AWS Machine Learning Blog

JULY 11, 2024

This allows customers to further pre-train selected models using their own proprietary data to tailor model responses to their business context. This allows customers to further pre-train selected models using their own proprietary data to tailor model responses to their business context.

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AWS Machine Learning Blog

NOVEMBER 7, 2024

In this second part, we expand the solution and show to further accelerate innovation by centralizing common Generative AI components. We also dive deeper into access patterns, governance, responsible AI, observability, and common solution designs like Retrieval Augmented Generation. This logic sits in a hybrid search component.

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IBM Journey to AI blog

OCTOBER 12, 2023

But the implementation of AI is only one piece of the puzzle. The tasks behind efficient, responsible AI lifecycle management The continuous application of AI and the ability to benefit from its ongoing use require the persistent management of a dynamic and intricate AI lifecycle—and doing so efficiently and responsibly.

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Pickl AI

FEBRUARY 17, 2025

Summary: Machine Learning’s key features include automation, which reduces human involvement, and scalability, which handles massive data. It uses predictive modelling to forecast future events and adaptiveness to improve with new data, plus generalization to analyse fresh data.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

About the Authors Dheer Toprani is a System Development Engineer within the Amazon Worldwide Returns and ReCommerce Data Services team. He specializes in large language models, cloud infrastructure, and scalable data systems, focusing on building intelligent solutions that enhance automation and data accessibility across Amazons operations.

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The MLOps Blog

JUNE 27, 2023

This includes features for hyperparameter tuning, automated model selection, and visualization of model metrics. Automated pipelining and workflow orchestration: Platforms should provide tools for automated pipelining and workflow orchestration, enabling you to define and manage complex ML pipelines.

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Machine Learning Metadata Data Scientist Data Quality 134

Unite.AI

MAY 6, 2024

They can automate tasks, optimize processes, and empower individuals or small teams to achieve remarkable feats. These assistants adhere to Responsible AI principles, ensuring transparency, accountability, security, and privacy while continuously improving their accuracy and performance through automated evaluation of model output.

Automation 147

Automation Software Engineer Generative AI Software Development 147

John Snow Labs

SEPTEMBER 4, 2023

Proportional Augmentation is based on robustness and bias tests, while Templatic Augmentation is based on templates provided by user input data. Proportional Augmentation can be used to improve data quality by employing various testing methods that modify or generate new data based on a set of training data.

NLP 52

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ODSC - Open Data Science

OCTOBER 25, 2024

Focusing on multiple myeloma (MM) clinical trials, SEETrials showcases the potential of Generative AI to streamline data extraction, enabling timely, precise analysis essential for effective clinical decision-making. Delphina Demo: AI-powered Data Scientist Jeremy Hermann | Co-founder at Delphina | Delphina.Ai

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Data Scientist Software Engineer Automation Machine Learning 52

ODSC - Open Data Science

OCTOBER 16, 2024

The Rise of AI Agents for Automated Workflows: The sessions “ Building an Agentic Rag Application with LangGraph ” and “ LangGraph for AI Agents and RAG ” center around the concept of AI agents, autonomous entities that leverage LLMs and other AI techniques to perform complex tasks and interact with the environment.

LLM 40

LLM Large Language Models Responsible AI Data Quality 40

Pickl AI

JUNE 23, 2023

Data Annotation In many AI applications, data annotation is necessary to label or tag the data with relevant information. Data annotation can be done manually or using automated techniques. This involves analyzing metrics, feedback from users, and validating the accuracy and reliability of the AI models.

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Continuous Learning Data Quality AI AI 52

Pickl AI

APRIL 27, 2023

Data & Analytics leaders must count on these trends to plan future strategies and implement the same to make business operations more effective. For example, how can we maximize business value on the current AI activities? Hence, introducing the concept of responsible AI has become significant. Wrapping it up !!!

