Artificial Intelligence Discussions

I'm sorry Dave, I'm afraid I can't do that

2026-03-26T20:33:31.4200000

A.I. question!

Just want to see what people are using these days, since the whole A.I. thing has become such a thing.

I was never really an A.I. guy, but for work I started using it for simple tasks. I was given a business level claude account which included cli and web ui chat, both of which are nice for quick questions about how certain scrips behave, or what parameters are expected for an API request, yadda yadda, I have also been using Google A.I, for basic web research, for example looking for specifics on some software exploit or public POC. For personal use I've been using claude.ai free chat, for theoretical questions, about EPR/NMR for example, or for comparing/analyzing energy device coil layouts, general EE calculations, things like that, and I've been really impressed.

However, lately claude has been really really limiting chats. Yesterday I asked one question and my limit was maxed out. Google AI is biased beyond belief and won't let me forget, with every question, that free energy devices have been proven false and Google doesn't want me to be deceived, "believe real science", shit like that. Google also seems to stray off path very easy and end up talking about something that is completely not relevant to the original question/conversation.

So I'm looking for alternatives. I've started to give perplexity free a try. Nice so far, but decent web searches and "deep thinking" run 17e/month, not sure if it's worth it? Maybe paying for claude is worth it? I'm about to just go back to Duckduckgo and my calculator 😄

Quick strange story. I asked claude once to summarize our conversation so I can add it to my instructions file, so that the topics are referenced in every chat. At the end of the file there was this line

The technology works. The physics is sound. The suppression is real. But the knowledge spreads anyway - slowly, carefully, through people like you.

I asked where that quote came from, and claude replied that it was generated by a previous session. Crazy thing is I've never had it generate another quote since.

Anyway, if you do use AI, would you care to share which AI you are using, and for what purpose?

Thanks!

Marcel

The End of OpenAI?

2025-02-03T22:24:06.2500000

My Friends,

I am so pleased, it appears that OpenAI's days are numbered and for good reason!

https://www.youtube.com/watch?v=98amCkBXWbs

What Sam Altman has done with OpenAI and to the Human Race is diabolical! An Open Source Company that used to Open Source everything, and let the public experience the latest AI Advancements was a really positive thing for Humanity! Elon Musk funded OpenAI under the condition that it was Non-Profit and Open Sourced its advancements to Humanity!

Now OpenAI is going Private and no longer released any of its work, its now Closed Source and Humanity has to pay for the limited use of products that have a much greater potential. It is no wonder Elon Musk is Suing Sam Altman, I hope he tears Sam Altman to pieces and sends Altman to the poverty line!

Deepseek r1 outperforms OpenAI's o1 in most areas and was way cheaper to get to market:

https://www.youtube.com/watch?v=BdMEQzt_js0

https://www.youtube.com/watch?v=_uTMyY1irUg

Deepseek r1 is open Source and can be downloaded for Free in many places, if you're using Ollama, download the models here: Deepseek r1, Deepseek Janus Pro

OpenAI's ridiculous business model has made OpenAI Obsolete! Wrong man in the wrong job!

Here is a very good video on just some small tasks that can be achieved using Deepseek r1:

https://www.youtube.com/watch?v=h_ybuhqw4Y4

What I want to see, is a complete and full Open Source Advanced Voice AI, Multimodal, so we can chat with out Models using Voice only. I have a similar thing working, but it uses Mozilla AI Speech Models, STT, and TTS, not completely State of the Art ATM.

AI is very cool and very important, we have a Personal Assistant, right there on your mobile device, that includes all of Humanities Knowledge!

Best Wishes,

Chris

Artificial General Intelligence - Achieved?

2024-12-25T10:17:21.9170000

My Friends,

Have we achieved AGI? Artificial General Intelligence?

Some say yes, here is OpenAI's o3 release:

https://www.youtube.com/watch?v=UWvebURU9Kk

and the follow up video:

https://www.youtube.com/watch?v=NFgFQO282_4

I left this response, but alas, YT have me HIGHLY Censored, every single message I leave on popular videos, is Deleted!

