anyone hosting? want to try it
Readit Newselevenoh4 commented on Open-source, uncensored alternative to CharacterAI opencharacter.org... · Posted by u/bobcoi
seems you're using both open & closed source models
i just tried it out. solid, but doesn't seem as uncensored or capable as e.g. https://uncensored.com/ai
btw: do u know whether c.ai actually parses tone/emotion from voice (or just from the SpeechToText stream?
i'd reach out to https://uncensored.com for api access
smartest/most human uncensored ai i've used. i think the api is live now
This is my most used app right now.
How the f did you make this? And it's so fast
elevenoh4 commented on I'm Peter Roberts, immigration attorney who does work for YC and startups. AMA · Posted by u/proberts
1. I'd be happy to speak with you and go through your options. 2. That's not the most important factor; we do E-2s for existing businesses and solo founders all the time.
What are the top items a solo software founder (of a treaty country) seeking e-2 might not have in their application/background or want in the outcome of an e-2?
elevenoh4 commented on Jim Keller on AI, RISC-V, Tenstorrent’s Move to Edge IP eetimes.com/jim-keller-on... · Posted by u/JoachimS
I have a list of some I'm keeping tabs on, I'll share it here. I do it out of a combination of personal obsession plus because I want to source angel investments.
Note though that I'm very biased toward AI companies...
Most established, clear product-market fit:
- OpenAI
- Midjourney
- Character ai
- Runway ML
Ones that are interesting:
- Adept AI
- Modal, Banana.dev
- new.computer
- Magic.dev
- Modular (Mojo)
- tiny corp
- Galileo
- Hippo ML
- Tenstorrent
- contextual.ai
- Chroma
- e2b.dev
- Steamship
- Patterns.app
- GGML
Ones that I want to learn more about before deciding:
- Inflection AI
- GetLindy
- Embra
- Jam.dev
- Vocode.dev
That's about 50% of my list. Happy to clean up the rest and write a post if there's interest
Solid sample. Let's see the list!
Sounds a lot the style I learned from working through HTPD[1]. Define data types, then pass the data around through functions. You work through it in a dynamic language, but you keep track of all your data types, writing them above your function definition and make sure they line up, kind of like a manual, self-imposed type-checking system.
One thing that amazed me while working through HTDP was that almost all my bugs came from not understanding the data types correctly, or messing something up with the process of manual type-checking. Once I understood the data structures I was trying to pass around and compute with, the bugs almost always melted away.
Now I program basically everything in a language with type checking (mostly in TypeScript) with thinking about data types and type definitions as the foundation. I'm amazed to see how 95% of the pain, complexity, and bugs has just melted away.
[1]: https://htdp.org
I'd like to do more of this. but every time i use typescript in react/nextjs i end up hitting breakpoints in transpiled js code instead of the TS source, esp. in my tests/running single-files.. and i've tried so many debug configurations
BMath 2005 here.
I worked with a bunch of smarter-than-me UW grads after graduating.
My “how to write large systems” takeaway from that early point in my career was to focus on the interfaces between various parts. What I’d never thought about until now is that is a very data centric viewpoint.
- What system has what data?
- In what shape?
- What shape does the next system need its data in?
- Are the interfaces between these orthogonal? Shallow? Easy to grok? Tight (as opposed to leaky)?
Great article.
great way to put it.
>Shallow?
too many deep inheritance typescript libraries being built today I find!
i've seen too many businesses destroyed by sudden "your account is closed" with no human contact