handle your big data tasks. By unlocking the potential of your data, this powerful integration drives tangible business results.

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How Twilio generated SQL using Looker Modeling Language data with Amazon Bedrock

AWS Machine Learning - AI

This solution uses Amazon Bedrock, Amazon Relational Database Service (Amazon RDS), Amazon DynamoDB , and Amazon Simple Storage Service (Amazon S3). DynamoDB is a highly scalable and durable NoSQL database service, enabling you to efficiently store and retrieve chat histories for multiple user sessions concurrently.