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Trustworthy AI explained with 12 principles and a framework
To be considered trustworthy, AI systems should meet these 12 principles and employ a four-step framework to ensure the use of AI is ethical, lawful and robust.
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What businesses should know about OpenAI's GPT-4o model
Enterprise use cases are driving the need for faster AI response times, better data handling and cost optimization. OpenAI attempts to meet that need with GPT-4o.
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What business leaders should know about EU AI Act compliance
AI compliance expert Arnoud Engelfriet shares key takeaways from his book 'AI and Algorithms,' describing the EU AI Act's effects on innovation, risk management and ethical AI.
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How can AI drive revenue? Here are 10 approaches
Artificial intelligence has captured the imagination of many a boardroom. Now, the emphasis has shifted to capturing revenue through AI-driven use cases.
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AI Infrastructure News
Cerebras' inference AI tool challenges Nvidia, but faces hurdles
The hardware vendor says its new inference offering outperforms Nvidia's GPU-based tools. However, Nvidia dominates the market.
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AI Technologies News
iPhone 16 built around Apple Intelligence AI features
The consumer electronics giant introduced a new generation of iPhones with generative AI features such as writing tools, summarization and better Siri.
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AI Platforms News
Nvidia launches NIM Agent Blueprints to speed AI use
Nvidia introduced new microservice that helps enterprise developers deploy GenAI applications. It also introduced three Blueprints for different use cases.
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ML Platforms Get Started
How do big data and AI work together?
Enterprises are leaning on big data to train AI algorithms and, in turn, are using AI to understand big data. The results are pushing business operations forward.
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AI Business Strategies Get Started
Trustworthy AI explained with 12 principles and a framework
To be considered trustworthy, AI systems should meet these 12 principles and employ a four-step framework to ensure the use of AI is ethical, lawful and robust.
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Applications of AI Evaluate
Will AI replace technical writers? One user's experience
As with many jobs, how AI advancements will affect the future of technical writing is up for debate. Hear from one expert on why AI is here to stay -- but so are technical writers.
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What businesses should know about OpenAI's GPT-4o model
Enterprise use cases are driving the need for faster AI response times, better data handling and cost optimization. OpenAI attempts to meet that need with GPT-4o.
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How to choose the best GPUs for AI projects
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Democratization of AI creates benefits and challenges
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10 top AI and machine learning trends for 2024
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Problem Solve
6 ways to reduce different types of bias in machine learning
As adoption of machine learning grows, companies must become data experts or risk results that are inaccurate, unfair or even dangerous. Here's how to combat machine learning bias.
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A short guide to managing generative AI hallucinations
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What companies are getting wrong about AI
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Best practices for getting started with MLOps
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Manage
What business leaders should know about EU AI Act compliance
AI compliance expert Arnoud Engelfriet shares key takeaways from his book 'AI and Algorithms,' describing the EU AI Act's effects on innovation, risk management and ethical AI.
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How can AI drive revenue? Here are 10 approaches
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AI model optimization: How to do it and why it matters
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AI regulation: What businesses need to know in 2024
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E-Handbook | August 2020
Machine learning and bias concerns weigh on data scientists
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E-Handbook | November 2019
Data visualization process yields 360 AI-driven analytics view
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E-Handbook | October 2019
Neural network applications in business run wide, fast and deep
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E-Handbook | July 2019
Machine learning platform architecture demands deep analysis
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Buyer's Handbook | June 2019
Pinpoint the right RPA products to advance your organization
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Enterprise Artificial Intelligence Basics
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Trustworthy AI explained with 12 principles and a framework
To be considered trustworthy, AI systems should meet these 12 principles and employ a four-step framework to ensure the use of AI is ethical, lawful and robust.
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Get Started
What is machine learning bias (AI bias)?
Machine learning bias, also known as 'algorithm bias' or 'AI bias,' is a phenomenon that occurs when an algorithm produces results that are systemically prejudiced due to erroneous assumptions in the machine learning (ML) process.
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What businesses should know about OpenAI's GPT-4o model
Enterprise use cases are driving the need for faster AI response times, better data handling and cost optimization. OpenAI attempts to meet that need with GPT-4o.
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AI business strategies
Former OpenAI scientist raises $1B for AI safety venture
Ilya Sutskever's new company is focused on providing safe artificial general intelligence. While some see a need for it, others find it distracting.
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AI technologies
Copilot+ PCs with AMD and Intel silicon show AI PC trends
The tech giant introduced computers with chips from Intel and AMD. The new machines come amid a refresh cycle for organizations and employees and open prospects for local AI apps.
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AI technologies
IBM's latest Z mainframe offers lessons in building AI systems
Studying the engineering behind IBM's mainframe architecture could help enterprises build higher reliability into the GPU clusters used to run AI applications.
Enterprise AI Definitions
- What is machine learning bias (AI bias)?
- What is singularity in technology and AI?
- What is the Turing Test?
- What is an intelligent agent?
- What is AI (Artificial Intelligence)?
- What is natural language processing (NLP)?
- What is narrow AI (weak AI)?
- What is natural language generation (NLG)?