Berlin Brown and Software Development

  I asked this to Chat GPT, this is the response. "What would Aaron Swartz feel about the current state of the web, paywalls, advertising and cookie tracking?" Before I post, he actually was one of the creators of RSS, I am looking at now.  A machine readable web.  Wanted to post some links. Even RSS board has ads. https://www.rssboard.org/news/15/rss-advisory-board-goes-public https://www.openweb.com/resources This is straight from Chat GPT - openai "Given Aaron Swartz’s passionate advocacy for open access, freedom on the internet, and privacy rights, it's very likely that he would be deeply disappointed with several current trends on the web, including paywalls, advertising models, and cookie tracking. Here’s a breakdown of what he might think: 1. Paywalls and Information Access Swartz was a vocal proponent of open access to information, famously co-founding Infogami (which became Reddit ) and later being involved with initiatives like Open Library and The Public...

 

 Here is a mushroom gravy recipe. To make a lightweight thin mushroom gray sauce in a crockpot, you're likely aiming for a smooth, savory mushroom-based gravy that can be used as a sauce or topping. Here's a simple recipe to make mushroom gravy in a crockpot: Ingredients: 2 cups fresh mushrooms (such as cremini or button), sliced 1 medium onion, finely chopped 2 cloves garlic, minced 2 tablespoons butter or olive oil 1 cup vegetable broth (or chicken broth for non-vegetarian option) 1 cup milk or heavy cream (for a lighter version, use milk or a non-dairy option) 2 tablespoons flour (or cornstarch for a gluten-free version) 1 teaspoon soy sauce (optional, for umami) Salt and pepper to taste Fresh thyme or rosemary (optional) Instructions: Sauté the Aromatics (Optional): In a pan, melt the butter or heat the olive oil over medium heat. Add the chopped onions and cook for 3-4 minutes until soft. Add the garlic and cook for another 1-2 minutes until fragrant. Prepare the Mushroom ...

 This is from Chat GPT Streaming text character by character in a web-based UI can be achieved using several modern web technologies. Here's how it can be done: 1. Using Server-Sent Events (SSE) How it works: The server streams text data to the client using an HTTP connection. The client listens for incoming data and updates the UI in real-time. Implementation: Server-side (Node.js Example): javascript Copy code const express = require('express'); const app = express(); app.get('/stream', (req, res) => {     res.setHeader('Content-Type', 'text/event-stream');     res.setHeader('Cache-Control', 'no-cache');     res.setHeader('Connection', 'keep-alive');     let i = 0;     const interval = setInterval(() => {         res.write(`data: Character ${i++}\n\n`);         if (i > 10) {             clearInterval(interval);             ...

 You can see my posts here: https://bsky.app/profile/berlinbrown.bsky.social

 So I took Sebastian's large language model code as is.  Note, copyright to him.  But I was curious what are parameters? What are parameters?  See my previous post but... # This is a large model, reducing #LLAMA2_CONFIG_7B = { # "vocab_size": 32000, # Vocabulary size # "context_length": 4096, # Context length # "emb_dim": 4096, # Embedding dimension # "n_heads": 32, # Number of attention heads # "n_layers": 32, # Number of layers # "hidden_dim": 11008, # NEW: Size of the intermediate dimension in FeedForward # "dtype": torch.bfloat16 # NEW: Lower-precision dtype to save memory #} # Previous run # huggingface_hub version: 0.26.1 # sentencepiece version: 0.2.0 # torch version: 2.4.1 # Total number of parameters: 6,738,415,616 # float32 (PyTorch default): 52.33 GB # bfloat16: 26.17 GB LLAMA2_CONFIG_7B = { "vocab_size" : 32000 , # Keeping ...