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!
Some samples from the article are similar to what is found on my favorite Generative Art site - Dwitter. It's a social network of coders where we can view, interact and remix live code. Everything under 140 characters of creative JavaScript code: https://www.dwitter.net/top/all
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.
There are IFS-like fractals that can be generated using small iterative functions. Here are examples in JavaScript that can be remixed (and they are very short, only 140 characters or less). E.g.:
https://www.dwitter.net/h/fractal and https://www.dwitter.net/h/fern
Dwitter is a cool social network where JavaScript programmers can share demos, fractals, art algorithms and interactive code viewed on <canvas>.
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.
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?
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?
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.
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.
I've just implemented this Blancmange curve using less than 140 characters of javascript. It's a fractal also known as Takagi curve. Source code and graphics: https://www.dwitter.net/d/28260 (it can be edited and remixed)
An evolution of the demoscene has emerged in the form of a social network where 140 characters of JavaScript code are used to create incredibly impressive and compact demos. Check out Dwitter: https://www.dwitter.net/top/all
I think it's not secure to have a domain extension like .zip.
Imagine if people were to search for, for example, "install.zip," and there is a domain with that name and extension automatically assigned to it. It could potentially lead users to automatically download a malicious version of the "install.zip".
No. It's because OpenAI's token model is highly biased towards English words. In this way, other languages are greatly disadvantaged, reducing competitiveness in non-English-speaking countries. In my language (Portuguese and Spanish), for example, my cost increases by 60% to 75% due to the content I need to process not being in English.
The real gain would be if we were able to use the 100K Context Windows and not this "embeddings trick". The embeddings work only in some cases where the answer is in a short part(s) of the document. If user asks something like "what are the main ideas?" or "Summarize the document." or any question that needs context from large portions of the book/pdf/file, then it will not work with the embeddings trick that use just short passages in prompt. But if large context windows costs are high, we need to keep using embeddings and few text parts.
Fractals: https://www.dwitter.net/h/fractal
Dynamical systems / chaos: https://www.dwitter.net/h/chaos
Strange attractors: https://www.dwitter.net/h/attractor
Spiral-based generative art: https://www.dwitter.net/h/spiral
Fireworks simulation: https://www.dwitter.net/h/fireworks
Procedural scenes: https://www.dwitter.net/h/scene
Wavelets (3D and 2D): https://www.dwitter.net/h/wavelet
And the most popular dweets: https://www.dwitter.net/top/all