adi2907

Lovable is the Wordpress of today. No developer worth his salt would have touched Wordpress to develop websites but it was a boon to non developers who could use its templates. Lovable fills the same need for non techies today

I was confounded when many in my accelerator batch were using Lovable to string up demos when Claude Code would have done the same with much better controls. Thing is terminals, repos dont appeal to most.

That said, Replit, Lovable, Emergent are making hay till frontier labs dont release a wrapper agent app to do what they do.

Its refreshing to see corporate research labs in a non AI area. Clickhouse has been a huge beneficiary of the AI wave and its good to see some of the value going into advancing fundamental research in infrastructure

Once OpenAI and Anthropic are public, every such announcement will become a reliable sell signal

What a transformation by Xiaomi to build almost frontier level models. Five years back, when I was in the data science team, they dint really bother about AI models and were using Baidu for NLP and vision under the hood of their APIs

This is definitely very useful, and something i've been thinking of to build myself. A personal CRM. Issue is when I see something like this - where it will take me around half hour to figure out - while i can vibe code something in an hour which will do much more and personalize it for me, I hold back on trying it out.

This is a 5 day - only code , no maths -introduction to data science covering all critical topics and suitable for beginners. As a practicing data scientist, this covers 80% of my toolkit. All datasets are created synthetically. I created this course as almost all the existing courses cover too much material, too much theory and maths and don't emphasize the practical aspect of using existing algorithms to achieve impactful output. I hope this helps beginners and I wish a course like this existed when I started years back to not dissuade me from learning this approachable field

Very impressed. I am not a scientist but am building a product for intent-based discounting in Shopify. Typically Google scholar gives me very generic results using LSTM etc however this search gave me some interesting results with focus on real world implementation. The clarifying questions are also quite impressive as it gives the impression that it is understanding the query really well. Good stuff. I think it might be useful for end-users and not just company/research folks as well