Architecture Engineering Management Storage 
TechCrunch
AUGUST 16, 2022
Part of the problem is that data-intensive workloads require substantial resources, and that adding the necessary compute and storage infrastructure is often expensive. Pliop’s processors are engineered to boost the performance of databases and other apps that run on flash memory, saving money in the long run, he claims.
AWS Machine Learning - AI
DECEMBER 11, 2024
When Amazon Q Business became generally available in April 2024, we quickly saw an opportunity to simplify our architecture, because the service was designed to meet the needs of our use caseto provide a conversational assistant that could tap into our vast (sales) domain-specific knowledge bases.
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AWS Machine Learning - AI
OCTOBER 8, 2024
In this post, we collaborate with the team working on PyTorch at Meta to showcase how the torchtitan library accelerates and simplifies the pre-training of Meta Llama 3-like model architectures. Introduction to torchtitan torchtitan is a reference architecture for large-scale LLM training using native PyTorch.
Honeycomb
NOVEMBER 30, 2021
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.
CTOvision
FEBRUARY 4, 2015
Implementing an Enterprise Data Hub — Technical perspectives for implementing enterprise data hub architectures, converged analytics for workflow optimization, and the essential role of open standards and frameworks to ensure continuous innovation. High Performance Computing Lead, NASA Center for Climate Simulation (NCCS). Eddie Garcia.
Altexsoft
JULY 19, 2022
In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. They are: domain-oriented decentralized data ownership and architecture, data as a product, self-serve data infrastructure as a service, and.
CTOvision
JANUARY 18, 2015
Implementing an Enterprise Data Hub — Technical perspectives for implementing enterprise data hub architectures, converged analytics for workflow optimization, and the essential role of open standards and frameworks to ensure continuous innovation. High Performance Computing Lead, NASA Center for Climate Simulation (NCCS). Eddie Garcia.
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