Tracking and analyzing 340 AI leaders/blogs to find out what matters

One of the challenges I face as a AI engineer/leader/founder is knowing about what's important in AI and what's noise. It's hard to understand what really matters and what tools I should use and not use.

To help solve for this, I created BrightRay. It currently tracks 340 AI leaders across X, blogs, the web, and papers, and then distills these into daily, weekly, and monthly summaries.

It tells me what really matters and what to avoid. I'm reading it daily now.

I want this to be valuable to more people than just me, so I'm sharing it. It's early and rough, so please give me feedback on how to make it better.

Here's my site to try out: https://brightray.ai/ You can leave me comments here, or just click on the 'Make a wish' button.

3 recent data it found in the past 2 days that were helpful to me, just for reference:

Sakana AI's announcements is clickbait - https://brightray.ai/summary/deb-e1ed2d7b3181?via=mountaind

DeepMind came out with an AI Control paper - https://brightray.ai/summary/dev-2d75bf4b3125?via=mountaind

Mistral and new open source OCR for document processing - https://brightray.ai/summary/dev-c8528ec501b6?via=mountaind