Remove 2020 Remove Data Processing Remove Experimentation Remove Modeling
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Your New Cloud for AI May Be Inside a Colo

CIO Business Intelligence

Many companies whose AI model training infrastructure is not proximal to their data lake incur steeper costs as the data sets grow larger and AI models become more complex. The cloud is great for experimentation when data sets are smaller and model complexity is light. Potential headaches of DIY on-prem infrastructure.

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The DataOps Vendor Landscape, 2021

DataKitchen

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. Acquired by Informatica, July 2020) . GitHub – A provider of Internet hosting for software development and version control using Git. Meta-Orchestration .

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Try semantic search with the Amazon OpenSearch Service vector engine

AWS Big Data

Amazon OpenSearch Service has long supported both lexical and vector search, since the introduction of its kNN plugin in 2020. For the demo, we’re using the Amazon Titan foundation model hosted on Amazon Bedrock for embeddings, with no fine tuning. Only items that have all or most of the words the user typed match the query.

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How Agencies Can Gain the Cyber Edge with Smart Data Solutions

Cloudera

Consider the fact that the SolarWinds Orion supply chain breach (attributed to Russia) from 2020 continues to make news , with many customers still in the dark as to whether they were compromised or not. To learn more, read our technical brief: Securely Train and Deploy Machine Learning Models in Production with Cloudera Data Platform.

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The mainframe is dying: Long live the mainframe application!

CIO Business Intelligence

Fujitsu remains very much interested in the mainframe market, with a new model still on its roadmap for 2024, and a move under way to “shift its mainframes and UNIX servers to the cloud, gradually enhancing its existing business systems to optimize the experience for its end-users.”

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On the Hunt for Patterns: from Hippocrates to Supercomputers

Ontotext

Ever since Hippocrates founded his school of medicine in ancient Greece some 2,500 years ago, writes Hannah Fry in her book Hello World: Being Human in the Age of Algorithms , what has been fundamental to healthcare (as she calls it “the fight to keep us healthy”) was observation, experimentation and the analysis of data.

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Themes and Conferences per Pacoid, Episode 9

Domino Data Lab

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Introduction. 2018-06-21).