How-to & Style


Web server vs. application server: https://ibm.biz/Apache_Vs_NGINX
NGINX Reverse Proxy: https://ibm.biz/NGINX_proxy
If you're into web development, you have undoubtedly heard of Apache and Nginx. They're both open source web servers, but they have different strengths, and both are worth considering as part of your web architecture choices. Is speed at all costs your thing? Or extensibility? In this video, Martin Keen explains how these web servers work and then breaks down the tradeoffs of each solution (spoiler: it's not an either/or answer).
Get started for free on IBM Cloud → https://ibm.biz/sign-up-today
Subscribe to see more videos like this in the future → http://ibm.biz/subscribe-now
#AI #Software #Dev #lightboard #IBM #MartinKeen #Apache #NGINX


MANY THANKS TO ALL MY PATRONS on https://www.patreon.com/onemarcfifty !!!
Please visit my channel page: https://www.youtube.com/onemarcfifty
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We will install IOTStack and Webmin on a raspberry Pi4. IOTStack is a complete collection of famous home automation software such as Home Assistant, Openhab, Node Red and many others. With this you can run your home automation software in docker on a pi.
0:00 Use a Pi as Home Automation Server
0:38 Intro jingle
0:48 TLDR/TLDW
1:01 description of IOTStack
2:06 Get IOTStack and Install Docker on the Pi
3:33 Installing IOTStack on the Pi
5:22 Installing Webmin
7:30 Call to Action
the commands used in this video
To download, install and start IOTStack:
sudo apt install -y git curl
git clone https://github .com/SensorsIot/IOTstack.git IOTstack
# please remove the space before the dot com
cd IOTstack/
./menu.sh
sudo raspi-config
locale
sudo reboot
cd IOTstack/
./menu.sh
docker-compose up -d
To install webmin:
wget https://prdownloads.sourceforge .net/webadmin/webmin_1.962_all.deb
# please remove the space before the dot net
clear
sudo dpkg -i webmin_1.962_all.deb
sudo apt -f install
Licence-free music on / Lizenzfreie Musik von https://www.terrasound.de/lize....nzfreie-musik-fuer-y


Unlock the full potential of **uncensored AI image generation** with this comprehensive guide! In this video, I walk you through setting up an Ubuntu 22.04 server with NVIDIA drivers, Ollama, OpenWebUI, and ComfyUI for powerful image creation. Whether you're a beginner or advanced user, learn how to configure OpenWebUI beyond the basics and integrate it with ComfyUI to generate uncensored images effortlessly. Plus, I’ll show you how to download models from top resources like Civitai and explore the highest-ranked models from ImgSys.
Watch as I break down:
- Full Ubuntu server setup with NVIDIA drivers
Full video : https://youtu.be/FUmO-jREy4s?si=u1BDf9XWDqmUXiDY
- Ollama and OpenWebUI installation for local AI processing
- Deep dive into ComfyUI integration and advanced configuration
- Tips on downloading and using AI models for uncensored image generation
00:00 - Introduction and Demo
03:43 - Server Setup with NVIDIA Drivers and Ollama
17:43 - Setup SearXNG
33:15 - ComfyUI Setup
49:43 - ComfyUI Tutorial and Basics
1:09:59 - Tools Setup
Check out my GitHub repository for the full setup and links to all tools: https://github.com/Teachings/AIServerSetup
**Model Resources:**
- [RealVisXL Model](https://civitai.com/models/139562/realvisxl-v50)
- [Model Rankings](https://imgsys.org/)
Don't miss out on this unique tutorial—no one else is showing this uncensored AI image generation integration!"


