Today, I caught up on some AI news.
There are lots of cool AI demos floating around on the net. Some look super impressive, but they fall apart when you dig into actual use cases.
In December last year, we learned that the Google Gemini model was edited favourably to look more impressive than it actually is. There’s no doubt that these models are incredible, but the demos are often designed to stir up more hype than is warranted.
Recently, there’s been talk of tools like Devin replacing software engineers. But experts in the field are more sceptical. Here’s a great breakdown video that tames the hype. (The Reddit discussion is good, too.)
And what of large language models in general? People are starting to see limits. Here’s a good perspective from one person who’s used LLMs on half a billion tokens in an enterprise use case.
Overall it’s great to see all the cool things generative AI can do. But we need to tame expectations! These tools have limits.