Artificial Intelligence

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artificial intelligence / machine learning / network

Boosting AI’s smarts in the absence of training data

Zero-shot learning repurposes knowledge through statistical or semantic approaches without needing huge amounts of fresh training data

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How to future-proof your IT career in the age of AI

Worried that artificial intelligence will eliminate tech jobs -- your job specifically? Here’s what you should and shouldn’t focus on in a world of AI.

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Use Azure Cognitive Services to automate forms processing

Form Recognizer brings unsupervised machine learning to paper document processing, and it’s a snap to build into your applications

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Only AI can save us from a world of fakes (a world AI is also creating)

Deepfake video and audio. AI-generated texts, poetry and lyrics. Fake sites. Fake influencers. Fake news. Will life ever be real again?

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Can you put your trust in AIops?

As ops tools morph into AIops, they bring greater value to more complex deployments—if users will let them

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A brief history of artificial intelligence

Despite huge advances in machine learning models, AI challenges remain much the same today as 60 years ago

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Microsoft speeds up PyTorch with DeepSpeed

A new open source project from Microsoft accelerates PyTorch machine learning without major code rewrites

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How to deploy RPA successfully

IT professionals with hands-on robotic process automation experience discuss the key factors contributing to a successful RPA deployment.

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Keeping your enterprise AI expertise up to speed

AI is such a significant force, you can’t afford not to stay on top of the ever-changing developments

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How AI will improve API security

By using AI models to continuously inspect all API activity, we can fill in the cracks left by policy-based API protections

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8 misleading AI myths — and the realities behind them

With all of the hype around AI and machine learning come many factual inaccuracies. Let’s separate the truth from the fiction

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Cloud AI is like nuclear power

With incredible potential for both good and harm, AI needs worldwide regulation to ensure it isn't misused

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2 cloud and AI myths you shouldn’t believe

If you think the cloud will drive data centers to extinction and that AI projects are doomed to fail, think again

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How to keep bias out of your AI models

AI models are empty, neutral machines. They will acquire a bias when trained with biased data

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Making AI’s arcane neural networks accessible

Data scientists remain in hot demand, but they will give up more of their core functions this year and beyond to automated tools

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Is AI judging your personality?

Forget ‘surveillance capitalism.’ AI-based social media monitoring could cost you a job, college admission, rental property and more – and you’ll never know how it happened.

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Deep learning vs. machine learning: Understand the differences

Both machine learning and deep learning discover patterns in data, but they involve dramatically different techniques

succession brain sharing intellectual knowledge sharing

Deep learning vs. machine learning: Understand the differences

Both machine learning and deep learning discover patterns in data, but involve dramatically different techniques

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Mitigating the risks of the AI black box

If we don’t understand how machine learning works, how can we trust it? Increasing model transparency creates risks as well as rewards

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Wanted: More types of machine learning

Now that we’re big into machine learning in the cloud, perhaps we should start thinking about how to do it better

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