Dynatrace

JULY 6, 2022

While automating IT processes without integrated AIOps can create challenges, the approach to artificial intelligence itself can also introduce potential issues. This requires significant data engineering efforts, as well as work to build machine-learning models. AI that is based on machine learning needs to be trained.

Artificial Intelligence 246

Artificial Intelligence Tuning Strategy Big Data 246

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 results for data-related topics are both predictable and—there’s no other way to put it—confusing. This follows a 3% drop in 2018.

Software Architecture 142

Software Architecture DevOps Data Engineering Architecture 142

O'Reilly

MARCH 2, 2020

The most important is discovering how to work with data science and artificial intelligence projects. 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.

Artificial Intelligence 22

Artificial Intelligence Software Architecture Programming C++ 22

Abhishek Tiwari

DECEMBER 27, 2017

Data solution vendors like SnapLogic and Informatica are already developing machine learning and artificial intelligence (AI) based smart data integration assistants. These assistants can recommend next-best-action or suggest datasets, transforms, and rules to a data engineer working on a data integration project.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

InfoQ

APRIL 15, 2024

He specifically delved into Venice DB, the NoSQL data store used for feature persistence. At the QCon London 2024 conference, Félix GV from LinkedIn discussed the AI/ML platform powering the company’s products. By Rafal Gancarz

Artificial Intelligence 109

Artificial Intelligence Big Data Data Engineering Latency 109

InfoQ

MAY 8, 2024

Jules Damji discusses which infrastructure should be used for distributed fine-tuning and training, how to scale ML workloads, how to accommodate large models, and how can CPUs and GPUs be utilized? By Jules Damji

Tuning 91

Tuning Infrastructure Artificial Intelligence Data Engineering 91

InfoQ

AUGUST 3, 2023

AWS recently announced the general availability (GA) of Amazon EC2 P5 instances powered by the latest NVIDIA H100 Tensor Core GPUs suitable for users that require high performance and scalability in AI/ML and HPC workloads. The GA is a follow-up to the earlier announcement of the development of the infrastructure. By Steef-Jan Wiggers

AWS 75

AWS Availability Scalability Infrastructure 75