Get ready to master Webmin on Ubuntu 22.04! In this easy-to-follow tutorial, I'm Josh from KeepItTechie, and I'll guide you through every step of installing Webmin. Perfect for beginners and pros alike!
From updating your system to configuring your firewall, we've got it all covered. You'll be managing your server like a pro in no time!
👉 What's inside:
Introduction to Webmin and its benefits
Step-by-step installation instructions
Tips for accessing and using Webmin
Firewall configuration for secure access
❓ Questions? Drop them in the comments!
👍 Like and subscribe for more awesome Linux guides. Let's dive into the world of server management with ease and confidence! #Webmin #Ubuntu2204 #LinuxTutorial"
Linux Operating System | Beginners Crash Course - 3 Hours
https://youtu.be/BgGeGVqgt0s
Rocky Linux by CIQ: https://ciq.co/rocky-linux/
Remember to Like, Share, and Subscribe if you enjoyed the video! Also, if you are interested in more Linux content, please consider becoming a channel member so I can continue to produce great content!
✔️RECOMMENDED LINUX BOOKLIST
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Linux Pocket Guide: Essential Commands: https://amzn.to/3xGPvsK
CompTIA Linux+ Certification All-in-One Exam Guide: Exam XK0-004 https://amzn.to/3uQ3wmh
101 Labs - CompTIA Linux+ https://amzn.to/3vtj7rb
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Easy System Administration Web Interface Raspberry Pi with Webmin! In this video i will be showing you how to setup your raspberry pi as a web administration system using Webmin. #raspberrypi #webmin #sstec tutorials.
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I hope you enjoy/enjoyed the video. If you have any questions or suggestions feel free to post them in the comments section!
Disclaimer: This video description may contain some affiliate links. If you use these links to buy something we may earn a commission. Also, all the information which are provided in our videos is only for educational purposes and informational purposes. I will not be responsible for any of your actions. Thanks!


We build a Generatively Pretrained Transformer (GPT), following the paper "Attention is All You Need" and OpenAI's GPT-2 / GPT-3. We talk about connections to ChatGPT, which has taken the world by storm. We watch GitHub Copilot, itself a GPT, help us write a GPT (meta :D!) . I recommend people watch the earlier makemore videos to get comfortable with the autoregressive language modeling framework and basics of tensors and PyTorch nn, which we take for granted in this video.
Links:
- Google colab for the video: https://colab.research.google.....com/drive/1JMLa53HDu
- GitHub repo for the video: https://github.com/karpathy/ng-video-lecture
- Playlist of the whole Zero to Hero series so far: https://www.youtube.com/watch?v=VMj-3S1tku0&list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ
- nanoGPT repo: https://github.com/karpathy/nanoGPT
- my website: https://karpathy.ai
- my twitter: https://twitter.com/karpathy
- our Discord channel: https://discord.gg/3zy8kqD9Cp
Supplementary links:
- Attention is All You Need paper: https://arxiv.org/abs/1706.03762
- OpenAI GPT-3 paper: https://arxiv.org/abs/2005.14165
- OpenAI ChatGPT blog post: https://openai.com/blog/chatgpt/
- The GPU I'm training the model on is from Lambda GPU Cloud, I think the best and easiest way to spin up an on-demand GPU instance in the cloud that you can ssh to: https://lambdalabs.com . If you prefer to work in notebooks, I think the easiest path today is Google Colab.
Suggested exercises:
- EX1: The n-dimensional tensor mastery challenge: Combine the `Head` and `MultiHeadAttention` into one class that processes all the heads in parallel, treating the heads as another batch dimension (answer is in nanoGPT).
- EX2: Train the GPT on your own dataset of choice! What other data could be fun to blabber on about? (A fun advanced suggestion if you like: train a GPT to do addition of two numbers, i.e. a+b=c. You may find it helpful to predict the digits of c in reverse order, as the typical addition algorithm (that you're hoping it learns) would proceed right to left too. You may want to modify the data loader to simply serve random problems and skip the generation of train.bin, val.bin. You may want to mask out the loss at the input positions of a+b that just specify the problem using y=-1 in the targets (see CrossEntropyLoss ignore_index). Does your Transformer learn to add? Once you have this, swole doge project: build a calculator clone in GPT, for all of +-*/. Not an easy problem. You may need Chain of Thought traces.)
- EX3: Find a dataset that is very large, so large that you can't see a gap between train and val loss. Pretrain the transformer on this data, then initialize with that model and finetune it on tiny shakespeare with a smaller number of steps and lower learning rate. Can you obtain a lower validation loss by the use of pretraining?
- EX4: Read some transformer papers and implement one additional feature or change that people seem to use. Does it improve the performance of your GPT?
Chapters:
00:00:00 intro: ChatGPT, Transformers, nanoGPT, Shakespeare
baseline language modeling, code setup
00:07:52 reading and exploring the data
00:09:28 tokenization, train/val split
00:14:27 data loader: batches of chunks of data
00:22:11 simplest baseline: bigram language model, loss, generation
00:34:53 training the bigram model
00:38:00 port our code to a script
Building the "self-attention"
00:42:13 version 1: averaging past context with for loops, the weakest form of aggregation
00:47:11 the trick in self-attention: matrix multiply as weighted aggregation
00:51:54 version 2: using matrix multiply
00:54:42 version 3: adding softmax
00:58:26 minor code cleanup
01:00:18 positional encoding
01:02:00 THE CRUX OF THE VIDEO: version 4: self-attention
01:11:38 note 1: attention as communication
01:12:46 note 2: attention has no notion of space, operates over sets
01:13:40 note 3: there is no communication across batch dimension
01:14:14 note 4: encoder blocks vs. decoder blocks
01:15:39 note 5: attention vs. self-attention vs. cross-attention
01:16:56 note 6: "scaled" self-attention. why divide by sqrt(head_size)
Building the Transformer
01:19:11 inserting a single self-attention block to our network
01:21:59 multi-headed self-attention
01:24:25 feedforward layers of transformer block
01:26:48 residual connections
01:32:51 layernorm (and its relationship to our previous batchnorm)
01:37:49 scaling up the model! creating a few variables. adding dropout
Notes on Transformer
01:42:39 encoder vs. decoder vs. both (?) Transformers
01:46:22 super quick walkthrough of nanoGPT, batched multi-headed self-attention
01:48:53 back to ChatGPT, GPT-3, pretraining vs. finetuning, RLHF
01:54:32 conclusions
Corrections:
00:57:00 Oops "tokens from the _future_ cannot communicate", not "past". Sorry! :)
01:20:05 Oops I should be using the head_size for the normalization, not C


