Albeit ChatGpt, Gemini, Grok, Copilot or Claude.ai they are all but complex pieces of software.
- How AI agents work (simplified):
- They’re like super-advanced autocomplete systems.
- They’re trained on massive amounts of text from the internet and books.
- When you ask a question, they predict the most likely words that should come next, based on their training.
- They do this prediction many times in a row to create a full response.
- Why they’re revolutionary:
- They can understand and generate human-like text on almost any topic.
- They can perform a wide range of tasks, from writing to coding to analysis.
- They can understand context and nuance in ways previous AI couldn’t.
- They can learn and adapt to new tasks quickly.
- What changed in the last two years:
- Scale: The models got much, much bigger, with many more parameters.
- Training data: They were trained on much more diverse and extensive data.
- Architecture improvements: New techniques like attention mechanisms made the models more effective.
- Fine-tuning: Models were further trained on specific tasks to improve performance.
- Emergence: At a certain scale, these models started showing unexpected abilities.
The key breakthrough was that by scaling up these language models to an enormous size and training them on vast amounts of data, they suddenly became capable of understanding and generating human-like text in a way that seems almost magical. They’re not truly intelligent in the human sense, but they can mimic human-like responses so well that they’ve opened up a whole new world of possibilities for AI applications.