IBM Journey to AI blog

JANUARY 10, 2024

.¹ That means businesses should expect dependency on AI technologies to increase, with the complexity of enterprise IT systems increasing in kind. But with the IBM watsonx™ AI and data platform , organizations have a powerful tool in their toolbox for scaling AI.

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IBM Journey to AI blog

DECEMBER 14, 2023

IBM introduced watsonx as the AI and data platform built for business. And just this month, IBM and Meta, together with over 50 founding members and collaborators, launched the AI Alliance. Its goal is to advance open, safe and responsible AI. Quite fascinating.

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Automation Large Language Models Software Development Data Platform 210

Marktechpost

MARCH 12, 2024

Croissant adds extensive layers for data resources, default ML semantics, metadata, and data management to make it even more ML-relevant. From the beginning, the primary objective of the Croissant initiative was to promote Responsible AI (RAI). Dataset writers also prioritize their datasets’ discoverability and use.

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Metadata Machine Learning ML Data Discovery 120

IBM Journey to AI blog

JUNE 23, 2023

AI analyzes financial statements, notes, disclosures and other and applicable data, then translates and interprets the data to provide context-rich answers to your questions. We can help you build a strategic roadmap for transformation, so generative AI can deliver immense business value and improve operational efficiency.

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Generative AI AI AI Data Analysis 189

AWS Machine Learning Blog

JULY 29, 2024

In this post, we show how native integrations between Salesforce and Amazon Web Services (AWS) enable you to Bring Your Own Large Language Models (BYO LLMs) from your AWS account to power generative artificial intelligence (AI) applications in Salesforce.

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Unite.AI

OCTOBER 23, 2024

I think we’ll see marketers shift from expecting (and using) GenAI to improve efficiency and productivity, to also ensuring AI tools deliver measurable increased performance. Establishing AI governance and standards will also become more important as companies expand AI use cases with an eye on responsible AI.

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AWS Machine Learning Blog

AUGUST 4, 2023

As a result, businesses can accelerate time to market while maintaining data integrity and security, and reduce the operational burden of moving data from one location to another. With Einstein Studio, a gateway to AI tools on the data platform, admins and data scientists can effortlessly create models with a few clicks or using code.

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IBM Journey to AI blog

AUGUST 3, 2023

Watsonx amplifies the impact of AI throughout HR workflows, while ensuring responsible AI use to meet the highest ethical, privacy and regulatory requirements. While watsonx started rolling out in July, it has already transformed the fan experience for IBM clients including the Masters and Wimbledon.

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AWS Machine Learning Blog

MARCH 5, 2025

By following these guidelines, organizations can follow responsible AI best practices for creating high-quality ground truth datasets for deterministic evaluation of question-answering assistants. Rahul Jani is a Data Architect with AWS Professional Service.

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John Snow Labs

JANUARY 14, 2025

This is the result of a concentrated effort to deeply integrate its technology across a range of cloud and data platforms, making it easier for customers to adopt and leverage its technology in a private, safe, and scalable way. The curated Models Hub crossed 100,000 models, of which 63% are now LLMs.

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Large Language Models NLP Natural Language Processing LLM 40

Pickl AI

JUNE 23, 2023

This includes ensuring data privacy, security, and compliance with ethical guidelines to avoid biases, discrimination, or misuse of data. Also Read: How Can The Adoption of a Data Platform Simplify Data Governance For An Organization?

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Continuous Learning Data Quality AI AI 52

ODSC - Open Data Science

JULY 19, 2023

Data Estate: This element represents the organizational data estate, potential data sources, and targets for a data science project. Data Engineers would be the primary owners of this element of the MLOps v2 lifecycle. The Azure data platforms in this diagram are neither exhaustive nor prescriptive.

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Machine Learning Data Drift Data Science Data Scientist 52

AWS Machine Learning Blog

SEPTEMBER 6, 2024

From internal knowledge bases for customer support to external conversational AI assistants, these applications use LLMs to provide human-like responses to natural language queries. Rahul Jani is a Data Architect with AWS Professional Services.

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IBM Journey to AI blog

JULY 27, 2023

Precisely conducted a study that found that within enterprises, data scientists spend 80% of their time cleaning, integrating and preparing data , dealing with many formats, including documents, images, and videos. Overall placing emphasis on establishing a trusted and integrated data platform for AI.

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ODSC - Open Data Science

MARCH 18, 2025

Since 2022, she has been driving digital transformation, designing cloud architectures, and developing cutting-edge data platforms incorporating IoT, real-time analytics, machine learning, and generative AI. It will demonstrate model creation, model tuning, model evaluation, and model interpretation.

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Data Science Machine Learning Software Engineer Data Scientist 64

IBM Journey to AI blog

MARCH 13, 2024

Our solutions are designed to address complexity at every level: from data to governance to scaling. IBM believes that scaling AI with governance is the path to sustainable, ethically responsible AI —boosting customer trust and corporate reputation.

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AWS Machine Learning Blog

SEPTEMBER 12, 2024

We all need to be able to unlock generative AI’s full potential while mitigating its risks. It should be easy to implement safeguards for your generative AI applications, customized to your requirements and responsible AI policies. Guardrails can help block specific words or topics.

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The MLOps Blog

MARCH 21, 2023

They work with other users to make sure the data reflects the business problem, the experimentation process is good enough for the business, and the results reflect what would be valuable to the business. Responsible AI and explainability. What do they want to accomplish? Model serving. Monitoring and observability.

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Machine Learning Data Scientist ML Metadata 69

Bugra Akyildiz

FEBRUARY 24, 2024

Responsible AI Development: Phi-2 highlights the importance of considering responsible development practices when building large language models. Increased Democratization: Smaller models like Phi-2 reduce barriers to entry, allowing more developers and researchers to explore the power of large language models.

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NVIDIA

JANUARY 7, 2025

Its a critical component of agentic AI , as it serves as a bridge between an organizations knowledge base and AI-powered applications, enabling more accurate, context-aware responses. AI agents form the basis of an AI query engine, where they can gather information and do work to assist human employees.

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Flipboard

NOVEMBER 27, 2024

To demonstrate, we create a generative AI-enabled Slack assistant with an integration to Amazon Bedrock Knowledge Bases that can expose the combined knowledge of the AWS Well-Architected Framework while implementing safeguards and responsible AI using Amazon Bedrock Guardrails.

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Generative AI Data Ingestion AI AI 142

Unite.AI

NOVEMBER 6, 2024

He is a distinguished authority in the intersection of artificial intelligence (AI) and human-computer interaction (HCI), and an advocate for responsible AI. Pienso ‘s interactive learning interface is designed to enable users to harness AI to its fullest potential without any coding.

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