5 years ago (after Alphago beat Lee Sedol), I and many others thought RL would soon change the world. It's impact has been smaller than we anticipated (mainly due to the Sim2Real problem)
If LLM's have less impact by 2027 than many now expect, what will be the reason?
Dan Becker
2,181 posts
- Kaggle is formally releasing a new micro-course by @alexis_b_cook next week. But it's already available at kaggle.com/learn/data-vis… It's just so good. Possibly the single best resource on the internet for someone new to Python who wants the fast path to useful skills.
- What would a more applied approach to AI look like? I think I have the answer. So I'm leaving Google and Kaggle to build a business around it. Check it out at why.decision.ai Want help getting more than predictions, so you can optimize decisions? Let's talk. I can help
- Announcing something I've wanted to do for years A Decision Optimization course with @wandb covering both simple & sophisticated techniques to help data scientists and ML engineers make their existing skills far more valuable wandb.courses/courses/decisi… The backstory 👇
00:00 - I'm 50/50 on whether we'll still use deep learning in 2030 But I'm confident we'll still use transfer learning Transfer learning is such a good idea, it's gotta be here to stay.
- 1) Start with a brainless baseline 2) Repeatedly make small improvements That's how xgboost and deep learning work It's how people run successful ML projects Not a bad strategy. We should use that more in other places.
- Kaggle just released a new Python course based on the wildly successful 7-day Learn Python Challenge. Check it out: kaggle.com/learn/python Great explanations, and a range of exercises that will be fun for both new and experienced Python programmers.
- Great summary of the state of RL. Why it has huge potential How it currently doesn't work (really, it doesn't) Suggestions on where to go from here jacobbuckman.com/2019-09-23-aut… I hope RL returns from its academic meandering, and we refocus on what's needed to solve real problems
- For anyone that wants to Learn Python, Kaggle will be host the "Learn Python Challenge" from June 11-18. In 20 minutes a day, you'll learn the basics most relevant for data science (and apply it to interesting hands-on puzzles). kaggle.com/python-challen…
- Kaggle is hiring an AI educator. Want to have a global impact? Here's your chance to share your skills with 10000s of data scientists a month.
- I keep hearing the claim "ChatGPT is just autocompletion" or "modern AI approaches just predict the next word." That changed a year ago with the InstructGPT paper. Important read for anyone that wants to understand current AI openai.com/blog/instructi…
- Writing about LLMs has so much hype and academic stuff with little actionable insight. This article is clear, real and practical. It's a great read oreilly.com/radar/what-we-…
- My favorite questions when interviewing data scientists are about ML explainability. ML explainability is so useful, but it isn't as widely known as it should be. Kaggle has a free micro-course teaching the key ideas in ML explainability.
- I just saw that the notebooks I authored for #Kaggle Learn courses have been forked over 2,000,000 times 🤯 There are a lot of great, free, applied data science courses at kaggle.com/learn

