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TAL launched the self-developed 100-billion-level mathematical model MathGPT and started public beta testing

TAL launched the self-developed 100-billion-level mathematical model MathGPT and started public beta testing

  8moontwenty fourday, in the future20In the anniversary live event,CTOTian Mi announced the 100-billion-level large-scale model in the field of mathematics developed by TALMathGPTOpen beta.From now on, users canofficial websiteApply for a registered account for a free trial experience.

  In May of this year, TAL announced that it was developing a self-developed large mathematical model, named MathGPT. According to reports, MathGPT is a large-scale model in the vertical field of mathematics with the core of problem-solving and lecture algorithms for mathematics enthusiasts and scientific research institutions around the world, and it is also a large-scale model specially designed for mathematics.

  When users use MathGPT, they can upload math questions in text or pictures, and then they can get dialogue-style answer feedback. They can also use the “random question” button to randomly generate math questions and give answers by the system. Currently, MathGPT supports PC and mobile experiences in Chinese and English versions.

  According to Tian Mi, MathGPT brings together TAL’s years of education, teaching and research data accumulation, focusing on the field of mathematics. Through high-quality educational data, multi-task continuous training and supervised fine-tuning such as topic calculation, explanation, and question-and-answer are realized, showing excellent performance.

  According to the official website of MathGPT, MathGPT’s mathematical computing ability has covered mathematics problems in elementary school, junior high school, and high school. Q&A interaction.

  MathGPT technical report

  The MathGPT technical report shows that among the test results of six public mathematics evaluation collections including CEval-Math, AGIEval-Math, APE5K, CMMLU-Math, Gaokao Mathematics and Math401, TAL’s MathGPT has achieved the highest scores in multiple tests. At the same time, MathGPT also performed well on the general test collection of C-Eval’s middle and high schools.

  MathGPT’s C-Eval list of junior and senior high school subjects

  In terms of problem-solving stability and explanation friendliness, MathGPT conducts model training based on a large number of famous teachers’ problem-solving process data, and the model’s problem-solving steps are professional and clear.

  Taking a sequence question as an example, the answer given by MathGPT includes three parts: “analysis”, “detailed explanation” and “finishing points”, which is more detailed than the rough explanation of the general large model. “Analysis” provides the problem-solving ideas , way of thinking, to help users better understand the questions, “detailed explanation” gives specific calculation methods and answers, and the last “finishing” link reminds the test points, difficulties, and key points of the questions, helping users review and reflect on the questions Intention, draw inferences about other cases from one instance.

  For users, researching mathematical problems is not only about getting the answers themselves, but also about the problem-solving principles and thinking logic behind the answers. Compared with other general-purpose large models, MathGPT can solve problems with higher accuracy, and can also analyze the answers more clearly and explain them more clearly, and better meet the core needs of users to use AI products to solve mathematical problems.

  At the same time as MathGPT was released, TAL also updated a representative and challenging math task evaluation set on its official website for global artificial intelligence experts and math enthusiasts to experience and evaluate.

  With the rise of large language models, how to use AI technology to serve all walks of life is the focus of social attention. “AI brings the opportunity to redefine the education industry, and large-scale model technology makes it possible to realize large-scale individualized teaching.” Tian Mi believes that the essence of large models is a more efficient way of learning knowledge from data and way of applying it. With the blessing of AI capabilities, the new learning method of “students’ self-study + AI Q&A” has become widely possible. The threshold and cost for learners to obtain high-quality teaching content are reduced, and the degree of personalization and refinement of the obtained teaching content continues to increase. It can realize AI teaching and Q&A tutoring for thousands of people, and every student can get the learning content that suits them .

  According to Tian Mi, with the smooth progress of the internal test, MathGPT’s problem-solving ability will continue to improve, and product-level applications based on MathGPT are also being developed at an accelerated pace and will be released in the near future.

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