Turing to Transformers

#ai #tech #history #future

The Imitation Game

The story of Artificial Intelligence doesn't begin with a microchip, but with a question. In 1950, Alan Turing published a paper titled Computing Machinery and Intelligence, in which he posed the famous question: "Can machines think?"

He proposed the Turing Test, a criterion for intelligence: if a human interacting with a machine cannot distinguish it from another human, the machine is said to be intelligent.

"We can only see a short distance ahead, but we can see plenty there that needs to be done."

— Alan Turing

The Rollercoaster: Summers and Winters

The term "Artificial Intelligence" was officially coined at the Dartmouth Workshop in 1956. The optimism was intoxicating. Researchers believed a machine as intelligent as a human would exist within a generation.

They were wrong.

The Timeline of Evolution

  • 1950s-60s (The Golden Years): Early programs like ELIZA (a chatbot) and checkers-playing algorithms showed promise. Logic and rules were the primary tools.
  • 1970s-80s (The AI Winter): Funding dried up. The "rules-based" approach hit a wall; computers couldn't handle the ambiguity of the real world.
  • 1997: IBM's Deep Blue defeated world chess champion Garry Kasparov. It was brute force, not "thinking," but it was a milestone.
  • 2010s (Deep Learning): The availability of massive data (Big Data) and GPUs allowed Neural Networks to flourish. Systems could finally "see" (Computer Vision) and "hear" (Speech Recognition).

Abstract Neural Network

The Transformer Revolution (2017–Present)

Everything changed in 2017 with a paper from Google titled "Attention Is All You Need." This introduced the Transformer architecture.

Unlike previous models that read text sequentially (left to right), Transformers could pay "attention" to entire sentences at once, understanding context and nuance. This architecture paved the way for Large Language Models (LLMs) like BERT, Claude, and GPT.

Suddenly, AI wasn't just classifying images; it was generating poetry, code, and art.

What's Next? (2026 and Beyond)

As we stand here in late 2025, the "Chatbot" era is arguably peaking. We are moving from AI that talks to AI that acts.

1. Agentic AI

The next massive shift is Agents. Instead of you typing a prompt and getting text back, you will give an Agent a goal: "Plan a trip to Tokyo for under $3,000." The AI will autonomously browse the web, compare flights, book hotels, and add dates to your calendar—looping until the task is complete.

2. Embodied AI

Brain, meet Body. We are seeing the rapid convergence of LLMs and Robotics. Robots are no longer being hard-coded to pick up a box; they are being taught via vision and language models to navigate complex, messy human environments.

3. Reasoners

Models are moving from pattern matching to System 2 Thinking—slow, deliberate reasoning. We are seeing models that can pause, "think" through a math problem step-by-step, verify their own work, and correct errors before responding.

The history of AI is a history of moving the goalposts. Once a machine can do it, we stop calling it AI and just call it "software." But the next decade promises to blur that line until it vanishes completely.