The Computer Dudes Inc

Fall Weather is finally Arriving!!   Here is your update from Computer Dudes for Fall 2027

As with all other Technology Companies our focus including products and services change quite rapidly.   This article briefly reviews where we are and current operations. 

It is a terrible thing, but unless one is corrupt, one can not make money or even do research here in the United States in 2026

To solve this issue - we moved our research and headquarters to European Nations we are friends with - Nations that are Strong Militarily and Economically. 

Somewhere with better quality healthcare.

Unlike the "Tech Bros" and their President no one was fired, demoted, or took a pay cut.

When the Rule of Law and the US Constitution are back in effect we will transfer back to America.

Some will find this funny - some will cheer us leaving - but we are like Ukraine - we have the technology you need to survive and protect the USA.   

The country that wants us most, and is most honest, may receive our Global Operations headquarters.   Discussions are underway.  :)

Everything to help you will continue to be posted on this and other websites.   Also our research, development, prototyping, testing, and production methods will go faster without all the interruptions and other problems here in the USA now. 

Those of you who think this is too difficult or expensive to do - are wrong.    We already have friends and companies we work with there and around the world.

Sincerely,

Todd W. Byars
Computer Dudes
Global Operations and Services
Homebase: Tallahassee, Florida, USA 

The Computer Dudes, Inc. has been working on a different approach to AI for several years now.

We have also been working with AI running on much less power hungry computers and data centers.

The chart shows where the leading Generative AI companies are at, the name of their product, and much more.

Our version is a modified Llama Open Source with OUR programming for the human interface and for AI responses that include senses and emotions. Our programming method is based on Human DNA being converted to computer code modules or arrays that work with different versions of AI.

As far as we know we are the only company working with DNA to Code and a true AI.

I hope you enjoyed this little update - personally I find the evolution of generative AI and real AI to be fascinating.

Please share - especially with other computer techs, engineers, and companies.

Sincerely,

Todd Byars
Computer Dudes Global Operations and Services
Tallahassee, Florida, USA

Epstein.

Its's a word, but its more than a word.   It's an Idea, a Statement, a Symbol, a Hook. Like a Train Whistle, that gets everyone's attention.

For the last week we have been posting statements like this:

'Lets have a little fun. Like at a party.

When I say "Epstein"
You say "Epstein!"

Epstein.

Copy, paste, repost, post across all social networks.

Enjoy,

Todd W. Byars
Tallahassee, Florida, USA
**1**'

and of course we have been posting or "answering" posts of Epstein with Epstein.

We have done this for several reasons, and after you look at the reasons - we would like to ask you to join us.  :)

A) As An Experiment to see how many would see the postings and respond given no mass media support.
B) To see which Social Network would respond the most.
C) To see if it would cross between networks.
D) To use as an attention signal with a wordcode or number code behind it. 
E) Signal in Signal (More on this Shortly.)

Aside from the Experiment listed above we have done this to:

1) Make "Epstein" just go "viral" as a comment, and statement, on "The Epstein List" and its  "Open Coverup."
2) To make the statement that WE are all aware of what was done in the past, and has been done recently.
3) To get everyone's attention focused on one thing as they are being bombarded with more "distractions and lies."

So again, we hope you will join us. 

Results:
This was not an official experiment more a testing of the "Waters" on Internet / Social Network adverstising with words that get people's attention and how many of them responded.

The short posts with instructions received the most reaction.    We did 4 of those.    They received about 50 likes, 34 shares, and 30 postings of just "Epstein."
We also did about a week of just posting "Epstein" which received 36 likes and 54 "reply" postings of just the word "Epstein."

The experiment was a success proving one can share words and phrases to spread advertising or other information.   We proved that we could get views, reactions, and shares without paying for advertising.   

Conclusions:   Words and Phrases can be used to inform and spread information without spending dollars on advertising.   Also the response to these words and phrases grows in size with distribution - again - with no dollars spent to get people involved and sharing content.

This is the end of this experiment.   We may try more experiments with spreading information across the Social Media in the future.   We hope you found some of this useful.

Remember, when I say Epstein, you Say Epstein.   "Epstein."

Thank you!  :)T

Let's start with a bit of History and the evolution of High Power Consumption Computers and Data Center as well as our research over the decades.

