AWS Machine Learning Blog

JULY 11, 2024

Agents for Amazon Bedrock automates the prompt engineering and orchestration of user-requested tasks. After being configured, an agent builds the prompt and augments it with your company-specific information to provide responses back to the user in natural language. He holds an MS degree in Computer Science.

Data Ingestion 135

Data Ingestion DevOps Prompt Engineer Prompt Engineering 135

Unite.AI

OCTOBER 16, 2023

Prompt Engineering : Engineering precise prompts is vital to elicit accurate and reliable responses from LLMs, mitigating risks like model hallucination and prompt hacking. While seemingly a variant of MLOps or DevOps, LLMOps has unique nuances catering to large language models' demands.

Large Language Models 189

Large Language Models LLM Machine Learning Neural Network 189

TransOrg Analytics

MARCH 17, 2025

Enhancing Digital Transformation Capabilities: As global innovation accelerates, TransOrg Analytics is e expanding its digital consulting and transformation services to help enterprises navigate cloud adoption, cybersecurity challenges, and the complexities of DevOps, LLMOps, and MLOps.

Machine Learning 52

Machine Learning Data Science DevOps Prompt Engineer 52

AWS Machine Learning Blog

SEPTEMBER 1, 2023

Strong domain knowledge for tuning, including prompt engineering, is required as well. Consumers – Users who interact with generative AI services from providers or fine-tuners by text prompting or a visual interface to complete desired actions. Only prompt engineering is necessary for better results.

Generative AI 127

Generative AI Prompt Engineer Prompt Engineering ML 127

AWS Machine Learning Blog

FEBRUARY 1, 2024

Make sure to validate prompt input data and prompt input size for allocated character limits that are defined by your model. If you’re performing prompt engineering, you should persist your prompts to a reliable data store.

Generative AI 136

Generative AI Prompt Engineer Prompt Engineering AI 136

AWS Machine Learning Blog

AUGUST 26, 2024

DevOps From a DevOps perspective, the frontend uses Amplify to build and deploy, and the backend is uses AWS Serverless Application Model (AWS SAM) to build, package, and deploy the serverless applications. We use the few-shot prompting technique by providing a few examples to produce an accurate ASL gloss.

Generative AI 122

Generative AI DevOps AI AI 122

AWS Machine Learning Blog

MAY 1, 2024

It allows you to retrieve data from sources beyond the foundation model, enhancing prompts by integrating contextually relevant retrieved data. You can use prompt engineering to prevent hallucination and make sure that the answer is grounded in the source documentations. He holds a Masters degree in Software Engineering.

Chatbots 129

Chatbots Automation Machine Learning DevOps 129

AWS Machine Learning Blog

OCTOBER 8, 2024

Prompt design for agent orchestration Now, let’s take a look at how we give our digital assistant, Penny, the capability to handle onboarding for financial services. The key is the prompt engineering for the custom LangChain agent. Prompt design is key to unlocking the versatility of LLMs for real-world automation.

Automation 115

Automation Prompt Engineer Prompt Engineering Machine Learning 115

AWS Machine Learning Blog

NOVEMBER 17, 2023

Components in agents for Amazon Bedrock Behind the scenes, agents for Amazon Bedrock automate the prompt engineering and orchestration of user-requested tasks. They can securely augment the prompts with company-specific information to provide responses back to the user in natural language.

DevOps 114

DevOps Prompt Engineer Prompt Engineering Automation 114

AWS Machine Learning Blog

FEBRUARY 25, 2025

By using the capabilities of Amazon Bedrock Agents, it offers a scalable and intelligent approach to managing IaC challenges in large, multi-account AWS environments.

Generative AI 65

Generative AI Prompt Engineer Prompt Engineering AI 65

AWS Machine Learning Blog

NOVEMBER 19, 2024

These sessions, featuring Amazon Q Business , Amazon Q Developer , Amazon Q in QuickSight , and Amazon Q Connect , span the AI/ML, DevOps and Developer Productivity, Analytics, and Business Applications topics. In this session, learn best practices for effectively adopting generative AI in your organization.

