Yogi Schulz

1 week ago | troymedia.com | Yogi Schulz

Reading Time: 4 minutesAlberta’s oil and gas industry outperforms most of the world in cutting emissions. It’s time environmentalists focused on the real global offendersEnvironmentalists often target oil and gas companies as the villains of climate change. It’s easier to blame corporations than to confront the reality that consumers are responsible for the vast majority of emissions. But if we’re serious about cutting greenhouse gases (GHGs), we need to tell the whole story.

3 weeks ago | engineering.com | Yogi Schulz

This two-part series introduces five of the 10 most common AI risks and how to mitigate them. AI functionality is increasingly a component of digital transformation projects. Delivering AI functionality adds business value to digital transformation. However, engineers will encounter multiple AI risks in these projects. Engineers can use these risk topics as a helpful starter list for their digital transformation project risk register.

1 month ago | engineering.com | Yogi Schulz

Some things to consider when opting for graph databases in engineering applications. Graph databases have moved from a topic of academic study into the mainstream of information technology in the last few years. Now engineers want to better understand: What advantages do graph databases offer over widely implemented relational databases? How can graph databases advance digital transformation initiatives? How do graph databases enhance engineering applications?

1 month ago | troymedia.com | Yogi Schulz

Reading Time: 4 minutesA layman’s guide to prompt engineeringPrompt engineering is a new skill that helps users get better results when using generative AI tools like ChatGPT. It involves writing clear and effective instructions—called prompts—so the AI understands what the user wants and responds appropriately. This guide explains the basic dos and don’ts of prompt engineering, with examples to help you get more useful responses from AI, whether for work, research or fun.

2 months ago | engineering.com | Yogi Schulz

More best practices engineers can use to significantly reduce model hallucinations. Many engineers have adopted generative AI at a record pace as part of their organization's digital transformation. They like its tangible business benefits, the breadth of its applications, and often its ease of implementation. Hallucinations can significantly undermine end-user trust. They arise from various factors, including: Patchy, insufficient or false training data.