Artificial Intelligence

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Tech Spotlight   >   Analytics [InfoWorld]   >   An image of an IT leader processing data analytics.

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4 key tests for your AI explainability toolkit

Enterprise-grade explainability solutions provide fundamental transparency into how machine learning models make decisions, as well as broader assessments of model quality and fairness. Is yours up to the job?

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8 ways to jump-start your machine learning

From exploratory data analysis to automated machine learning, look to these techniques to get your data science project moving — and to build better models.

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Ensuring that citizen developers build AI responsibly

'Trust but verify' is good advice, but can we realistically do either with AI?

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Data wrangling and exploratory data analysis explained

Data rarely comes in usable form. Data wrangling and exploratory data analysis are the difference between a good data science model and garbage in, garbage out.

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What we just learned about data science — and what’s next

The past 12 months have revealed how valuable data science can be while also exposing its limitations. Expect big advances in the year to come.

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BlazingSQL review: Fast ETL for GPU-based data science

BlazingSQL builds on RAPIDS to distribute SQL query execution across GPU clusters, delivering the ETL for an all-GPU data science workflow.

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8 great Python libraries for natural language processing

With so many NLP resources in Python, how to choose? Discover the best Python libraries for analyzing text and how to use them.

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Battling bias and other toxicities in natural language generation

Despite numerous and concerted efforts to train NLG systems to generate content without offensive elements, success is still elusive.

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Deno 1.8 preps for GPU-accelerated machine learning

WebGPU API for GPU rendering and computation is supported in the latest upgrade to the JavaScript/TypeScript runtime.

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Does AI-driven cloud computing need ethics guidelines?

It’s clear that artificial intelligence is powerful and cost-effective in the public cloud. However, it can be weaponized for unethical tasks.

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Review: AWS AI and Machine Learning stacks up, and up

Amazon Web Services provides an impressively broad and deep set of machine learning and AI services, rivaling Google Cloud and Microsoft Azure.

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3 kinds of bias in AI models — and how we can address them

A biased AI model must have learned a biased relationship between its inputs and outputs. We can fix that.

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3 ways to get into reinforcement learning

Whether you like theoretical study or want to get your hands dirty, plenty of reinforcement learning resources are out there.

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Swift for TensorFlow project shuts down

Google pulls the plug on effort to integrate the Swift language and TensorFlow machine learning library, while citing multiple achievements.

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8 databases supporting in-database machine learning

While approaches and capabilities differ, all of these databases allow you to build machine learning models right where your data resides.

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Developing a Turing test for ethical AI

AI is ready for a new challenge: Can we train the machine behind the curtain to incorporate humanistic ethics into its processes?

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How to design AI into your applications

3 conscious experience design principles that will help you integrate ‘living’ AI into your applications and how to implement them.

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Use DirectML to add machine learning to C code

Microsoft provides new tools for working with machine learning in GPUs.

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