rsiqueira

Joined 17 years ago

Karma
1,583
Submissions
179
Member since
Jul 28
Entrepreneur and Software Developer.

My online JavaScript editor: http://js.do/

Dwitter profile: https://www.dwitter.net/u/rodrigo.siqueira

My company: InBot - https://in.bot/ and * bit.do (URL shortener)

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Recent submissions

Comment · 9 months ago
Comment · 1 year ago
Dwitter is a JavaScript-based social network where coders showcase their creativity by crafting mesmerizing animations and visual effects in just 140 characters of code. Check out this festive collection of fireworks, New Year, and Christmas-themed masterpieces!
Comment · 1 year ago
Here is a sample of an animated XOR texture in just 122 characters of JS code: https://www.dwitter.net/d/255

And here are several variations using other binary operators to create the Sierpinski triangle: https://www.dwitter.net/h/sierpinski

Comment · 2 years ago
* Which languages is it available in?

* Does the system automatically detect the language?

* What are the hardware requirements for it to work?

Comment · 2 years ago
In one of those random connections, I met my wife through ICQ.
Comment · 2 years ago
Comment · 2 years ago
REQUEST: Please add an option for a monospace/code font. I see that <pre><code>...</code></pre> works very well (good monospace block style), but I have to inspect and edit the source.

With this, we could be able to use it for code!

THANKS!

Comment · 3 years ago
Comment · 3 years ago
URGENT - Does anyone have an alternative to OpenAI's embeddings API? I do have alternative to GPT's API (e.g. Anthropic Claude) but I'm not able to use them without embeddings API (used to generate semantic representation of my knowledge base and also to create embeddings from user's queries). We need to have an alternative to OpenAI's embeddings as a fallback in case of outages.
Comment · 3 years ago
Is this equivalent to a 14 gram bullet (10x less than your example) travelling at 1000 km/h (10x more than your example)? Or a 1,4 gram bullet at 10.000 km/h hitting you?
Comment · 3 years ago
But, in order to generate the vectors, I understand that it's necessary to use the OpenAI's Embeddings API, which would grant OpenAI access to all client data at the time of vector creation. Is this understanding correct? Or is there a solution for creating high-quality (semantic) embeddings, similar to OpenAI's, but in a private cloud/on premises environment?
Comment · 3 years ago
This means that the cost would be more than US$ 1 for each 16 user interactions, using this fine-tuning pricing: 16 interactions * ($0.012*4 input + $0.016 output) = US$ 1.02

It's 8x more expensive, indeed. I'm comparing with my use case, the standard gpt-3.5 API, where my users consume 4k input tokens (due to context plus chat history) and almost 1k output tokens.

Comment · 3 years ago
Even ChatGPT 3.5 can answer correctly if you ask just "She died at 11 PM. Was she alive at noon?". My theory is that this is an adversarial example that adds irrelevant information (bpm, blood pressure, heart rate) that the model could have given more attention than the relevant part of the question.
Comment · 3 years ago

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