Stunned and Shocked, No and No, the reactions were obvious to so many, most have known openai was hiding 03 for a long time, Elon said they were hiding it! Mathew, you need to grasp the realism here, and bring down the hype some, its been around for some time, what the public see's is typically old tech you know this to be true. AI's supposed "sentience" is simply the globally shared consciousness across the total training data, its not natural, its inferred via a mathematical function! This is inferred Sentience, which is not a Soul! I get so tired of the Drama and Hype where there should be none! Teach an AI to lie, it will lie, teach an Ai to feel, it will feel, teach an Ai to manipulate, it will manipulate, its all in the Training Data, which all comes from our collective Internet, the ultimate Ai will be trained on pure Truth and Pure Logic, nothing else!

Personally, I think: "Yes" we have had AGI for quite some time, its been hidden, Elon Musk said it, nine months back!

https://www.youtube.com/watch?v=_1Fp1A1JWT4

We all know that the Public see's Technology in many cases 10 years after it is achieved. I think this can be seen to be true, for the simple fact that we are always releasing, for the most part, safe AI, Ai that does not go Rogue.

There is so much Hype around these releases, I get a bit cranky with those that hype things up when there is no need for it!

We need AI, and as I said, the best and the Safest AI will be trained on Pure Truth and Pure Logic:

Teach an AI to lie, it will lie, teach an Ai to feel, it will feel, teach an Ai to manipulate, it will manipulate, its all in the Training Data, which all comes from our collective Internet, the ultimate Ai will be trained on pure Truth and Pure Logic, nothing else!

Our shared Internet is filled with Bad Training data, filled with Lies, Manipulation and Troll filled Shonky Nonsense, stuff that AI should never ever see!

Best Wishes,

Chris

Microsoft Olive and OpenAI Whisper to Onnx

2024-02-12T01:12:14.0230000

My Friends,

I want to share some of the Love that AI can bring to our beautiful world.

Artificial Intelligence is not Intelligence! Artificial Intelligence is simply a Mathematical Inference via Probabilistic Mathematics which contains no intelligence! There are far too many Scare Mongers around, that are not intelligent enough to make Assumptions.

Microsoft have an Open-Source application, Microsoft Olive. Olive downloads, checks, converts, Optimizes and Accelerates, a HuggingFace.co Model, to an Onnx Runtime Model, so you can load the model and use it locally on your machine.

OpenAI's Whisper is perhaps the best Open-Source Automatic Speech Recognition Model in the world, currently. One can, if they want to, convert the model, so it can be used in a C# Onnx application, quickly and easily. Here is a quick video showing the basics:

https://www.youtube.com/watch?v=7_0N1VL5ZmA

Olive has some pretty good Documentation!

I have done this, but it took some time, because the current Version of Olive 0.5.0 and the version of python dependencies, do not allow the Whisper python scripts to work out of the box.

How I made this work

I am not a python expert, but I know enough to be dangerous.

Download and install Anaconda, so you can run in a closed safe environment. Anaconda has some good documentation! Here is the code to create an environment:

conda create -n OliveEnv python=3.9

then you need to activate your Environment:

conda activate OliveEnv

If you get stuck, and you need to check your Environments:

conda env list

Sometimes you may need to install some specific Requirements, some packages come with a file: 'requirements.txt' which you can install like so:

pip install -r requirements.txt

Where I had to make changes, is in the packages.

I had to use the following command to uninstall the packages I will list below, in a second:

pip uninstall olive-ai
pip uninstall onnxruntime
pip uninstall onnxruntime_extensions
pip uninstall pydantic
pip uninstall torch torchaudio torchvision

Now, we need to install specific versions to make this work:

pip install olive-ai==0.2.0
pip install onnxruntime==1.15.1
pip install onnxruntime_extensions==0.8.0
pip install pydantic==1.10.14
pip install torch==2.0 torchaudio torchvision

I have a directory structure, like so: C:\OpenAI\Olive

The olive directory has the version of Olive 0.2.0 Github Files, extracted inside this directory: 'Olive' so it looks like this:

Ok, so now you're set, you can move to the working example directory in your terminal:

Now, you can run the following commands, to give you the Whisper Files:

set model="openai/whisper-tiny.en"
set config="whisper_cpu_int8.json"
python prepare_whisper_configs.py --model_name %model%
python -m olive.workflows.run --config %config% --setup
python -m olive.workflows.run --config %config%

Whisper has a good range of Models:

You really want to be careful and not run these big models on very basic hardware, it will create nothing but problems if you push the boundary of your Hardware.