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🎬 *Table of Contents*
00:00 Intro
00:31 Make an AI Clone
01:09 Steps before recording sample video
02:08 Upload your sample video
04:18 Record your own voice & generate video
05:35 Download the video
05:47 Check the pricing plan
06:30 Get better result using finetune feature
Step into the future of video creation with this comprehensive guide to create your own AI clone using HeyGen Labs! Learn how to transform a simple video clip into a lifelike, talking avatar that lip-syncs to your voice seamlessly.
By the end of this video, you'll be ready to create your own stunning AI clone with HeyGen, opening up a world of creative possibilities for presentations, social media, marketing, and more!
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AI is not a one-size-fits-all technology; every AI project is customized to solve a specific business problem, with machine learning models. These models, which rely on data and algorithms, are what address the project’s needs. There are seven steps to building an effective machine learning model, from understanding the business problem, to preparing data, to adjusting the model in operation.
🔎 Read more:
Detailed explanation ➡️ https://www.techtarget.com/sea....rchenterpriseai/feat
Ease data preparation process with organization and automation➡️ https://searchdatamanagement.t....echtarget.com/featur
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Work with David directly: https://gvw0h8ku6fc.typeform.com/to/oSg694t1 (limited to 5 people)
Do you want to join my team? Apply here: https://forms.gle/2iz4xmFvDCGnj2iZA
Access my code, templates and prompts inside of my community: https://www.skool.com/new-society
Follow me on Twitter - https://x.com/DavidOndrej1
My Google Colab: https://colab.research.google.....com/drive/1KHNjYT485
Andrej Karpathy Speech: https://youtu.be/fqVLjtvWgq8?si=77uSX3-jG6A6uecR
Sam Altman on GPT-5: https://twitter.com/H0wie_Xu/s....tatus/17456579924592
Please Subscribe.
Credits: @maya-akim @matthew_berman @BuildNewThings
AI Agents are the next big thing - and how to build your very own AI agent with Crew AI.


Want to learn Generative AI? Attend the FREE Intro to Generative AI Masterclass here : https://shorturl.at/fCQZ6
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100xengineers Twitter :https://twitter.com/100xengineers


AI art is leaking into the mainstream in the form of stable diffusion and Lensa, but there are serious ethical concerns with this unregulated tech. I'm NOT anti AI, in fact, I believe AI can be of immense benefit to us in the future. But the ethics of AI in its current state MUST be talked about, in order to steer this tech in the right direction. Leave ur thoughts in the comments below!
Thumbnail art by the amazing @ CaraidArt on twitter
Check out Steven Zapata's GREAT VIDEO on the dangers of AI: https://youtu.be/tjSxFAGP9Ss
✨ Monthly tutorials on my Patreon: https://www.patreon.com/samdoesarts
🤩 my Prints: https://www.inprnt.com/gallery/samdoesarts/
⭐️ my instagram: https://www.instagram.com/samdoesarts/
💫 Gumroad shop: https://gumroad.com/samdoesarts


