Towards AI

AUGUST 16, 2023

Pietro Jeng on Unsplash MLOps is a set of methods and techniques to deploy and maintain machine learning (ML) models in production reliably and efficiently. Thus, MLOps is the intersection of Machine Learning, DevOps, and Data Engineering (Figure 1). Background Saying that MLOps is in a state of flux would be an understatement [7].

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DevOps Machine Learning Software Development ML 92

Unite.AI

SEPTEMBER 4, 2024

The Claude Enterprise Plan is an advanced offering that allows organizations to securely integrate AI capabilities into their workflows using internal knowledge. This plan is built on the foundation of Claude, Anthropic's sophisticated AI model, but with enhanced features tailored for enterprise use.

DevOps 147

DevOps Large Language Models Automation Software Development 147

Flipboard

NOVEMBER 24, 2023

Moreover, the JuMa infrastructure, which is based on AWS serverless and managed services, helps reduce operational overhead for DevOps teams and allows them to focus on enabling use cases and accelerating AI innovation at BMW Group. Marinus Krommenhoek is a Senior Cloud Solution Architect and a Software Developer at BMW Group.

ML 154

ML DevOps Data Scientist ML Engineer 154

Chatbots Life

MAY 16, 2023

Generative AI integration service: proposes “Embedded Generative AI” integration methodology to build Generative AI features into a client’s existing Conversational AI platform without creating a chatbot from scratch. 10Clouds is a software consultancy, development, ML, and design house based in Warsaw, Poland.

Generative AI 98

Generative AI Chatbots Conversational AI Software Development 98

Unite.AI

JANUARY 25, 2024

Prompt engineering revolves around the art and science of crafting effective prompts to elicit desired responses from AI models, especially large language models like GPT. This surge in interest underscores the growing recognition of the nuanced skill required to interact efficiently with advanced AI systems.

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Prompt Engineering Prompt Engineer NLP Generative AI 182

AWS Machine Learning Blog

AUGUST 22, 2024

Building a deployment pipeline for generative artificial intelligence (AI) applications at scale is a formidable challenge because of the complexities and unique requirements of these systems. Generative AI models are constantly evolving, with new versions and updates released frequently.

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Generative AI Metadata Python ML 119

AWS Machine Learning Blog

NOVEMBER 19, 2024

The technical sessions covering generative AI are divided into six areas: First, we’ll spotlight Amazon Q , the generative AI-powered assistant transforming software development and enterprise data utilization.

ML 85

ML Generative AI AI AI 85

AWS Machine Learning Blog

FEBRUARY 1, 2024

She has a diverse background, having worked in many technical disciplines, including software development, agile leadership, and DevOps, and is an advocate for women in tech. The following are some considerations when using RAG: Setting appropriate timeouts is important to the customer experience.

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Generative AI Prompt Engineer Prompt Engineering AI 133

AWS Machine Learning Blog

JULY 18, 2024

These advanced generative AI models are great at understanding and analyzing vast amounts of text, making them the perfect tool for sifting through the flood of CVE reports to pinpoint those containing attack requirement details. About the Authors Hemmy Yona is a Solutions Architect at Amazon Web Services based in Israel.

Generative AI 116

Generative AI Automation Categorization Software Architect 116

AWS Machine Learning Blog

NOVEMBER 21, 2023

Amazon Music uses the power of AI to accomplish this. However, optimizing the customer experience while managing cost of training and inference of AI models that power the search bar’s capabilities, like real-time spellcheck and vector search, is difficult during peak traffic times.

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ML Deep Learning Machine Learning DevOps 106

Viso.ai

MARCH 1, 2023

The value proposition of disruptive low-code AI technology gives companies the flexibility and agility to adapt to the fast-changing industry reality while accelerating the time-to-market of new applications to keep up with or change markets. The transformative potential of low-code AI development is evident.

Computer Vision 52

Computer Vision Software Development AI AI 52

Viso.ai

MARCH 29, 2024

MLflow is an open-source platform designed to manage the entire machine learning lifecycle, making it easier for ML Engineers, Data Scientists, Software Developers, and everyone involved in the process. MLflow can be seen as a tool that fits within the MLOps (synonymous with DevOps) framework.

Machine Learning 52

Machine Learning ML Automation Data Scientist 52

AWS Machine Learning Blog

JUNE 11, 2024

At AWS, he helps customers unlock business value through generative AI, assisting with the overall process from ideation to production. Ziwen Ning is a software development engineer at AWS. He currently focuses on enhancing the AI/ML experience through the integration of AWS Neuron with containerized environments and Kubernetes.

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Deep Learning ML Automation Auto-complete 120

Marktechpost

JULY 17, 2023

The advantages of using synthetic data include easing restrictions when using private or controlled data, adjusting the data requirements to specific circumstances that cannot be met with accurate data, and producing datasets for DevOps teams to use for software testing and quality assurance. How Important Is Synthetic Data?

Machine Learning 52

Machine Learning Data Scientist Computer Vision Deep Learning 52

AWS Machine Learning Blog

NOVEMBER 7, 2023

About The Authors Jin Tan Ruan is a Prototyping Developer within the AWS Industries Prototyping and Customer Engineering (PACE) team, specializing in NLP and generative AI. He is passionate about a range of topics, including cloud security, DevOps, and AI/ML, and can be usually found tinkering with these technologies.

Large Language Models 118

Large Language Models Generative AI LLM AI 118

AWS Machine Learning Blog

OCTOBER 30, 2024

Intelligent processing – A Lambda function, powered by generative AI models through Amazon Bedrock, analyzes and summarizes the transcribed text. Praveen Kumar Jeyarajan is a Principal DevOps Consultant at AWS, supporting Enterprise customers and their journey to the cloud. He holds a Masters degree in Software Engineering.

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DevOps Generative AI Software Engineer Software Development 96

IBM Journey to AI blog

MARCH 6, 2024

Software development is one arena where we are already seeing significant impacts from generative AI tools. A McKinsey study claims that software developers can complete coding tasks up to twice as fast with generative AI. A burned-out developer is usually an unproductive one.

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Generative AI DevOps Software Development Auto-complete 335

AWS Machine Learning Blog

AUGUST 29, 2024

Companies like Amgen , A-Alpha Bio , Agilent , and Hippocratic AI are among those using NVIDIA AI on AWS to accelerate computational biology, genomics analysis, and conversational AI. Qing Lan is a Software Development Engineer in AWS. Solution overview Getting started with NIM is straightforward.

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Generative AI Machine Learning Deep Learning AI 84

The MLOps Blog

MARCH 21, 2023

Version control for code is common in software development, and the problem is mostly solved. However, machine learning needs more because so many things can change, from the data to the code to the model parameters and other metadata. . My Story DevOps Engineers Who they are?

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Machine Learning Data Scientist ML Metadata 69