Scalegrid

FEBRUARY 8, 2024

Distributed storage technologies use innovative tools such as Hive, Apache Hadoop, and MongoDB, among others, to proficiently deal with processing extensive volumes encountered in multiple-node-based systems. This integration enhances the flexibility of cloud services while bolstering their computational and storage functions.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

DECEMBER 16, 2019

And while the concept is not new, the disruptions of cloud transformation and increasing time-to-market pressures shine a bright light on its many downsides. Our good intentions promise that we’ll revisit the shortcomings later—but of course “later” rarely arrives. Dynatrace news. Many of us are already familiar with technical debt.

Artificial Intelligence 147

Artificial Intelligence Traffic Efficiency Innovation 147

Dynatrace

JUNE 1, 2021

However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and of course, end-users that access these applications — including a company’s customers and employees. Increased time spent on innovation. Why cloud-native applications make APM challenging.

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

All Things Distributed

SEPTEMBER 4, 2017

In the case of artificial intelligence (AI) and machine learning (ML), this is different. Secondly, there is enough affordable computing capacity in the cloud for companies and organizations, no matter what their size, to use intelligent applications. Artificial intelligence helps to satisfy the customer.

Artificial Intelligence 147

Artificial Intelligence Transportation Education Airlines 147

O'Reilly

DECEMBER 2, 2019

What would the world look like if all of our storage was in the cloud, and access to that storage was so fast we didn’t care? If an office can get that kind of bandwidth to my laptop, with adequate guarantees for cloud security, why should we worry about office LANs? I do regular backups, but I know I’m the exception.

Wireless 53

Wireless Serverless IoT Artificial Intelligence 53

O'Reilly

FEBRUARY 18, 2020

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. The shift to cloud native design is transforming both software architecture and infrastructure and operations. Still cloud-y, but with a possibility of migration.

Software Architecture 134

Software Architecture DevOps Data Engineering Architecture 134

O'Reilly

NOVEMBER 28, 2023

Even with cloud-based foundation models like GPT-4, which eliminate the need to develop your own model or provide your own infrastructure, fine-tuning a model for any particular use case is still a major undertaking. And of course, companies that don’t use AI don’t need an AI use policy. We’ll say more about this later.)

Open Source 108

Open Source Artificial Intelligence Google Infrastructure 108

O'Reilly

FEBRUARY 13, 2024

I’m sure the monopolists would say “of course, those can be built by fine tuning our foundation models”; but do we know whether that’s the best way to build those applications? Or will innovation only be possible through the entrenched monopolies? Will that be possible in the future? Will there be a proliferation of models?

Open Source 93

Open Source Strategy Government Tuning 93