verghese

How does this compare with Spark TTS?

https://github.com/SparkAudio/Spark-TTS

Gumroad's journey has been interesting: https://sahillavingia.com/reflecting -> Billion dollar journey with VC backing to Kleiner selling back their stake to Gumroad for $1, which enabled Sahil to steer the company in a different direction.

Perhaps the shift to making the source available has more to do with work culture: https://sahillavingia.com/work

Switched over from Iterm - A fundamental feature I'm missing is the search feature (Cmd + F).

I'm not sure if this will impact the market the same way the R1 did. However, my general impression is that while Meta spent $20B on their 100k H100s, DeepSeek is demonstrating that you can achieve better results far more cost-effectively using just 2k H100s. This doesn't seem like good news for Nvidia, but it sets a great precedent for companies looking to train models.

How does this compare to a tool like RepoPrompt?

https://repoprompt.com

Reminds me of the the quote from Albert Einstein: "I very rarely think in words at all. A thought comes, and I may try to express it in words afterwards."

Language is a higher level abstraction for the brain. Sort of like a higher level programming language vs assembly or binary.

I remember growing up in India and plastic was introduced to "save the trees". It took us decades for us to fully grasp the environmental devastation it caused.

Checkout https://exemplary.ai - we incorporate a similar approach with our transcript editor.

Could you tell me how this compares with other open-source session replay projects such as: 1) OpenReplay (https://openreplay.com/) 2) PostHog (https://posthog.com/)

This list is limited to H1B founders - the list of all immigrant founded unicorns would be much larger. A comprehensive list of all startups (unicorn or otherwise) founded by h1b holders could be a better indicator. Another way to quantify contributions could be aggregate taxes paid by these individuals but this data may not be available.