I have realized that my browser is basically a graveyard for helpful links. I spend half my day saving essential AI guides and the other half feeling guilty for not reading them. It turns out that the actual secrets of the technology are being published for free by the people who build the models. I just had to stop looking for shiny marketing videos and start looking at the actual manuals.
Being Finnish means I have a deep and slightly irrational love for anything that costs zero euros. Give us a free plastic bucket and we will stand in the rain for hours just to claim it. This is why I feel such a strong sense of pride when I see the University of Helsinki mentioned alongside giants like MIT or Stanford. Their Elements of AI course is a perfect example of Finnish practicality. It is honest and does not try to sell you a dream of becoming a billionaire overnight. It just explains the logic so you can stop being confused.
My history with the University of Helsinki actually goes back quite a way. Even though I eventually focused on Literature as my major I spent some time in the computer labs during the distant nineties. I even managed to complete a basic programming course back then. We were using Turbo Pascal which was the cutting edge of the era. I honestly wonder if the younger generation has even heard of it or if they think it is some kind of vintage racing game. Moving from Turbo Pascal to Large Language Models feels like a massive leap but the foundation of logical thinking remains the same.
I have been sifting through the actual manuals from the big players lately as well. Anthropic has a guide that feels like a secret handbook that someone accidentally left on a park bench. OpenAI has documentation that is dense enough to be used as a structural support for a house. Even Microsoft Research has whitepapers that people think are locked away behind corporate paywalls but they are actually just sitting there waiting for someone to read them.
The problem is that I am a bit of a digital magpie. I see a shiny link from Andrew Ng or a course from MIT and I click save immediately. I have enough bookmarks to start a small library. However as we say in Finland it takes sisu to actually do the hard work. The information is not the problem anymore because it is everywhere. The real challenge is having the discipline to stop hoarding and start building something.
A resource is only useful if you actually open the tab and apply it. I am trying to spend less time collecting and more time creating. Below are the actual links that I have been hoarding. Hopefully you will use them better than I have.
Resources for your AI journey:
Anthropic Prompting Guide at https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/overview
OpenAI Prompt Engineering Guide at https://platform.openai.com/docs/guides/prompt-engineering
Google DeepMind Research on Chain of Thought at https://arxiv.org/abs/2201.11903
Microsoft Research Whitepapers at https://www.microsoft.com/en-us/research/our-research/
DeepLearning.AI short courses by Andrew Ng at https://www.deeplearning.ai/short-courses/
Fast AI Courses at https://www.fast.ai/
Elements of AI by the University of Helsinki at https://www.elementsofai.com/
MIT OpenCourseWare AI Curriculum at https://ocw.mit.edu/courses/6-034-artificial-intelligence-fall-2010/
Hugging Face Forums at https://discuss.huggingface.co/
Latent Space Transcripts at https://www.latent.space/
Simon Willison’s Blog at https://simonwillison.net/
AI Community and Tools Directory at http://beprompter.in
