Although artificial intelligence (AI) has been around in some form since the 1950s, it was the first public release of ChatGPT and OpenAI’s foundational large language models (LLMs) like GPT 3.5 that made generative AI (GenAI) applications available to people who aren’t data scientists and computer geniuses.OpenAI’s models and models from companies such as Google, Facebook, Anthropic, and others ignited the world’s demand for increasingly sophisticated GenAI models and tools, and the market was quick to deliver.

When you’re new to crafting AI prompts, you can easily make mistakes. Using AI tools the right way makes you more productive and efficient. But if you aren’t careful, you may develop bad habits when you’re still learning. We clue you in to 10 mistakes you should avoid from the start in this video and article. Not Spending Enough Time Crafting and Testing PromptsOne common mistake when using AI tools is not putting in the effort to carefully craft your prompts.

A geographic information system (GIS) is a software for making maps, analyzing data, and more. This cheat sheet tells you about what you can do with GIS, provides a handy guide to raster-based functions, gives you some key ideas to keep in mind about maps (relating to scales, projections, and datums), and the X, Y, and Z of GIS.

The field of SAS and SAS programming has evolved over nearly 50 years, leading to the development of various shorthand techniques. These techniques may not be immediately apparent to new SAS users, but they become clear with learning and practice. Use the tips here to get a head-start and accelerate your initiation to SAS.

Artificial intelligence (AI) offers a lot of promise to companies, but deploying AI can be complex with many considerations and pitfalls. Data is the necessary asset to make AI work, and your organization is probably swimming in it.But how well-managed is your data? The answer hinges on whether your company will be successful in its AI efforts.