anupsurendran

Some CTA stats included based on research with 12 SaaS companies

Does Pathway's ability to use multithreading improve the processing when you deal with multiple kafka topics?

I had the same question Jacknews, I couldnt find the person who is running this at vercel to ask this question. Maybe we should just tweet?

Historically yes - uppercases came first. Even when lower cases showed up, the combination key sequence to get the lowercases working was harder so that took more time to catchup

every side has a story to tell. a story without emotion is not worth telling.

This is a Google Colab notebook (that works in Jupyter too). The notebook can connect to live data sources (e.g. Kafka) and you can do analysis. You could do a CSV replay if you have timestamped data entries

100% vthallam. The upside for OpenAI is much higher.

Does this only work with Jupyter? Or does it also work with Google Colab?

Jan, can you explain briefly how the deduplicator checks if the new answer is significantly different? Is there code in the repository we can take a look at?

I feel that there are too many moving pieces here especially for prototyping. There was a much more simpler app recently I took a look at on a recent hackernews post : https://news.ycombinator.com/item?id=36894142

They still have work to do with different connectors (e.g. PDF etc) but the realtime simple document pipeline is what helps a lot.

I understand much better. Thanks. So this is much more programmer extensible and possibly get data from other sources (not just unstructured data).

Thanks for these links. I also had a thread around alternatives to vector databases going on today on Linkedin https://www.linkedin.com/feed/update/urn:li:activity:7090376... . What is the criteria to go for a vector index vs vector database?

My favorite ones are the data science and AI video tutorials (actually meant for kids) @ https://www.Pathway.ai

I just created a whole playlist of what I think kids should learn for basic data analysis here : https://www.youtube.com/playlist?list=PLoDI7JNsZEp8aNw2OaaOJ...

Kids were out on summer vacation and I started a Khanacademy style youtube video for Kids to get introduced to Data Science and AI. I am only introducing programming concepts on an as needed basis. Would love feedback and thoughts on how to improve this. My intent was 1. to get them used to other real environments than mit scratch 2. To start with Data Exploration first and then get into ML 3. Use simpler gaming concepts and techniques as it gets tougher to grasp these skills

I have been struggling with this. Obviously Farnam Street and some medium posts have done a great job here. I wanted to teach mental models to a younger audience and make it more fun and actionable so I just started this and am collecting a group of kids (including mine ;) ) http://www.enchanting.io