🧠💬 Meet ELIZA – The OG AI Therapist from the 60s!

Before ChatGPT, Claude, or Gemini…
Before even Windows or iPhones existed...
There was ELIZA 👵💻

Developed in the 1960s by MIT’s Joseph Weizenbaum, ELIZA was the first chatbot that shocked people by mimicking a psychotherapist. You’d say “I feel sad” and she’d go:

“Why do you feel sad?”

🧠 Mind-blowing at the time. People really thought she understood them.

Sure, she might sound like your grandma playing therapist after 2 cups of tea ☕, but back then this was sci-fi level genius.

Sure, compared to today's LLMs that can write code, explain black holes, or beat you in trivia — ELIZA seems basic...
But she was the spark that started it all.

👉 Try chatting with her here:
🌐 https://www.masswerk.at/eliza/

Ask her questions.
Test her logic.
Mess with her responses.

She’ll still reply like it’s 1966.

You’ll gain a new appreciation for how far we’ve come in AI — and maybe even a good laugh 😂

#AIHistory #ELIZA #ChatbotClassic #ThrowbackTech #LLMroots

This is what I got 😂😂kinda Delulu, but still appreciable

Go on Tell me funniest file name on your PC..

What a crazy week in AI 🤯

Here’s EVERYTHING you need to know, AI NEWS of week:

OpenAI o3-Pro :- OpenAI launches o3-Pro, their most capable reasoning model yet, now available to ChatGPT Pro and Team users. Replaces o1-Pro with enhanced performance in science, education, and programming, scoring 64% win rate vs o3 on human evaluations.

Google AI Extract:- Google unveils “Extract”, an AI assistant that transforms handwritten planning documents into digital data in minutes. Built with Google DeepMind's Gemini model, it processes 100 records daily vs the current 1-2 hours per document manually.

Krea 1 Image Model:- Krea launches their first flagship image model with state-of-the-art photorealism and superior aesthetic control. Features 1.5K native resolution output, supports custom training, and offers free daily generations with no signup required.

Midjourney AI Video:- Midjourney is putting the finishing touches on their V1 Video Model, it'll be launching soon.

Topaz Video Upscaler It’s the first-ever creative upscaler for video. It lets users upscale AI-generated videos to crisp 4K resolution while enhancing quality and finer details.

Dia AI-first web browser The Browser Company launches Dia, an AI-first browser with a built-in assistant directly in the address bar. It can summarize articles, write emails, and even browse websites on your behalf.

Mistral Reasoning Models They are Europe’s first reasoning models, with Small (24B parameters) open-source and Medium for enterprise. Unique feature: can reason natively in multiple languages including English, French, Spanish, and Arabic.

Scouts Web Monitor Agents They are always-on AI agents that monitor the web for anything you care about. Simply tell them what to track and they deploy across dozens of sites, running in the cloud 24/7.

SkyReels Open-Source AI Video It’s the world's first open-source infinite-length video generation model using AutoRegressive Diffusion-Forcing architecture.

Join GenAI: https://whatsapp.com/channel/0029VayIXpnKLaHhzg4Cvp12/123

I pissed on the man who called me a dog. Why was he so surprised?

Diogenes

Diogenes is the funniest and interesting philosopher I've ever read about!😂

Fascinating repo🧐

It's been 5 yrs, but it's great podcast check it out.

I think Ilya is underrated. I know most people argue it's not, but I insist his name should be at level of Geoffrey Hinton and Yann LeCun. He and Demis Hassabis would be pioneers in AGI development.

I think this tweet shows the greatness of Ilya!

Dropping some factos 👀

You Beautiful Alien🔥🔥🔥No Any AGI or ASI system would be like him. Beyond Greatness😎

It's Ridiculous seeing other clubs cooking Europe Teams in this club world cup. Al Hilal and Inter Miami has surprised me.

🐍 Why Python is Dynamically Typed — and What That Really Means

In the world of programming languages, a major distinction you’ll encounter is ''statically typed'' vs ''dynamically typed'' languages. Python falls into the latter category — and understanding what that means is not just theoretical. It affects how you write code, debug, and build scalable systems.

🧠 What Does "Dynamically Typed" Even Mean?

In a dynamically typed language like Python, variable types are determined at runtime, not in advance.

That means:

- You don’t have to declare the type of a variable.
- The type is determined when the code is executed.
- The same variable can hold values of different types at different points in time.

Compare that to statically typed languages (like Java, C, or Go), where:

- You must declare the type beforehand.
- The compiler enforces type correctness.
- Type-related bugs are caught at compile time.


🧪 A Simple Python Example

print(type(x))  # <class 'int'>

x = "hello"   # Now x holds a string!
print(type(x))  # <class 'str'>

Python lets you reassign a variable to a completely different type. No complaints, no compiler errors — because Python doesn't check types until the code runs.


🔬 What’s Going on Under the Hood?

When you write x = 42 in Python, you’re not binding a type to a variable. Instead, you’re:

1. Creating an object of type int with value 42.
2. Binding the name x to that object in a dictionary that represents the current namespace.

You can think of Python variables as labels attached to objects, not as memory slots of a specific type like in C.

Internally:

Python stores all objects in memory, and every object has:

- A type tag (`PyTypeObject*`)
- A reference count
- Optional value fields

When x = 42, this happens:

When you do x = "hello":

- Python decreases the reference count of the integer object (maybe deletes it if count == 0).
- Then creates a new str object.
- Binds x to this new string object.

This level of indirection is what makes Python dynamic — and flexible.


⚖️ Static Typing Comparison: Java

Here’s a similar example in Java:

x = "hello"; // ❌ Compile-time error!

Java won't allow this because the variable x is statically typed as int. The compiler enforces this restriction before the program even runs.

That’s the difference: Static typing = types known and checked before runtime.

🚨 Benefits and Drawbacks of Dynamic Typing

✅ Pros:

* Fast prototyping
* Less boilerplate code
* More flexible (you can write generic functions easily)
❌ Cons:

* Type-related bugs are found at runtime
* Harder to reason about large codebases
* Less performance optimization by interpreter

🧰 Optional Static Typing in Python

Thanks to Python’s evolution, you can now use type hints (via [PEP 484](https://peps.python.org/pep-0484/)) to make your code feel more like statically typed code — without losing flexibility.

Example:

    return "Hello, " + name

But remember: type hints are not enforced by Python itself. They’re used by tools like mypy or IDEs to check types statically, but they don’t change how Python runs your code.


🛠️ Recap: Why Python Is Dynamically Typed

* Type is determined at runtime
* Variables are just names bound to objects, not memory slots with types
* No compiler-time type checking
* You can reassign a variable to any type

Under the hood, Python uses dynamic memory management, object metadata, and runtime type checking to make this flexibility possible — at the cost of some performance and type safety.


🧩 Final Thought

Python’s dynamic nature is what makes it intuitive and elegant, especially for scripting, data science, and AI development. But as your codebase grows, combining dynamic typing with good practices and optional static hints can give you the best of both worlds.