Information, ML Engineer and Responsible AI - Artificial Intelligence Zone

Track LLM model evaluation using Amazon SageMaker managed MLflow and FMEval

AWS Machine Learning Blog

JANUARY 28, 2025

Regular interval evaluation also allows organizations to stay informed about the latest advancements, making informed decisions about upgrading or switching models. By investing in robust evaluation practices, companies can maximize the benefits of LLMs while maintaining responsible AI implementation and minimizing potential drawbacks.

LLM

LLM Large Language Models ML Algorithm

Top Artificial Intelligence AI Courses from Google

Marktechpost

MAY 30, 2024

Introduction to AI and Machine Learning on Google Cloud This course introduces Google Cloud’s AI and ML offerings for predictive and generative projects, covering technologies, products, and tools across the data-to-AI lifecycle. It includes labs on feature engineering with BigQuery ML, Keras, and TensorFlow.

Artificial Intelligence

Artificial Intelligence Artificial Intelligence BERT Computer Vision

From concept to reality: Navigating the Journey of RAG from proof of concept to production

AWS Machine Learning Blog

FEBRUARY 12, 2025

Machine learning (ML) engineers must make trade-offs and prioritize the most important factors for their specific use case and business requirements. You can use advanced parsing options supported by Amazon Bedrock Knowledge Bases for parsing non-textual information from documents using FMs.

Auto-classification

Auto-classification Metadata Generative AI Machine Learning

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Learn how to assess the risk of AI systems

Flipboard

NOVEMBER 28, 2023

The following figure is a good starting point to map out AI stakeholder roles. Source: “Information technology – Artificial intelligence – Artificial intelligence concepts and terminology”. An important next step of the AI system risk assessment is to identify potentially harmful events associated with the use case.

Artificial Intelligence

Artificial Intelligence Artificial Intelligence Responsible AI Machine Learning

Accelerating ML experimentation with enhanced security: AWS PrivateLink support for Amazon SageMaker with MLflow

AWS Machine Learning Blog

DECEMBER 9, 2024

MLflow , a popular open-source tool, helps data scientists organize, track, and analyze ML and generative AI experiments, making it easier to reproduce and compare results. Amazon SageMaker with MLflow is a capability in SageMaker that enables users to create, manage, analyze, and compare their ML experiments seamlessly.

ML

ML Data Scientist Machine Learning Software Engineer

Best practices for Amazon SageMaker HyperPod task governance

AWS Machine Learning Blog

FEBRUARY 19, 2025

These graphs inform administrators where teams can further maximize their GPU utilization. In this example, the ML engineering team is borrowing 5 GPUs for their training task With SageMaker HyperPod, you can additionally set up observability tools of your choice.

Data Scientist

Data Scientist Data Science ML Engineer Generative AI

Map Earth’s vegetation in under 20 minutes with Amazon SageMaker

AWS Machine Learning Blog

OCTOBER 16, 2024

Amazon SageMaker supports geospatial machine learning (ML) capabilities, allowing data scientists and ML engineers to build, train, and deploy ML models using geospatial data. This example of vegetation mapping is just the beginning for running planetary-scale ML. He is an ACM Fellow and IEEE Fellow.

Machine Learning

Machine Learning ML Data Scientist Robotics

Deploy a Slack gateway for Amazon Bedrock

AWS Machine Learning Blog

JUNE 19, 2024

On the app details page, choose Basic Information in the navigation pane. On the Basic Information page, Bots and Permissions should now both have a green check mark. For more information about requesting model access, see Model access. After you create the app, you can configure its permissions. j2-ultra-v1 (Jurassic-2 Ultra).For

ML Engineer

ML Engineer Generative AI Big Data ML

The journey of PGA TOUR’s generative AI virtual assistant, from concept to development to prototype

AWS Machine Learning Blog

MARCH 14, 2024

Generative artificial intelligence (generative AI) has enabled new possibilities for building intelligent systems. Recent improvements in Generative AI based large language models (LLMs) have enabled their use in a variety of applications surrounding information retrieval.

Generative AI

Generative AI LLM AI AI

Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

AWS Machine Learning Blog

OCTOBER 2, 2024

It’s a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like Anthropic, Cohere, Meta, Mistral AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Generative AI

Generative AI Data Ingestion AI AI

Establishing an AI/ML center of excellence

AWS Machine Learning Blog

MAY 9, 2024

Governance Establish governance that enables the organization to scale value delivery from AI/ML initiatives while managing risk, compliance, and security. Additionally, pay special attention to the changing nature of the risk and cost that is associated with the development as well as the scaling of AI.