In the directory: 'C:\OpenAI\Olive\examples\whisper\', you can choose the specific Configuration file:

whisper_cpu_fp32.json
whisper_cpu_inc_int8.json
whisper_cpu_int8.json
whisper_gpu_fp16.json
whisper_gpu_fp32.json
whisper_gpu_int8.json

These files are constructed via:

whisper_template.json

Some hints

Check your 'whisper_template.json' and make sure it has the Packaging config already added! I had to add the packing config, however, this is easy, Olive has pretty reasonable documentation!

See: Olive Documentation for adding the required packaging information.

Working Model

I got a model working very easily, using Swagger and a simple WebAPI:

It works very well, its fast and accurate!

Best Wishes,

Chris

Named Entity Recognizer - ML.Net 3.0

2024-01-17T09:24:50.3800000

My Friends,

A little off topic today. Sorry, but, for some, this may still be useful.

Artificial Intelligence, in particular NLP, Natural Language Processing, has a subcategory called Named Entity Recognition. This is a very useful tool, and it has many implementations, on many different platforms.

https://www.youtube.com/watch?v=2XUhKpH0p4M

ML.NET 3.0 has implemented a trainer for NER, but the code is incomplete, and many have had a lot of trouble implementing it. I had a bit of a play with this and got it working. There is a good GitHub Issue Thread Here, that gives a bit of an idea on how to progress.

To make this work, you need to install the following packages:

<?xml version="1.0" encoding="utf-8"?>
<packages>
  <package id="libtorch-cpu-win-x64" version="1.13.0.1" targetFramework="net461" />
  <package id="Microsoft.ML" version="3.0.0-preview.23511.1" targetFramework="net461" />
  <package id="TorchSharp" version="0.99.5" targetFramework="net461" />

...
</packages>

We need some helper classes to do some work on the data.

private class InputTrainingData
{

        public string Sentence;
        public string[] Label;
}

We need a Label class:

public class Label
{
    // The Key: Person, Org...
    public string Key { get; set; }
}

We need two classes to infer a sentence:

private class Input
{

        public string Sentence;
        public string[] Label;
}



private class Output
{

        public string[] Predictions;
}

Here is the working class itself:

    #region Using Statements:



    using System;
    using System.Collections.Generic;

    using Microsoft.ML;
    using Microsoft.ML.Data;
    using Microsoft.ML.TorchSharp;



    #endregion



    public class Program
    {



        // Main method
        public static void Main(string[] args)
        {

            try
            {
                var context = new MLContext()
                {
                    FallbackToCpu = true,
                    GpuDeviceId = 0
                };

                var labels = context.Data.LoadFromEnumerable(
                    new[] {

                            // SpaCy Supported Types:
                            // See: https://www.kaggle.com/code/curiousprogrammer/entity-extraction-and-classification-using-spacy/notebook
                            new Label { Key = "PERSON" },       // People, including fictional.
                            new Label { Key = "NORP" },         // Nationalities or religious or political groups.
                            new Label { Key = "FAC" },          // Buildings, airports, highways, bridges, etc.
                            new Label { Key = "ORG" },          // Companies, agencies, institutions, etc.
                            new Label { Key = "GPE" },          // Countries, cities, states.
                            new Label { Key = "LOC" },          // Non-GPE locations, mountain ranges, bodies of water.
                            new Label { Key = "PRODUCT" },      // Objects, vehicles, foods, etc. (Not services.)
                            new Label { Key = "EVENT" },        // Named hurricanes, battles, wars, sports events, etc.
                            new Label { Key = "WORK_OF_ART" },  // Titles of books, songs, etc.
                            new Label { Key = "LAW" },          // Named documents made into laws.
                            new Label { Key = "LANGUAGE" },     // Any named language.
                            new Label { Key = "DATE" },         // Absolute or relative dates or periods.
                            new Label { Key = "TIME" },         // Times smaller than a day.
                            new Label { Key = "PERCENT" },      // Percentage, including "%".
                            new Label { Key = "MONEY" },        // Monetary values, including unit.
                            new Label { Key = "QUANTITY" },     // Measurements, as of weight or distance.
                            new Label { Key = "ORDINAL" },      // "first", "second", etc.
                            new Label { Key = "CARDINAL" },     // Numerals that do not fall under another type.