The Computer Dudes, Inc has been a leader in low power Single Board Computer research and design since the company's founding in 1997. At that time we were using Intel 486 single board computers that were about the size of an ISA Sound or Ethernet Card. The rest of the world was still using huge ISA type motherboards that required a "card" for each function such as Video Card, Sound, Ethernet, Modem, Printer, Hard Drive Controller or others.

As "Moore's Law" progressed Single Board Computers, SBC's, grew smaller, more powerful and required less power.

The advent of the Raspberry Pi series rapidly expanded our work in this area and by the Raspberry Pi 4 we were able to run the equivalent of "full sized computers" off a single RPI 4.

During the evolution of the Raspberry Pi series SBC's we worked on Clustering to increase power and to build servers that were essentially modular so more "nodes" could be added to increase power and performance. We also experimented with using Cloud Architecture to increase the speed, however, we quickly determined that "cloud architecture" was not secure.

In the late 2000's we began developing custom flat and then circular "computer cores" to hold each of the SBC's instead of standard tower or rack mounted server designs. The computer cores too up much less space, were lighter, and allowed for easier maintenance and repair.

In the 2010's we began designing custom computer cases and DC power supplies for our Computer Cores - including "Outdoor" solar and battery powered computers and super computers.

in the early 2020's we designed the worlds first Off Grid, Outdoor, No Building Required Computers - the "Solar One Monoliths." The Solar One Monoliths are made of Granite, Glass and Steel to hold the round 3D printed Computer Cores and were run off custom DC Solar and Battery Power Systems.

By 2022 we had built the worlds first "Monolithic Data Center" for off grid operation with multiple options for internet connectivity. These required no building and the first one is still in place at our headquarters / lab in Tallahassee, Florida, USA

Flash Forward to 2025 - High Power Consumption Data Centers with the "wrong architecture" and unbelievably high power consumption for Large Language Model, LLM, "Generative" AI's arose as a global problem. In our view the power consumption as well as cost in dollars is not sustainable.

To solve that problem we have now used the Raspberry Pi 5 series, in clusters, to create LLM Generative AI's. Below is our first publication on this work along with a "How To" guide. This document is "Open Source" and we have already progressed to the next level.

You can use the information below to build your own - or you can contact The Computer Dudes, Inc. (www.thecomputerdudesinc.com/index.php) to purchase a custom version or the newest version we are working on.

Now we are happy to present to you and the world - How to build a LLM Generative AI using clustered Raspberry Pi 5's and Alpaca 7B

Running Alpaca 7B on a Raspberry Pi 5 Beowulf cluster of 10 Pi 5s.

This example won’t give you true LLM-level performance like an A100 GPU, but it can distribute the workload using parallel processing without power hungry GPU's.

Here is how to setup a basic Generative LLM AI using only 10 clustered Raspberry Pi 5's. Build this version first then use it for testing and to design the next version using hundreds, or thousands, of Raspberry Pi 5 nodes or clusters.

Architecture:
Alpaca 7B (quantized, 4-bit GGUF) on a 10-node Raspberry Pi 5 cluster, with:
A master node (master controller)
9 worker nodes (inference or supporting roles)
Shared filesystem (via NFS or rsync)
Parallelized inference using llama.cpp or llm.cpp + custom sharding/load-balancing logic

Hardware & Network:
10x Raspberry Pi 5 (8GB)
10x MicroSD cards (32GB+)
1x Gigabit switch + Ethernet cables (avoid Wi-Fi bottlenecks)
1x USB SSD for model storage (shared or on each node)
Active cooling on all units (very important)
For the smallest footprint: PoE HATs + PoE switch for power and networking (like a backplane when used in a cluster)

Network Topology:
Assign static IPs to each node.
Node naming convention: pi-master, pi-node01, ..., pi-node09

Software Stack:
Component Description
OS Raspberry Pi OS 64-bit (Lite preferred)
MPI Message Passing Interface: OpenMPI
llama.cpp Inference engine: OpenBLAS
GGUF Model Alpaca 7B quantized (4-bit recommended)
Optional Python + Flask/Gradio for web API

SETUP Procedure:

STEP 1: Flash and Configure Raspberry Pi OS
Flash 64-bit Raspberry Pi OS Lite onto each Pi:
Set hostname: /etc/hostname
Set static IP: /etc/dhcpcd.conf
Enable SSH

Update:
How To:
bash
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sudo apt update && sudo apt upgrade -y
Repeat for each Pi.

