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Mushroom Gravy Recipe from Chat GPT
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From Chat GPT. 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 Base: Place the sl...
Calculating parameters and what does that mean - straight from Chat GPT
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This is a question from Chat GPT and Sebastain's book on large language models from scratch. First, this data is interesting. 124 Million parameters GPT_CONFIG_124M = { "vocab_size": 50257, # Vocabulary size "context_length": 1024, # Context length "emb_dim": 768, # Embedding dimension "n_heads": 12, # Number of attention heads "n_layers": 12, # Number of layers "drop_rate": 0.1, # Dropout rate "qkv_bias": False # Query-Key-Value bias } The 1.5 billion parameter GPT model config GPT_CONFIG_1558M = { "vocab_size": 50257, # Vocabulary size "context_length": 1024, # Context length "emb_dim": 1600, # ...
Testing multi machine hadoop cluster
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So I was testing setup of a hadoop cluster and running map reduce. There are preliminary notes in first post. One key, I ran all commands under openssh as that user Setup the user Main machine: sudo usermod --shell /bin/bash mainhdfs Start openssh openssh su - mainhdfs sudo apt-get install openssh-server sudo systemctl enable ssh sudo systemctl enable ssh --now sudo systemctl start ssh su - mainhdfs sudo mkdir /usr/local/hadoop sudo mv hadoop-3.3.6 /usr/local/hadoop/ sudo chown own -R mainhdfs:hadoop /usr/local/hadoop sudo chown -R mainhdfs:hadoop /usr/local/hadoop Setup more on ssh: ssh-keygen -t rsa -P '' -f ~/.ssh/id_rsa cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys chmod 600 ~/.ssh/authorized_keys chmod 700 ~/.ssh Write the following .bashrc and .bash_profile for that user export HADOOP_HOME=/usr/local/hadoop/hadoop-3.3.6 export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin export HADOOP_CONF_...
More posts around deep learning and google deep mind
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robotics http://hutter1.net/ai/suaibook.pdf https://arxiv.org/abs/1708.04782 https://github.com/google-deepmind/pysc2/blob/master/pysc2/lib/named_array.py https://github.com/google-deepmind/deepmind-research/tree/master/tandem_dqn https://www.youtube.com/watch?v=hCeJeq8U0lo&t=9s https://arxiv.org/pdf/2105.14039 https://arxiv.org/pdf/2102.05182 https://openreview.net/forum?id=nPHA8fGicZk https://github.com/google-deepmind/deepmind-research/tree/master/tandem_dqn . Neuromorphic Computing Technologies: Neuromorphic chips like Intel's Loihi or IBM's TrueNorth are designed to mimic the structure and function of the human brain, making them ideal for brain-like AI models. Purpose: These chips are designed to support spiking neural networks (SNNs), which are more biologically plausible than traditional artificial neural networks. 2. Spiking Neural Networks (SNNs) Algorithms: SNNs use spikes (events) to transmit information, similar to how neurons communicate in the brain. This al...
Was going to watch twitter x - Trump and Elon Musk - It crashed
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Random thoughts on AI
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Random AI Thoughts Posts - things I am looking at: scale ai Pinecone Perplexity Notion Hebbia Character AI --- web server web client stand alone - limited html and http - validates your html and shit very strict -- tomcat based -- my own ML-From-Scratch Description: This repository provides implementations of various machine learning algorithms from scratch in Python, without using libraries like Scikit-learn. It's educational and shows how algorithms like k-means clustering, decision trees, and linear regression work under the hood. Repository: ML-From-Scratch on GitHub You-Get Description: A simple and powerful tool for downloading media files from the web. It uses machine learning for analyzing and categorizing the downloaded media. Features: Supports various media sites, custom download options, and automated media organization. 3. OpenAI Gym Description: A toolkit for developing and comparing reinforcement learning algorit...
See older post on cellular automata
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An older post on cellular automata https://berlinbrowndev.blogspot.com/2013/02/wolframs-cellular-automata-new-kind-of.html A New Kind of Science The name Stephan Wolfram has been mentioned several times in this post. He is the founder of Wolfram|Research, his company is known for the popular Mathematica software suite and Wolfram|Alpha knowledge engine. He did not initially discover cellular automata but recently he has been a prominent figure in its advocacy. He spent 10 years working on his book, A New Kind of Science. In the 1300 page tome, he discusses how cellular automata can be applied to every field of science from biology to physics. NKA is a detailed study of cellular automata programs. Basic Cellular Automata Figure: Wolfram's Elementary CA Rule 30. Look at 3 bit input and 1 bit output. The diagram above depicts the rule 30 program (or rule 30 elementary cellular automaton). There are 8 input states (2 ^ 3) and an output state of one or zero. If you look at the diagram ...
What we learned from machine learning
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What we learned machine learning and deep learning So we have learned a lot from the machine learning and deep learning from Sebastian Raschka. See his blog https://magazine.sebastianraschka.com/ And the following machine learning and deep learning courses. https://sebastianraschka.com/blog/2021/ml-course.html https://sebastianraschka.com/blog/2021/dl-course.html The first set of courses cover: kNN - k nearest neighbor decision trees and popular ML python libraries.
Basic install jupyter
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Jupyter is the new thing for data science colab. It is a web based system for sharing interactive documents. To install linux (mint): Here I basically installed via pip with Linux sudo apt install jupyter-core sudo apt --fix-broken install jupyter-core sudo apt install jupyter-core pip install jupyterlab python3 -m jupyterlab And then with Mac Sonoma I had python3 already installed https://jupyter.org/install This one worked with Mac as well with python3 and myenv With the virtual environment setup jupyter notebook mkdir ~/myenv python3 -m venv ~/myenv ~/myenv/bin/python ~/myenv/bin/pip install ~/myenv/bin/pip install numpy ~/myenv/bin/python -m jupyter notebook ~/myenv/bin/pip install jupyter ~/myenv/bin/pip install --upgrade pip ~/myenv/bin/python -m jupyter notebook ~/myenv/bin/pip install numpy pandas numpy scipy matplotlib scikit-l...
Good Keynote and Hackerthon Adrej Karpathy
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https://www.youtube.com/watch?v=tsTeEkzO9xc " At the 2024 UC Berkeley AI Hackathon's Awards Ceremony, the atmosphere was electric as Andrej Karpathy, founding member of OpenAI, delivered an inspiring keynote. Out of 371 projects, the top 8 teams took the stage to pitch their groundbreaking AI solutions. After intense deliberation by our esteemed judges,"
Thoughts on #chatgpt5
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Thoughts on chatgpt5 #japan #atl #atx #llm Chat gpt has interesting responses to your prompt. And you have to prompt it. It comes back with a good response. PhD level? A PhD is what 30 years old. Went through life 30 years came up with papers on his own. https://www.tomsguide.com/ai/chatgpt/openai-cto-says-chatgpt-will-have-phd-level-intelligence-in-the-next-2-years
About Andrew Tanenbaum and Computing History
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I hope to add more talks about computing history and what not. #llm #history #minix https://www.theregister.com/2024/06/25/tanenbaum_minix_award/ Andrew Tanenbaum created a popular computer science book. I still may have a copy. It was about operating system design. Start from scratch. And he create the operating system Minix. I believe no direct code relation to Linux or Unix. Except, Linus of Linux did learn a lot from Minix.