Want to learn more? I’m launching a 6-week live BootCamp for AI Builders.
👉 Learn more: https://maven.com/s/course/13437a45a7
Save 50% at checkout with the code FOUNDER50
This is the 6th video in a series on using large language models (LLMs) in practice. Here, I review key aspects of developing a foundation LLM based on the development of models such as GPT-3, Llama, Falcon, and beyond.
More Resources:
▶️ Series Playlist: https://www.youtube.com/playli....st?list=PLz-ep5RbHos Read more: https://towardsdatascience.com..../how-to-build-an-llm
[1] BloombergGPT: https://arxiv.org/pdf/2303.17564.pdf
[2] Llama 2: https://ai.meta.com/research/p....ublications/llama-2-
[3] LLM Energy Costs: https://www.statista.com/stati....stics/1384401/energy
[4] arXiv:2005.14165 [cs.CL]
[5] Falcon 180b Blog: https://huggingface.co/blog/falcon-180b
[6] arXiv:2101.00027 [cs.CL]
[7] Alpaca Repo: https://github.com/gururise/AlpacaDataCleaned
[8] arXiv:2303.18223 [cs.CL]
[9] arXiv:2112.11446 [cs.CL]
[10] arXiv:1508.07909 [cs.CL]
[11] SentencePience: https://github.com/google/sent....encepiece/tree/maste
[12] Tokenizers Doc: https://huggingface.co/docs/tokenizers/quicktour
[13] arXiv:1706.03762 [cs.CL]
[14] Andrej Karpathy Lecture: https://www.youtube.com/watch?v=kCc8FmEb1nY&t=5307s
[15] Hugging Face NLP Course: https://huggingface.co/learn/n....lp-course/chapter1/7
[16] arXiv:1810.04805 [cs.CL]
[17] arXiv:1910.13461 [cs.CL]
[18] arXiv:1603.05027 [cs.CV]
[19] arXiv:1607.06450 [stat.ML]
[20] arXiv:1803.02155 [cs.CL]
[21] arXiv:2203.15556 [cs.CL]
[22] Trained with Mixed Precision Nvidia: https://docs.nvidia.com/deeple....arning/performance/m
[23] DeepSpeed Doc: https://www.deepspeed.ai/training/
[24] https://paperswithcode.com/method/weight-decay
[25] https://towardsdatascience.com..../what-is-gradient-cl
[26] arXiv:2001.08361 [cs.LG]
[27] arXiv:1803.05457 [cs.AI]
[28] arXiv:1905.07830 [cs.CL]
[29] arXiv:2009.03300 [cs.CY]
[30] arXiv:2109.07958 [cs.CL]
[31] https://huggingface.co/blog/ev....aluating-mmlu-leader
[32] https://www.cs.toronto.edu/~hi....nton/absps/JMLRdropo
--
Homepage: https://shawhintalebi.com/
Book a call: https://calendly.com/shawhintalebi
Intro - 0:00
How much does it cost? - 1:30
4 Key Steps - 3:55
Step 1: Data Curation - 4:19
1.1: Data Sources - 5:31
1.2: Data Diversity - 7:45
1.3: Data Preparation - 9:06
Step 2: Model Architecture (Transformers) - 13:17
2.1: 3 Types of Transformers - 15:13
2.2: Other Design Choices - 18:27
2.3: How big do I make it? - 22:45
Step 3: Training at Scale - 24:20
3.1: Training Stability - 26:52
3.2: Hyperparameters - 28:06
Step 4: Evaluation - 29:14
4.1: Multiple-choice Tasks - 30:22
4.2: Open-ended Tasks - 32:59
What's next? - 34:31


Dave explains the reasons why and the steps needed to set up your own local AI engine ala ChatGPT. For my book on the autism spectrum, check out: https://amzn.to/3zBinWM
Helpful links and tips:
Install ollama:
curl -fsSL https://ollama.com/install.sh | sh
ollama serve
WSL Kernel Update Package: https://learn.microsoft.com/en....-us/windows/wsl/inst
Run the UI Docker Container:
Run UI with Docker:
docker run -d -p 3000:8080 --gpus=all -v ollama:/root/.ollama -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:ollama


Join the fastest growing AI education platform and instantly access 20+ top courses in AI: https://bit.ly/skillleap
Mistral has release a free AI agent builder, powered by their large language model, Mistral Large 2.
With this agent builder, you can build a custom AI chatbot with your own set of instructions and prompt examples.
These AI agents are similar to Custom GPTs on ChatGPT and Projects inside of Claude, but you do not need a subscription to create them, use them or share them.
You can build your own AI agents here: https://chat.mistral.ai/chat
Use this GPT to create a system prompt: https://chatgpt.com/g/g-2Vxwgp....MMk-custom-instructi


