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Solving The Von Neumann Bottleneck With FPGAs

Hu's Place - HitachiVantara

Today I will be covering the advances that we have made in the area of hybrid-core architecture and its application to Network Attached Storage. This hybrid-core architecture is a unique approach which we believe will position us for the future, not only for NAS but for the future of compute in general.

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Bringing an AI Product to Market

O'Reilly Media - Ideas

For example, an AI product that helps a clothing manufacturer understand which materials to buy will become stale as fashions change. CTRs are easy to measure, but if you build a system designed to optimize these kinds of metrics, you might find that the system sacrifices actual usefulness and user satisfaction.

Marketing 145
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Journey to Event Driven – Part 2: Programming Models for the Event-Driven Architecture

Confluent

Part 1 of this series discussed why you need to embrace event-first thinking, while this article builds a rationale for different styles of event-driven architectures and compares and contrasts scaling, persistence and runtime models. In this way, we don’t think about solution architecture in just one dimension. Data evolution.

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Journey to Event Driven – Part 3: The Affinity Between Events, Streams and Serverless

Confluent

What is more, as the world adopts the event-driven streaming architecture, how does it fit with serverless? Serverless functions provide a synergistic relationship with event streaming applications; they behave differently with respect to streaming workloads but are both event driven. Do they complement or compete? What is FaaS?

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Journey to Event Driven – Part 4: Four Pillars of Event Streaming Microservices

Confluent

Storing events in a stream and connecting streams via stream processors provide a generic, data-centric, distributed application runtime that you can use to build ETL, event streaming applications, applications for recording metrics and anything else that has a real-time data requirement. Why a payment system, you ask?

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Image Recognition with Deep Neural Networks and its Use Cases

Altexsoft

Since most deep learning methods use neural network architectures, deep learning models are frequently called deep neural networks. Neural networks are computing systems designed to recognize patterns. Their architecture is inspired by a human brain structure, hence the name. What makes a neural network deep?

Network 20
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Technology Trends for 2022

O'Reilly Media - Ideas

What are the bigger changes shaping the future of software development and software architecture? Content about privacy is up 90%; threat modeling is up 58%; identity is up 50%; application security is up 45%; malware is up 34%; and zero trust is up 23%. This report is about those transitions. Software Development.

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