Artificial Intelligence

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artificial intelligence / machine learning / network

ChatGPT and software development

How can developers use generative AI to write better code, increase productivity, and meet high user expectations?

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Tabnine readies AI-generated unit testing for developers

Forthcoming Tabnine Enterprise feature, now in beta, uses artificial intelligence to generate unit tests for Python, Java, and JavaScript code.

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90% of APAC enterprises plan to deploy AI over the next 12 months: Report

The top three business processes in which APAC enterprises are expected to incorporate AI/ML include IT operations, security, and customer support and service.

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Altostra template creates ChatGPT-like apps on AWS

Altostra says ChatGPT-like apps can be built using AWS Lambda and any of the OpenAI GPT-3 models in less than five minutes.

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AI still requires human expertise

AI generates a lot of answers and saves a lot of time, but it’s too often incomplete or untrustworthy.

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The cost and sustainability of generative AI

All the people using DALL-E to create images or letting ChatGPT write their term papers are eating up a lot of cloud resources. Who’s going to pay for all this?

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GitHub Copilot update includes security vulnerability filtering

GitHub says the controversial AI-assisted coding tool is now being used by more than 400 organizations to increase developer productivity and improve code quality.

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Zero-shot learning and the foundations of generative AI

This alternative to training with huge data sets has potential for business, but data science teams will need to spend time on research and experimentation.

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10 reasons to worry about generative AI

After decades of speculation, real-world artificial intelligence has finally hit a tipping point. Now that we know what AI models like ChatGPT and DALL-E can do, should we be worried?

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Why observability in dataops?

Because building reliable data pipelines is hard, and the first step to becoming a data-driven organization is trusting your data.

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The tech leader's guide to 2023

What's ahead for cryptocurrency, cybersecurity, AI-based application development, and extended reality in 2023? Here's a roadmap from some of tech's most forward-thinking leaders.

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Gradient descent in Java

Find out why backpropagation and gradient descent are key to prediction in machine learning, then get started with training a simple neural network using gradient descent and Java code.

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Getting started with Azure OpenAI

Microsoft’s Azure-hosted OpenAI language models are now generally available, and it’s surprisingly simple to use them in your code.

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nbdev v2 review: Git-friendly Jupyter Notebooks

Add-on to Jupyter Notebooks enables a literate Python development style that gives you high-quality documentation, tests, continuous integration, and packaging for free.

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MLops is the hot new cloud computing career path

Amid the popularity of ChatGPT, MLops spending will surge in 2023 as leaders increase investments in machine learning. Cloud pros should take a look.

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The tip of the data science iceberg

Data science is already a vital element of a successful business. Before long it will be part of every application, and AI will be embedded in every transaction workflow.

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How to build a neural network in Java

The best way to understand neural networks is to build one for yourself. Let's get started with creating and training a neural network in Java.

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Can AI replace cloud architects?

AI systems get more impressive every day. Today’s AI can automate the tasks of many information workers, so those in cloud jobs worry they're next.

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Styles of machine learning: Intro to neural networks

Modeled on the human brain, neural networks are one of the most common styles of machine learning. Get started with the basic design and concepts of artificial neural networks.

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What kind of future will AI bring enterprise IT?

Think of artificial intelligence as a useful tool to help a company take small steps forward, rather than something to supplant people.

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