ML 97

ML Generative AI AI AI 97

ODSC - Open Data Science

DECEMBER 1, 2023

How to protect your main branch and how to trigger tasks in the machine learning workflow How to automate code checks whenever you update code How to train, test, and deploy a machine learning model by using environments How to automate and test model deployment with GitHub Actions and the Azure Machine Learning CLI (v2) Introduction to Machine Learning (..)

Data Science 52

Data Science Machine Learning DevOps Large Language Models 52

Heartbeat

MARCH 19, 2024

Like machine learning operations, LLMOps involves efforts from several contributors, like prompt engineers, data scientists, DevOps engineers, business analysts, and IT operations. This is, in fact, a baseline, and the actual LLMOps workflow usually involves more stakeholders like prompt engineers, researchers, etc.

Large Language Models 52

Large Language Models Prompt Engineering Prompt Engineer Natural Language Processing 52

Heartbeat

OCTOBER 5, 2023

MLOps, often seen as a subset of DevOps (Development Operations), focuses on streamlining the development and deployment of machine learning models. Where is LLMOps in DevOps and MLOps In MLOps, engineers are dedicated to enhancing the efficiency and impact of ML model deployment.

Large Language Models 52

Large Language Models DevOps Machine Learning Prompt Engineer 52

Mlearning.ai

JUNE 16, 2023

Game changer ChatGPT in Software Engineering: A Glimpse Into the Future | HackerNoon Generative AI for DevOps: A Practical View - DZone ChatGPT for DevOps: Best Practices, Use Cases, and Warnings. GPT-4 Data Pipelines: Transform JSON to SQL Schema Instantly Blockstream’s public Bitcoin API.

Software Development 52

Software Development Generative AI ChatGPT Prompt Engineer 52

The MLOps Blog

JUNE 5, 2023

How do you have a similar tool for experimentation on prompts? Keep track of versions of prompts and what worked and all that. Why do we have MLOps as opposed to DevOps? Stephen : I just wanted to touch on the experimentation part of I know developers are already taking notes, A lot of prompt engineering is happening.

Large Language Models 52

Large Language Models Machine Learning Software Engineer Natural Language Processing 52

The MLOps Blog

JUNE 27, 2023

The platform also offers features for hyperparameter optimization, automating model training workflows, model management, prompt engineering, and no-code ML app development. MLOps tools and platforms FAQ What devops tools are used in machine learning in 20233?

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

The MLOps Blog

AUGUST 3, 2023

We have someone from Adobe using it to help manage some prompt engineering work that they’re doing, for example. We have someone precisely using it more for feature engineering, but using it within a Flask app. The data scientists are here with software engineers. ML platform team can be for this DevOps team.

ML 52

ML Data Scientist Software Engineer Machine Learning 52

AWS Machine Learning Blog

NOVEMBER 29, 2023

After the selection of the model(s), prompt engineers are responsible for preparing the necessary input data and expected output for evaluation (e.g. input prompts comprising input data and query) and define metrics like similarity and toxicity.

LLM 111

LLM Data Scientist Algorithm Generative AI 111

AWS Machine Learning Blog

NOVEMBER 27, 2024

Architecture Diagram Prerequisites To implement the solution, you need the following: Understanding of Amazon Bedrock Agents, prompt engineering , Amazon Bedrock Knowledge Bases , Lambda functions, and AWS Identity and Access Management (IAM).

Generative AI 106

Generative AI Automation DevOps Prompt Engineer 106

Flipboard

JANUARY 7, 2025

Elias has experience in migration delivery, DevOps engineering and cloud infrastructure. Marcin Czelej is a Machine Learning Engineer at AWS Generative AI Innovation and Delivery. He is a technical and business program manager helping customers be successful on AWS.

IDP 140

IDP Machine Learning Generative AI LLM 140

O'Reilly Media

NOVEMBER 26, 2024

Examples of these skills are artificial intelligence (prompt engineering, GPT, and PyTorch), cloud (Amazon EC2, AWS Lambda, and Microsoft’s Azure AZ-900 certification), Rust, and MLOps. A higher completion rate could indicate that the course teaches an emerging skill that is required in industry.

Machine Learning 110

Machine Learning Software Engineer Python Software Architect 110