What would an AI model have to do for you to finally say “okay, this is AGI”?

We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks: Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better: Diagrams / images. Instead of writing, ask your LLM to create a diagram. These can be a lot easier to process, parse, and understand. But even better: Web pages. Ask for output "in HTML" to get a beautiful, interactive webpage. LLMs are getting really good at frontend and can create beautiful experiences, animations, etc. But even better: Explainer videos. The output format I am most bullish on is fully custom / bespoke explainer videos generated on any arbitrary topic. Experiment with things like "Create a 3b1b style video explainer on X. Use my ElevenLabs API key for audio narration". (you'd need an API key for the latter or you can ask your LLM to find you decent free alternatives that use your local compute). This is actually starting to work! In summary: - As LLMs get better, they will do more and more of the legwork autonomously, and a lot more of our work will rise up the abstractions into oversight and understanding. - Luckily, LLMs can help here too because as intelligence and code are increasingly abundant, you can ask for large, custom, discardable software artifacts (e.g. web apps, video explainers) that would have never made sense to create before. Push the boundaries here and you'll be surprised.

Can I ask a dumb question: Why do AI products fail?

Are you actually waiting for Fable 5.5 or has Opus 5.5 made you stop caring 😭

The $20 AI plan isn’t enough for my workload anymore 😭 How are you people getting through a full day of work on ChatGPT or Claude’s $20 plan?

Be honest: How many times has a Tibo reset interrupted your plans to cancel ChatGPT?

So where does a downloaded AI model keep what it “knows”? In numbers called weights, saved inside the model files. During training, those numbers are adjusted as the model learns patterns from examples. When you ask a question, your computer uses them and your prompt to generate an answer. That’s why a local model can work offline once the necessary files and software are downloaded. But reconnecting it to WiFi doesn’t magically update its knowledge. It needs tools to fetch new information, information you provide, or further training.

The reason why you’re losing to your competitors:

If this question made you curious, you’ll probably enjoy my articles too 😂 I write about AI and developer tools in plain English, with a new article every Wednesday. Check my Articles tab and follow along, we’re figuring this stuff out together 🤍

Do you do this? 😂

Does anyone else open a new AI chat because the previous one knows too much about how badly the project is going?

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What do you guys think?