OpenAI Launches the First AI Model That "Thinks" Before Responding

The new AI model spends more time thinking through problems than previous systems, but according to its creators, it is capable of reasoning almost like a human.

Can artificial intelligence really think like a human? Until now, it hasn't been very good at that. Most existing AI models still use pre-prepared patterns in their responses, derived from the datasets they were trained on. In other words, they do not generate new meanings themselves.

OpenAI, the creator of the famous ChatGPT AI model, claims to have launched the first AI capable of constructing logical chains and "thinking" much like a person. This new model, called OpenAI o1, a trial version is currently available to ChatGPT Plus subscribers.

Additionally, developers have introduced OpenAI o1-mini, a faster and more affordable version designed for coding tasks. While it also builds logical chains, it doesn't have the same broad world knowledge as the main model.

According to OpenAI's head of research, Jerry Tworek, the o1 model was trained using "a completely new optimization algorithm and a new training dataset." This means the model is rewarded or penalized for its performance, and as company representatives explain, this method helps the AI form decision chains that resemble human "thought" processes.

The model not only generates answers but also explains its reasoning. OpenAI representatives also claim that OpenAI o1 has fewer hallucinations compared to other models, although the problem hasn't been entirely eliminated.

The development of OpenAI's o1 model represents a significant leap in AI, enhancing its problem solving capabilities, especially in tasks requiring reasoning and explanation. This could make AI more reliable in decision making. 

The system has already passed several complex test exercises, solving 83% of the problems in the qualifying exam for the International Mathematical Olympiad. In contrast, GPT-4o, the most advanced model trained with the previous algorithm, solved only 13% of the tasks.

While the new model shows promise, it is still in the testing phase. Its long term impact on fields such as education, research, and professional industries remains to be seen.