Generative Data Intelligence

Tag: design patterns

Build a robust text-to-SQL solution generating complex queries, self-correcting, and querying diverse data sources | Amazon Web Services

Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. Today, generative AI can enable people without SQL...

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Simplifying the ‘data product’

Through the continuing evolution of the modern data platform, there is an exciting turn towards new architectural patterns and terms. What started with ‘data...

Building AI Products With A Holistic Mental Model

Note: This article is the first in a series called “Dissecting AI applications”, which introduces a mental model for AI systems. The model serves...

Best practices and design patterns for building machine learning workflows with Amazon SageMaker Pipelines | Amazon Web Services

Amazon SageMaker Pipelines is a fully managed AWS service for building and orchestrating machine learning (ML) workflows. SageMaker Pipelines offers ML application developers the...

New technical deep dive course: Generative AI Foundations on AWS | Amazon Web Services

Generative AI Foundations on AWS is a new technical deep dive course that gives you the conceptual fundamentals, practical advice, and hands-on guidance to...

Efficiently train, tune, and deploy custom ensembles using Amazon SageMaker | Amazon Web Services

Artificial intelligence (AI) has become an important and popular topic in the technology community. As AI has evolved, we have seen different types of...

Ensuring high availability for cloud-based banking applications

It’s tempting to think that a cloud service provider will ensure the high availability of your critical cloud-based banking applications. The problem is that...

A Brief on Ethereum Smart Contract Audit

Read Time: 6 minutes A “smart contract” is a set of instructions that run on Ethereum Blockchain. To audit, an ethereum smart contract means...

Model hosting patterns in Amazon SageMaker, Part 1: Common design patterns for building ML applications on Amazon SageMaker

Machine learning (ML) applications are complex to deploy and often require the ability to hyper-scale, and have ultra-low latency requirements and stringent cost budgets....

Are 100% Security Guarantees Possible?

There is no software without bugs, right? While this is a common sentiment, we make assumptions that rely on the premise that software has...

Adapter Design Pattern in Python

IntroductionThe Adapter Design Pattern is a popular Structural Design Pattern used in software engineering. This guide looks at how we can implement the Adapter...

Exploring Usability Principles of Efficiency and Self-evidency in Product Development

It was in the final semester when I was pursuing my Bachelor’s degree in psychology that I first heard the phrase, ‘User Experience Design’. Having no prior knowledge about the field, I applied for an Read more

The post Exploring Usability Principles of Efficiency and Self-evidency in Product Development appeared first on ixBlog.

Think Big, Start Small, Move Fast: Applying Lessons From The Mayo Clinic to Cybersecurity

I have previously written about how much the Mayo Clinic impacted my life through my experience and time there. In that article I discussed their approach to multi-disciplinary patient triaging and how looking at patients as a whole, rather than a system of discrete systems, helps them to make the right decisions.

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