How A.I. Chatbots Like ChatGPT and DeepSeek Reason

Artificial intelligence is getting smarter—well, sort of. The latest advancements in chatbot technology, driven by companies like OpenAI, Google, Anthropic, and DeepSeek, involve a new concept: reasoning. Unlike previous A.I. models that generated responses instantly, the newest versions, like the upgraded ChatGPT, take extra time to think through problems—especially in areas like math, science, and coding. These systems use reinforcement learning, a trial-and-error-based method, to refine their decision-making, much like a student working through difficult math problems step-by-step. But does this actually mean they "think" like humans? Experts remain divided, acknowledging that while these advancements improve accuracy, they still make mistakes and likely have a long way to go before reaching anything resembling human intelligence.

Key Takeaways:

• What is reasoning in A.I.?

  • It’s the ability of a chatbot to break down and analyze a question over time instead of responding instantly.
  • Chatbots like the new ChatGPT can refine their responses by testing out different approaches before settling on an answer.

• How does it work?

  • These systems often use reinforcement learning, a method where they "learn" from trial and error.
  • As OpenAI researcher Jerry Tworek puts it, “It is a little like training a dog. If the system does well, you give it a cookie. If it doesn’t do well, you say, ‘Bad dog.’”

• What kinds of problems do reasoning A.I. systems excel at?

  • They perform best in structured fields like math, science, and programming, where there are clear right and wrong answers.
  • They struggle with more subjective areas, like creative writing, ethics, and philosophy.

• Why is reasoning important now?

  • Companies hit a data limit—they’ve used nearly all publicly available internet text.
  • Instead of relying only on more data, they’re improving A.I. through new reasoning techniques.

• Does reinforcement learning mean A.I. is becoming truly intelligent?

  • Not exactly. While these models are improving, they still operate on probabilities and can make errors.
  • Experts remain split on whether this kind of machine reasoning is a step toward human-level intelligence.

As A.I. continues to evolve, the real question remains: Is this a breakthrough toward truly thinking machines, or just a clever way to make chatbots better at faking it?
Link to Article