ML

ML Generative AI AI AI

Evaluate large language models for quality and responsibility

AWS Machine Learning Blog

NOVEMBER 30, 2023

Reports holistically summarize each evaluation in a human-readable way, through natural-language explanations, visualizations, and examples, focusing annotators and data scientists on where to optimize their LLMs and help make informed decisions. What is FMEval? FMEval allows you to upload your own prompt datasets and algorithms.

Large Language Models

Large Language Models Algorithm LLM Responsible AI

Import a fine-tuned Meta Llama 3 model for SQL query generation on Amazon Bedrock

AWS Machine Learning Blog

AUGUST 1, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading artificial intelligence (AI) companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API. This process might take a couple of hours.

Generative AI

Generative AI Machine Learning Artificial Intelligence Artificial Intelligence

Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning Blog

NOVEMBER 14, 2024

Use case and model governance plays a crucial role in implementing responsible AI and helps with the reliability, fairness, compliance, and risk management of ML models across use cases in the organization. It helps prevent biases, manage risks, protect against misuse, and maintain transparency.

ML

ML Machine Learning Auto-complete Auto-classification

Evaluation of generative AI techniques for clinical report summarization

AWS Machine Learning Blog

MAY 13, 2024

This is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading artificial intelligence (AI) companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API. The first of these specifies the information for which the model needs to generate a response.

Generative AI

Generative AI Prompt Engineer Prompt Engineering LLM

Bria 2.3, Bria 2.2 HD, and Bria 2.3 Fast are now available in Amazon SageMaker JumpStart

AWS Machine Learning Blog

OCTOBER 15, 2024

After you choose Subscribe , you’re redirected to the model overview page, where you can read the model details, pricing, usage, and other information. For more information, refer to Requesting a quota increase. About the Authors Bar Fingerman is the Head of AI/ML Engineering at Bria. 24xlarge, and ml.p4de.24xlarge.

Generative AI

Generative AI ML Python Responsible AI

Achieve ~2x speed-up in LLM inference with Medusa-1 on Amazon SageMaker AI

AWS Machine Learning Blog

FEBRUARY 12, 2025

For more information, refer Configure the AWS CLI. The solution uses an ml.g5.4xlarge instance for the SageMaker AI training jobs, and three ml.g5.4xlarge instance are used for the SageMaker AI endpoints. About the authors Daniel Zagyva is a Senior ML Engineer at AWS Professional Services.

LLM

LLM ML Natural Language Processing Machine Learning

MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

JUNE 27, 2023

Can you debug system information? Tools should allow you to easily create, update, compare, and revert dataset versions, enabling efficient management of dataset changes throughout the ML development process. Can you compare images? Can you customize the UI to your needs? Can you find experiments and models easily?

Machine Learning

Machine Learning Metadata Data Scientist Data Quality

How Booking.com modernized its ML experimentation framework with Amazon SageMaker

AWS Machine Learning Blog

FEBRUARY 12, 2024

With this data, Ranking ML scientists can make informed decisions on how to further improve their model performance and account for the challenging prediction results that the model would occasionally provide. AWS Professional Services is ready to help your team develop scalable and production-ready ML in AWS.

ML

ML Explainability Machine Learning Deep Learning

Announcing the First Sessions for ODSC East 2024

ODSC - Open Data Science

JANUARY 10, 2024

In this talk, you’ll explore the need for adopting responsible AI principles when developing and deploying large language models (LLMs) and other generative AI models, and provide a roadmap for thinking about responsible AI for generative AI in practice through real-world LLM use cases.

Large Language Models

Large Language Models Deep Learning Data Science LLM

Where AI is headed in the next 5 years?

Pickl AI

JULY 14, 2023

Even in the time of pandemic, AI has enabled in providing technical solutions to the people in terms of information inflow. Therefore, AI has been evolving since years now and is currently at its peak of development. The average salary of a ML Engineer per annum is $125,087.

Neural Network

Neural Network Software Engineer Artificial Intelligence Artificial Intelligence

Explainable AI (XAI): The Complete Guide (2024)

Viso.ai

FEBRUARY 12, 2024

Compliance and Regulations: Any company using AI for marketing recommendations, financial decisions, etc. For example, it is illegal to use PII (Personal Identifiable Information) such as the address, gender, and age of a customer in AI models. Explainable AI is the pillar for responsible AI development and monitoring.

Explainable AI

Explainable AI Explainability Deep Learning Neural Network

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning Blog

JANUARY 26, 2024

Being aware of risks fosters transparency and trust in generative AI applications, encourages increased observability, helps to meet compliance requirements, and facilitates informed decision-making by leaders.

