The inimitable and unbelievably generous David Giard was kind enough to invite me onto his podcast to discuss artificial intelligence.
Making AI Practical and Practicable
Making AI Practical and Practicable
The inimitable and unbelievably generous David Giard was kind enough to invite me onto his podcast to discuss artificial intelligence.
If you’ve been alive in tech anytime in the past two years, you’ve been told, repeatedly, loudly, often by people who discovered prompt engineering five minutes ago, that large language models are here to revolutionize everything. Your job. Your team. Possibly civilization itself. This is not that article. Instead, I…
With my thanks to AgileIndy for putting on a lovely show, and my colleague Adam for taking the video. Abstract Artificial Intelligence (AI) is no longer science fiction; it’s here today, and it’s here to stay. It is in the products you use every day: home automation, digital assistants, or…
The AI gold rush has created a weird kind of pressure. If you’re not chasing the trend, you’re behind. If you ask hard questions, you’re a stick in the mud. If you jump in too fast? You might end up with a flashy prototype and no plan to support it.…
I love a good case study. AI never crops up in the ways you think it will. Here’s a discussion of optimization for the lumber industry that I first gave at Nebraska.Code() back in ’23, with many thanks to the folks at Amegala for putting on that show, and my…
Let me put a flag in the sand. The documents that come out of research aren’t the value. The value is in building expertise in the researcher.
It’s only been a year, and man, has this take aged in the interim. It’s hard to imagine today from a year ago, when many of the businesses I interacted with were terrified of what generative AI would mean for their data security postures and IP. Now that conversation is…
We’ve been here before. Several times. This is not to say today’s breakthroughs aren’t impressive, they are, but calm the hell down. This scale of breakthrough isn’t unprecedented, even in my lifetime.
Lately, we’ve been fielding a lot of interest in custom Retrieval Augmented Generation (RAG) systems. And honestly, it’s easy to see why. RAG systems are incredibly flexible tools for injecting up-to-date, domain-specific knowledge into AI responses for answering questions, generating content, analyzing internal data, or any other task that’s primarily completed by producing an artifact.
A short story on the dangers of misapplying generative AI technology, born of a prompt for a writing competition and more than a few at-bats with folks wanting to treat LLMs as a panacea.