Rescript is now at ★ 1,000+ Github stars 🤯
I built this as an open-source Descript alternative, it took a single weekend with Fable for the initial version!
Github: github.com/wassgha/rescript
Try it: getrescript.com
Rescript is a free, open-source podcast editor that lets you edit videos the same way you edit text. Unlike Descript, it runs fully offline, right on your device with nothing sent to the cloud.
starting over >>>> adapting pre-ai software
i respectfully disagree
i am actually quite bullish on underdog software startups, and feel fortunate to get to serve thousands of them at greptile.
here is what we see:
- ambitious startups have never been more leveraged. with coding agents they can punch far above their headcount. labs are competing to provide increasingly more value at lower prices.
- large software companies are being forced to step up their game in response. the best ones are painstakingly refactoring their engg orgs to adapt to a new way of building software
like many of the best tech disruptions, this one shifts power from incumbents to upstarts
Everyday, thousands of apple store employees have to explain to millions of apple store shoppers that the Apple Store app is not the same as the App Store app and that’s fascinating to me
Robots are now an API call. We are about to witness the physical equivalent of the “chatgpt wrapper” startup archetype, hundreds of companies will be specializing robots to various tasks and it’s freaking exciting.
Over the past month, we completely switched to frontier LLMs to control a robot in a customer deployment.
By doing this, we have a classic System 1/System 2 architecture, but on steroids.
For the high-level reasoning layer, we use an agent based on Opus and Astra, which are many generations more capable than any VLA. For the fast execution layer, we use computer vision code written by the model, which is fast, editable, and reliable.
As a bonus, we got in-context learning, which is just a basic feature of LLMs, and continual learning, since whenever a new situation arises, the large model steps in and adapts the pipeline.
And it just feels better to be on the right side of the Bitter Lesson, benefiting from the billions being invested in frontier models around the world.
Wassim retweeted
Over the past month, we completely switched to frontier LLMs to control a robot in a customer deployment.
By doing this, we have a classic System 1/System 2 architecture, but on steroids.
For the high-level reasoning layer, we use an agent based on Opus and Astra, which are many generations more capable than any VLA. For the fast execution layer, we use computer vision code written by the model, which is fast, editable, and reliable.
As a bonus, we got in-context learning, which is just a basic feature of LLMs, and continual learning, since whenever a new situation arises, the large model steps in and adapts the pipeline.
And it just feels better to be on the right side of the Bitter Lesson, benefiting from the billions being invested in frontier models around the world.
I built a literal Siri orb by gutting one of those amazon memory crystal things because why not 🤷🏻♂️