Generative AI

Generative AI ML LLM AI

Operationalize LLM Evaluation at Scale using Amazon SageMaker Clarify and MLOps services

AWS Machine Learning Blog

NOVEMBER 29, 2023

Their potential applications span from conversational agents to content generation and information retrieval, holding the promise of revolutionizing all industries. However, harnessing this potential while ensuring the responsible and effective use of these models hinges on the critical process of LLM evaluation.

LLM

LLM Data Scientist Algorithm Generative AI

Definite Guide to Building a Machine Learning Platform

The MLOps Blog

MARCH 21, 2023

As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale. In this comprehensive guide, we’ll explore everything you need to know about machine learning platforms, including: Components that make up an ML platform.

Machine Learning

Machine Learning Data Scientist ML Metadata

Enabling production-grade generative AI: New capabilities lower costs, streamline production, and boost security

AWS Machine Learning Blog

SEPTEMBER 12, 2024

As generative AI moves from proofs of concept (POCs) to production, we’re seeing a massive shift in how businesses and consumers interact with data, information—and each other. We all need to be able to unlock generative AI’s full potential while mitigating its risks. Guardrails can help block specific words or topics.

Generative AI

Generative AI AI AI ML

How TUI uses Amazon Bedrock to scale content creation and enhance hotel descriptions in under 10 seconds

AWS Machine Learning Blog

DECEMBER 17, 2024

The TUI content teams are tasked with producing high-quality content for its websites, including product details, hotel information, and travel guides, often using descriptions written by hotel and third-party partners. For more information, refer to Fine-tune Llama 2 for text generation on Amazon SageMaker Jumpstart.

LLM

LLM Prompt Engineer Prompt Engineering Generative AI

Dive deep into vector data stores using Amazon Bedrock Knowledge Bases

AWS Machine Learning Blog

OCTOBER 11, 2024

An LLM-powered agent, which is responsible for orchestrating steps to respond to the request, checks if additional information is needed from knowledge sources. The agent invokes the process to retrieve information from the knowledge source. The agent decides which knowledge source to use.

Metadata

Metadata Generative AI LLM Data Ingestion

A guide to Amazon Bedrock Model Distillation (preview)

AWS Machine Learning Blog

DECEMBER 4, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) along with a broad set of capabilities to build generative AI applications, simplifying development with security, privacy, and responsible AI. Now select your distillation job.

Metadata

Metadata Generative AI Categorization Data Scientist

How MSD uses Amazon Bedrock to translate natural language into SQL for complex healthcare databases

AWS Machine Learning Blog

NOVEMBER 18, 2024

This approach not only saves time but also democratizes data access, allowing even non-technical staff to extract insights quickly, thereby enhancing overall organizational productivity and accelerating informed decision-making. We have a config file that contains the information and paths associated with each database. # Nothing else.

LLM

LLM Generative AI Data Science Data Scientist

Artificial Intelligence Zone

Track LLM model evaluation using Amazon SageMaker managed MLflow and FMEval

Top Artificial Intelligence AI Courses from Google

Webinars

Trending Sources

From concept to reality: Navigating the Journey of RAG from proof of concept to production

Webinars

Learn how to assess the risk of AI systems

Accelerating ML experimentation with enhanced security: AWS PrivateLink support for Amazon SageMaker with MLflow

Best practices for Amazon SageMaker HyperPod task governance

Map Earth’s vegetation in under 20 minutes with Amazon SageMaker

Deploy a Slack gateway for Amazon Bedrock

The journey of PGA TOUR’s generative AI virtual assistant, from concept to development to prototype

Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

Establishing an AI/ML center of excellence

Evaluate large language models for quality and responsibility

Import a fine-tuned Meta Llama 3 model for SQL query generation on Amazon Bedrock

Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

Evaluation of generative AI techniques for clinical report summarization

Bria 2.3, Bria 2.2 HD, and Bria 2.3 Fast are now available in Amazon SageMaker JumpStart

Achieve ~2x speed-up in LLM inference with Medusa-1 on Amazon SageMaker AI

MLOps Landscape in 2023: Top Tools and Platforms

How Booking.com modernized its ML experimentation framework with Amazon SageMaker

Announcing the First Sessions for ODSC East 2024

Where AI is headed in the next 5 years?

Explainable AI (XAI): The Complete Guide (2024)

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

Operationalize LLM Evaluation at Scale using Amazon SageMaker Clarify and MLOps services

Definite Guide to Building a Machine Learning Platform

Enabling production-grade generative AI: New capabilities lower costs, streamline production, and boost security

How TUI uses Amazon Bedrock to scale content creation and enhance hotel descriptions in under 10 seconds

Dive deep into vector data stores using Amazon Bedrock Knowledge Bases

A guide to Amazon Bedrock Model Distillation (preview)

How MSD uses Amazon Bedrock to translate natural language into SQL for complex healthcare databases

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