STEP 2: Set Up the Master Node
On pi-master
How To:
Install dependencies
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sudo apt install git build-essential cmake libopenblas-dev libomp-dev openmpi-bin openmpi-common libopenmpi-dev -y
Create SSH key and distribute it:
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ssh-keygen -t rsa
for i in {1..9}; do ssh-copy-id pi-node0$i; done

STEP 3: Set Up Shared Filesystem
Option A: NFS Share (on pi-master)
How To:
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sudo apt install nfs-kernel-server -y
sudo mkdir /mnt/share
sudo chown pi:pi /mnt/share
echo "/mnt/share *(rw,sync,no_subtree_check)" | sudo tee -a /etc/exports
sudo exportfs -a
sudo systemctl restart nfs-kernel-server
Mount on worker nodes (pi-node01 → pi-node09)
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sudo apt install nfs-common -y
sudo mkdir /mnt/share
sudo mount pi-master:/mnt/share /mnt/share

STEP 4: Build llama.cpp with MPI Support on all nodes
How to:
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git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
mkdir build && cd build
cmake -DLLAMA_OPENBLAS=on ..
make -j4
OR for more rapid setup: create an automated deploy script using rsync from pi-master.

STEP 5: Download and Distribute Alpaca 7B GGUF on the master node:
How to:
Download from: https://huggingface.co/TheBloke/alpaca-7B-GGUF
Choose alpaca-7b-q4_0.gguf (4-bit quantized)
Store in /mnt/share/models/ or replicate to all nodes

STEP 6: MPI Configuration File
On pi-master, create hosts.txt:
How To:
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pi-node01 slots=4
pi-node02 slots=4
pi-node03 slots=4
pi-node04 slots=4
pi-node05 slots=4
pi-node06 slots=4
pi-node07 slots=4
pi-node08 slots=4
pi-node09 slots=4
You can also include pi-master if you want it to join inference.

STEP 7: Run Distributed Inference - Cluster and command testing
Using OpenMPI to broadcast simple load across cluster:
How To:
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mpirun -np 40 --hostfile hosts.txt ./main -m /mnt/share/models/alpaca-7b-q4_0.gguf -n 64 -t 4 -p "Instruction: What is gravity?nnResponse:"
-np 40: Total CPU threads across nodes
-t 4: Threads per node
Please Note: llama.cpp does not support true model sharding yet. You're parallelizing at a token/request level, not at transformer layer level.

STEP 8: Build a Web API Interface for control and configuration. (experiment here)
Install Flask (on pi-master):
How To:
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sudo apt install python3-pip -y
pip install flask
Create a simple Flask app that:
Accepts prompts
Sends them to available nodes via SSH or socket
Returns the response
You can expand this to include:
Load balancing (round robin)
Node health check
Token-based rate limiting

Performance Issues and Solutions:
Issue                       Workaround
Sharding                  Use batching across requests
RAM pressure         Use 4-bit quantized models
Latency                   Optimize thread count, cooling
IO bottlenecks         Use SSD and avoid SD cards
Python bottlenecks  Use Rust/C++ for inference layer

Expectations:
10 Pi 5s won't give near-GPU speeds but they can handle the load by using multiple cores and parallel processing
You can handle small workloads in parallel.
Best used for offline chatbot, local research, or LLM experimentation and design
Performance: 5–15 tokens/sec depending on load & optimization.

10 Pi Version is for configuring and testing - then add Pi to nodes or additional clustered Pi Nodes to improve performance and capabilities.

Options:
A Python or Bash wrapper that uses SSH to distribute jobs
A Flask/Gradio-based frontend to your cluster
An auto-scaling job scheduler with Pi health monitoring

FINAL NOTE:  If you do not like the Raspberry Pi series SBC's or prefer an Intel Chipset you can do the same thing with just about any other brand of Single Board Computer.

Are you a Computer Dude? v1.1  

Start Program

Query: Are you a Computer Dude?  ( text box with: Yes or No)

Comment: Dude is a pronoun used to describe a level of skill not a gender. Dude means you are good at what you do an do not have to be watched by others.  ( text box: 800 pixils wide by 200 pixils)

End Program