Join the AI Filmmaker Academy Today!
Unlock 40% off with coupon YOUTUBE40 —limited time only.
Create stunning AI movies for under $60.
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0:00 - Introduction to AI Video Creation
1:34 - Getting Started with Pix Firste
3:03 - Creating and Uploading Characters
6:08 - Crafting Effective Video Prompts
12:09 - Tips and Limitations of Pix Firste
15:17 - Exploring Different Outputs with Seed Variations
16:30 - Tips for Optimizing AI Video Animation
19:01 - Using Cinemagraphs and Other Animation Techniques
25:23 - Enhancing Videos with Music and Editing
Try it out now here today.
https://app.pixverse.ai/create/video
Thanks to Pixverse for sponsoring this video.
📧Join my newsletter
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👨🏫Check out my AI courses:
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Create Realistic Ai Influencer for Free | AI Model Instagram 2024 | Create Your Own Ai Influencer
#aiinfluencer #aimodel #instagraminfluencer
Hello Friends! In this incredible video tutorial, you're going to explore realistic AI creation and its impact. We'll show you the process of making amazingly impressive AI influencer profiles, as well as videos that make you doubt the truth of. From gathering sources to making breathtaking video and even face-changing, this class will change your understanding of artificial intelligence. If you're an experienced techie or just interested in AI's capabilities, AI this video tutorial should be watched. Learn the hidden secrets behind AI and allow people to convey their condolences. Let's look at what's coming the next step for influencer culture and AI imagination!
How to create a realistic AI influencer for free using only AI tools. I have used AI tools like Tensor Art, Insight Face bot, and Google Colab to create AI Instagram models and earn money through Instagram channel.
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
Step to Create Ai Influencer 🔗Links:
👌STEP-01➡️
TensorArt: https://tensor.art/
Demo Model: https://tensor.art/images/700972640476656117?model_id=700914916103796439
👌STEP-02 ➡️
Discord: https://discord.com/channels/@me
Face Swap: https://discord.com/oauth2/authorize?client_id=1090660574196674713&permissions=274877945856&scope=bot
👌STEP-03 ➡️
Google Colab: https://colab.research.google.....com/gist/trickydaya/
👌STEP-04 ➡️
🖼️Free Webste to Download Images & Videos:
a) Freepik: https://www.freepik.com/
b) Pexels: https://www.pexels.com/
c) Pixabay: https://pixabay.com/
d) Coverr: https://coverr.co/
🖼️Paid Webste to Download Images, Videos & Templates:
a) Envatoelements: https://elements.envato.com/
b) Storyblocks: https://www.storyblocks.com/
c) Istocks: https://www.istockphoto.com/
d) Shutterstock: https://www.shutterstock.com/
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
👧To Create Realistic AI Influencers Timestamps:
00:00 - Introduction
00:48 - Create Realistic AI Influencer Roadmap
01:33 - Generate Realistic AI Influencer Using Tensor Art
03:48 - AI Generated Pictures
04:07 - How to Generate face swap Images from same AI Influencer's face
04:38 - Face Swap Using Insight Face Bot
05:18 - How to Download Pictures and Videos
06:10 - Generate Instagram Reels & Videos Using Google Colab AI
07:04 - Create Instagram Account
07:08 - Create AI Influencer's Bio & Post
07:19 - Conclusion
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👍Aaditri Official Instagram ID: https://www.instagram.com/aaditritheai/
⚠ Disclaimer:
I don't recommend using videos of other people for deepfakes. Try to make them yourself; ask your girlfriend, sister, mother, or anyone on Fiverr to do it. It was shown in the tutorial to demonstrate the capabilities of AI.
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👍Credit:
Instagram links: https://www.instagram.com/naina_avtr/?hl=en
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🌐 Stay Connected:
▶YouTube: www.youtube.com/@theailearning
▶Twitter: https://twitter.com/theailearning
▶Facebook: https://www.facebook.com/theailearning
▶Instagram: https://www.instagram.com/theailearning
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📺 Related Videos:
📹AI Infographic Generator form Text: https://youtu.be/fEtMYjXPItc
📹How to Create Realistic AI Influencer From Shakker AI: https://youtu.be/1Wp2ToHSNnA
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