Data Science 52

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Pickl AI

AUGUST 1, 2024

These models can identify genetic markers associated with diseases and predict treatment responses, paving the way for more effective and personalised healthcare. Operational Efficiency Deep Learning can optimise healthcare operations by automating administrative tasks, predicting patient flow, and optimising resource allocation.

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ODSC - Open Data Science

JANUARY 30, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI. Think of it as like being a data doctor.

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Data Science Data Scientist Data Mining Machine Learning 52

Viso.ai

DECEMBER 18, 2023

Organizations can easily source data to promote the development, deployment, and scaling of their computer vision applications. Generation With Neural Network Techniques Neural Networks are the most advanced techniques of automated data generation. Neural networks can also synthesize unstructured data like images and video.

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Pickl AI

SEPTEMBER 2, 2024

Content Creation Creating innovative content becomes easier with generative AI. Applications include automated content generation for social media, news articles, and product descriptions. Transparency and accountability AI systems should be transparent, explainable, and accountable to ensure trust and responsible use.

Generative AI 52

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John Snow Labs

OCTOBER 19, 2023

One reason for this bias is the data used to train these models, which often reflects historical gender inequalities present in the text corpus. To address gender bias in AI, it’s crucial to improve the data quality by including diverse perspectives and avoiding the perpetuation of stereotypes.

NLP 52

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IBM Journey to AI blog

JUNE 20, 2024

A robust framework for AI governance The combination of IBM watsonx.governance™ and Amazon SageMaker offers a potent suite of governance, risk management and compliance capabilities that streamline the AI model lifecycle. It automates compliance checks and maintains audit trails, enhancing regulatory adherence.

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Unite.AI

OCTOBER 22, 2024

There are major growth opportunities in both the model builders and companies looking to adopt generative AI into their products and operations. We feel we are just at the beginning of the largest AI wave. Data quality plays a crucial role in AI model development.

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Unite.AI

APRIL 24, 2024

This dataset also includes a significant portion (over 5%) of high-quality non-English data, covering more than 30 languages , in preparation for future multilingual applications. However, Llama 3 is more than just a powerful language model; it's a testament to Meta's commitment to fostering an open and responsible AI ecosystem.

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LLM Large Language Models Data Quality Natural Language Processing 162

AWS Machine Learning Blog

NOVEMBER 14, 2024

It includes processes for monitoring model performance, managing risks, ensuring data quality, and maintaining transparency and accountability throughout the model’s lifecycle. He is focused on AI/ML technology, ML model management, and ML governance to improve overall organizational efficiency and productivity. Madhubalasri B.

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AWS Machine Learning Blog

JANUARY 26, 2024

You can use Amazon Inspector to automate vulnerability discovery and management for Amazon Elastic Compute Cloud (Amazon EC2) instances, containers, AWS Lambda functions, and identify the network reachability of your workloads. Learn more about our commitment to Responsible AI and additional responsible AI resources to help our customers.

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Unite.AI

AUGUST 8, 2024

While single models are suitable in some scenarios, acting as co-pilots, agentic architectures open the door for LLMs to become active components of business process automation. One noteworthy application of LLM-MA systems is call/service center automation. What is an LLM-MA System?

AI Modeling 162

AI Modeling LLM Automation Responsible AI 162

IBM Journey to AI blog

JULY 27, 2023

According to IBM’s Institute of Business Value (IBV) , AI can contain contact center cases, enhancing customer experience by 70%. Additionally, AI can increase productivity in HR by 40% and in application modernization by 30%. One example of this is reducing labor burdens by automating ticket assistance through IT operations.

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Unite.AI

JULY 5, 2024

Robust data management is another critical element. Establishing strong information governance frameworks ensures data quality, security and regulatory compliance. Clinical decision support systems leverage AI to provide healthcare professionals with evidence-based recommendations, alerts, and reminders.

