Remove AI Modeling Remove Data Analysis Remove Data Quality
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Optimizing Company Workflows with AI Agents: Myth or Reality?

Unite.AI

While AI can excel at certain tasks — like data analysis and process automation — many organizations encounter difficulties when trying to apply these tools to their unique workflows. Lexalytics’s article greatly highlights what happens when you integrate AI just to jump on the AI hype train.

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Microsoft Research Introduces AgentInstruct: A Multi-Agent Workflow Framework for Enhancing Synthetic Data Quality and Diversity in AI Model Training

Marktechpost

Large language models (LLMs) have been instrumental in various applications, such as chatbots, content creation, and data analysis, due to their capability to process vast amounts of textual data efficiently. In conclusion, AgentInstruct represents a breakthrough in generating synthetic data for AI training.

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The Path from RPA to Autonomous Agents

Unite.AI

While traditional AI tools might excel at specific tasks or data analysis, AI agents can integrate multiple capabilities to navigate complex, dynamic environments and solve multifaceted problems. Regularly involve business stakeholders in the AI assessment/selection process to ensure alignment and provide clear ROI.

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Inna Tokarev Sela, CEO and Founder of illumex – Interview Series

Unite.AI

While RAG attempts to customize off-the-shelf AI models by feeding them organizational data and logic, it faces several limitations. It's a black box – you can't determine if you've provided enough examples for proper customization or how model updates affect accuracy.

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Sarah Assous, Vice President of Product Marketing, Akeneo – Interview Series

Unite.AI

AI relies on high-quality, structured data to generate meaningful insights, but many businesses struggle with fragmented or incomplete product information. Akeneos Product Cloud solution has PIM, syndication, and supplier data manager capabilities, which allows retailers to have all their product data in one spot.

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AI and Automation Transforming Quality Engineering: Insights from the 2024 World Quality Report

Unite.AI

A staggering 71% of organizations have integrated AI and Gen AI into their operations, up from 34% in previous years. This shift marks a pivotal moment in the industry, with AI set to revolutionize various aspects of QE, from test automation to data quality management.

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How to build a successful AI strategy

IBM Journey to AI blog

Without an AI strategy, organizations risk missing out on the benefits AI can offer. An AI strategy helps organizations address the complex challenges associated with AI implementation and define its objectives. Commit to ethical AI initiatives, inclusive governance models and actionable guidelines.