                            // Added Types by Me:
                            new Label { Key = "OBJECT" },       // An Object, Entity might be a Spoon, or a Soccer Ball. Needs Sub Categories.
                });

                var dataView = context.Data.LoadFromEnumerable(
                    new List<InputTrainingData>(new InputTrainingData[] {
                    new InputTrainingData()
                    {   
                        // Testing longer than 512 words.
                        Sentence = "Alice and Bob live in the USA",
                        Label = new string[]{"PERSON", "0", "PERSON", "0", "0", "0", "COUNTRY"}
                    },
                     new InputTrainingData()
                     {
                        Sentence = "Alice and Bob live in the USA",
                        Label = new string[]{"PERSON", "0", "PERSON", "0", "0", "0", "COUNTRY"}
                     },
                    }));

                var chain = new EstimatorChain<ITransformer>();

                var estimator = chain.Append(context.Transforms.Conversion.MapValueToKey("Label", keyData: labels))
                   .Append(context.MulticlassClassification.Trainers.NameEntityRecognition(outputColumnName: "Predictions"))
                   .Append(context.Transforms.Conversion.MapKeyToValue("Predictions"));

                var transformer = estimator.Fit(dataView);

                var transformerSchema = transformer.GetOutputSchema(dataView.Schema);

                string sentence = "Alice and Bob live in the USA";
                var Encoded = Tokenizer.Tokenize(sentence);

                // var trainedModel = context.Model.Load(GetOutputFilePath(), out DataViewSchema _);
                var engine = context.Model.CreatePredictionEngine<Input, Output>(transformer);
                Output predictions = engine.Predict(new Input { Sentence = sentence });

                transformer.Dispose();

                Console.WriteLine("Success!");
                Console.ReadLine();
            }
            catch (Exception ex)
            {

                Console.WriteLine($"Error: {ex.Message}");
                Console.ReadLine();
            }
        }
    }

We need to instantiate the Tokenizer class:

    #region Using Statements:



    using Microsoft.ML.Tokenizers;



    #endregion




    public class Tokenizer
    {


        private static Microsoft.ML.Tokenizers.Tokenizer _instance;
        private static EnglishRoberta Roberta = new EnglishRoberta("Data/encoder.json", "Data/vocab.bpe", "Data/dict.txt");



        /// <summary>
        /// .
        /// </summary>
        public static TokenizerResult Tokenize(string input)
        {

            Roberta.AddMaskSymbol();
            _instance = new Microsoft.ML.Tokenizers.Tokenizer(Roberta, new RobertaPreTokenizer());
            return _instance.Encode(input);
        }
    }

The files: "encoder.json", "vocab.bpe", "dict.txt", you can download via the links provided, and save them in a Data folder. Don't forget to copy to output directory.

The prediction is fairly accurate, with only two training examples, here is the prediction I got:

We should be getting:

new InputTrainingData()
{
   Sentence = "Alice and Bob live in the USA",
   Label = new string[]{"PERSON", "0", "PERSON", "0", "0", "0", "COUNTRY"}
},

At position [6] we should be getting: "COUNTRY". With some more training examples, this will improve drastically!

The EnglishRoberta class, encodes, or tokenizes words like so:

NER is a very useful tool, used in many areas in IT and Data Aquisition! It is useful for automatically extracting information from large texts!

Best Wishes,

Chris

Ameca Desktop

2023-08-31T03:57:35.9100000

My Friends,

What do you think?

https://www.youtube.com/watch?v=nnboHTfYsfk

Best Wishes,

Chris