Data Integration 147

Data Integration Data Quality Algorithm AI Modeling 147

Unite.AI

SEPTEMBER 25, 2024

As a result, their first task is distinguishing among different flavors of AI, beginning with precision AI vs. generative AI. Precision AI is the use of machine learning and deep learning models to improve outcomes. It enables enterprises to automate decision-making processes, creating efficiencies and increasing ROI.

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AWS Machine Learning Blog

SEPTEMBER 9, 2024

Generative artificial intelligence (AI) has revolutionized this by allowing users to interact with data through natural language queries, providing instant insights and visualizations without needing technical expertise. This can democratize data access and speed up analysis. powered by Amazon Bedrock Domo.AI

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Software Architect Generative AI AI AI 121

Unite.AI

SEPTEMBER 26, 2024

Edge computing further lowers costs by processing data closer to its source, reducing data transfer expenses and enabling real-time processing for applications like autonomous vehicles and industrial automation. These technological advancements are expanding AI's reach, making it more affordable and accessible.

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AI AI Neural Network Data Quality 147

Unite.AI

JANUARY 23, 2025

In practical terms, this means standardizing data collection, ensuring accessibility, and implementing robust data governance frameworks. Responsible AI Companies that embed responsible AI principles on a robust, well-governed data foundation will be better positioned to scale their applications efficiently and ethically.

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The MLOps Blog

MARCH 21, 2023

It should be able to version the project assets of your data scientists, such as the data, the model parameters, and the metadata that comes out of your workflow. Automation You want the ML models to keep running in a healthy state without the data scientists incurring much overhead in moving them across the different lifecycle phases.

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69

Marktechpost

SEPTEMBER 8, 2024

Training the Model: A Focus on Quality and Compliance The training of EXAONE 3.0 This dataset was carefully curated to include web-crawled data, publicly available resources, and internally constructed corpora. The AI’s ability to identify patterns and trends in large datasets can provide financial institutions with deeper insights.

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ODSC - Open Data Science

SEPTEMBER 20, 2023

Confirmed Extra Events Halloween Data After Dark AI Expo and Demo Hall Virtual Open Spaces Morning Run Day 3: Wednesday, November 1st (Bootcamp, Platinum, Gold, Silver, VIP, Virtual Platinum, Virtual Premium) The third day of ODSC West 2023, will be the second and last day of the Ai X Business and Innovation Summit and the AI Expo and Demo Hall.

Data Science 52

Data Science Large Language Models Machine Learning Python 52

Dlabs.ai

DECEMBER 6, 2022

launched an initiative called ‘ AI 4 Good ‘ to make the world a better place with the help of responsible AI. So if you’re looking for a high-quality, ethical team, they’re a solid choice.

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Artificial Intelligence Artificial Intelligence Computer Vision Machine Learning 52

Snorkel AI

OCTOBER 31, 2023

However, one of the fundamental ways to improve quality and thereby trust and safety for models with billions of parameters is to improve the training data quality. Higher quality curated data is very important to fine-tune these large multi-task models.

Large Language Models 111

Large Language Models AI AI Data Quality 111

Snorkel AI

OCTOBER 31, 2023

However, one of the fundamental ways to improve quality and thereby trust and safety for models with billions of parameters is to improve the training data quality. Higher quality curated data is very important to fine-tune these large multi-task models.

Large Language Models 103

Large Language Models AI AI Data Quality 103

Unite.AI

NOVEMBER 21, 2024

They support us by providing valuable insights, automating tasks and keeping us aligned with our strategic goals. How is Generative AI reshaping traditional IT service models, particularly in industries that have been slower to adopt digital transformation? Just 18 months ago, these services were not the norm.

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DevOps Automation Responsible AI Software Development 147

Snorkel AI

OCTOBER 31, 2023

However, one of the fundamental ways to improve quality and thereby trust and safety for models with billions of parameters is to improve the training data quality. Higher quality curated data is very important to fine-tune these large multi-task models.

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