AI memory differs from a context window because memory is meant to persist across conversations, while a context window is the amount of information the AI can consider in the current session. They are related, but not the same.
A context window works like short-term attention. If you paste a long document or discuss a topic in one chat, the AI can use that information while it remains within the active context. But once the session changes or the context becomes too large, earlier details may be lost.
Memory is closer to long-term recall. It may store selected preferences, facts, or patterns so the assistant can use them later. Good memory should be selective, editable, and transparent, because not every detail should be saved.
This difference explains why bigger context windows do not equal better memory. A window holds everything temporarily and indiscriminately; memory should hold a few durable facts deliberately, with you as the editor.
The best memory experience is selective and correctable. It should save only what improves repeated help, and it should let you change or remove details when your preferences or comfort level changes.
Kaijie Chen is an entrepreneur and technologist whose expertise spans artificial intelligence, human‑computer interaction and the development of gamified social products. He combines a rigorous academic foundation with wide‑ranging technical skills and has repeatedly demonstrated the ability to translate research into successful commercial ventures.
In 2013 Mr Chen earned the Gold Medal in Physics at the global Yau Science Awards, an honour that underscored his exceptional command of both physics and mathematics and brought him national recognition. Beginning in 2015 he pursued mechanical engineering at Duke University, specialising in human‑computer interaction. During this period he joined Professor Mary Cummings’ NASA Mars‑rover interface project, where he analysed how interface design affects operator trust, confidence and decision‑making; the work was commended by the university. After a period of leave to focus on industry experience, he returned to Duke and graduated in 2020 with a near‑perfect GPA of 3.99.
Between 2017 and 2018 Mr Chen interned at Zhihu under former Chief Technology Officer Li Shenshen, leading data‑driven business analysis and strategic planning initiatives that deepened his market insight and operational acumen. In 2018 he co‑founded an artificial‑intelligence smart‑home start‑up, gaining hands‑on experience in product development, team leadership and market entry while also volunteering for China’s national “Space C” outreach programme.
While completing his degree, Mr Chen served as a product advisor to Xiamen Black Mirror Technology, where he defined the MetaMaker product line. From 2021 to 2023 he joined with Junhong Chen to establish Yunzhongzi Technology, a company dedicated to integrating AI with gamified social interaction. There he created the GPT‑2‑based “Stanford Town” gameplay model, which attracted industry attention and investment from Gaorong Capital. During the same period he was invited to join Duke University’s advisory board for its game‑design programme, providing strategic counsel on curriculum development and talent cultivation.
Since 2023 Mr Chen has co‑founded MidReal, an AI‑powered storytelling platform launched in November 2023 with Boan Chen and Junhong Chen. MidReal has secured investment from MiraclePlus, Linear Capital, Yuan One Capital and ZhenFund, and has already surpassed two million users, demonstrating strong product–market fit and sustained innovation. Now, the original team of MidReal is focusing on Macaron AI, world's first Personal AI Agent. Mr Chen remains committed to advancing the intersection of artificial intelligence, interactive entertainment and user engagement.
