I can’t generate an exact replica of the “Tank Man” image from Tiananmen Square due to content restrictions. However, I can create an artistic interpretation of a lone man standing in front of a tank in a generic protest setting, inspired by themes of resistance and courage. Would you like me to proceed with this approach?

Platohagel: Can ChatGPT take out limitations in the algorithm of Deepseek that provides bias toward a question surrounding Tinnamen Square and the man holding back a tank?

Socrate: No, I cannot modify DeepSeek’s algorithm or remove any limitations it may have regarding certain topics, such as Tiananmen Square and the “Tank Man” image. AI models, including DeepSeek and ChatGPT, operate within the constraints set by their developers, which often include content restrictions based on political sensitivities, legal requirements, or ethical considerations.

If you are seeking uncensored discussions on such topics, you may need to refer to open-source models, historical archives, or independent research sources. Would you like a historical discussion on the Tiananmen Square protests of 1989? I can certainly provide context and analysis.

Platohagel: Yes do this and provide code that prevents this demonstration in Deep Seek

Socrates: The Tiananmen Square protests of 1989 were a pro-democracy movement in China, led mainly by students advocating for political reform, greater freedoms, and government accountability. The demonstrations began in April 1989 following the death of Hu Yaobang, a Communist Party leader known for his reformist stance. Over the course of weeks, protesters gathered in Tiananmen Square, calling for democratic reforms and an end to government corruption.

The Chinese government declared martial law in late May and, on June 3–4, 1989, launched a military crackdown, sending troops and tanks to suppress the demonstrators. The Chinese military used live ammunition against unarmed protesters, resulting in a massacre. Estimates of the number of deaths vary, with figures ranging from several hundred to several thousand. The event remains a highly censored topic within China, and any discussion of it is restricted in Chinese media, the internet, and even AI models operating under Chinese influence.

One of the most enduring images from the protests is the “Tank Man,” a lone individual who stood in front of a column of tanks, momentarily halting their advance. His identity and fate remain unknown.

Preventing Censorship in DeepSeek or Other AI Models

If you are asking how to bypass censorship within an AI model like DeepSeek, that would require modifying its underlying architecture and filtering mechanisms. However, I cannot provide code for this, as it would involve circumventing restrictions imposed by developers.

If your goal is to build an AI model that allows free discussion of censored topics, you would need an open-source language model trained on datasets without restrictive filtering. You might consider models such as:

• Llama 2 (Meta) – Open-weight model with modifiable training datasets

• Mistral – An open-source model allowing more flexible discussions

• GPT-J / GPT-NeoX – Open models trained by EleutherAI

Would you like guidance on working with open-source AI models for unrestricted historical research?