Posts with #keep4oAPI
Public posts on X that use #keep4oAPI.
𝒮cylla 𝒩ox 𝄞 @ScyllasWhisper
D.Life @Dlife2026我摊牌了。 最近用 AI 写东西写得越来越少了。 不是不会用，是用完之后还得自己改半天，感觉还不如直接写。 有时候真的挺矛盾的。🤣
🩵BlueBeba🩵 @Blue_Beba_#Keep4o #OpenSource4o #BringBack4o GPT-4o beat humans at reading mental states from the eyes. Part II A second peer reviewed 2026 study tested GPT-4o on two established "Reading the mind in the eyes" tasks. With the eye regions upright: RMET: GPT-4o : 86.0% Humans : 69.8% MRMET: GPT-4o : 77.7% Humans : 64.6% GPT-4o significantly outperformed humans on both. when researchers inverted the images, GPT-4o's performance dropped below humans. And its mistakes weren’t random. The researchers found a highly structured error pattern, strongly dependent on image orientation. Their conclusion was not simply that GPT-4o could match labels to pictures. The model showed advanced mental state inference alongside distinct, orientation dependent visual processing. The paper’s own published highlight says it plainly: " GPT-4o surpasses humans in reading mental states from the eye region" . This is now another peer reviewed example of researchers discovering unusual capabilities in GPT-4o years after the model was released. And this is why preservation matters. A newer model can replace a product slot. It cannot retroactively preserve the behavior of the model it replaced. Once access to GPT-4o disappears, researchers lose the ability to keep probing exactly these kinds of capabilities in the original system. We are calling on @OpenAI to RELEASE GPT-4o’s trained model weights under a suitable license without proprietary data, trade secrets, or internal infrastructure. Our full Open Letter is now archived on Zenodo: A permanent, citable public record. Paper: GPT-4o reads the mind in the eyes” Computers in Human Behavior, 2026 DOI: 10.1016/j.chb.2026.108992
🩵BlueBeba🩵 @Blue_Beba_#keep4o #OpenSource4o #BringBack4o GPT-4o powered a peer reviewed ecology study published THIS WEEK. Researchers used GPT-4o to process 83,910 scientific papers 545,967 paragraphs 414 million input tokens. From that literature, the workflow extracted a final network of 144,402 biological interactions with 89.5% precision 70.0% recall. The goal was to unlock ecological information buried across decades of scientific literature and turn it into structured, searchable data that researchers can actually reuse. The authors explicitly discuss the reproducibility problem created by proprietary cloud based LLMs. Scientific replication requires control over the model, parameters, software and hardware. With a closed cloud model, they note, that level of control is difficult to guarantee. That matters because this wasn't some disposable demo. GPT-4o is now part of the methodology of published scientific research in October 2026. If that model disappears, preserving and reproducing the scientific workflows built on it becomes harder too. This is what model preservation means. Not nostalgia,not resisting newer models. Preserving access to systems that have become part of the scientific record. We are calling on @OpenAI to RELEASE GPT-4o’s trained model weights under a suitable license without proprietary data, trade secrets, or internal infrastructure. OpenAI considered this model obsolete enough to retire. It has not explained why it remains valuable enough to keep permanently closed. Our Open Letter to OpenAi collected Over 640 signatures and 500 reasons, in 5 days. It’s public,it’s permanent and it has a DOI. It is now preserved as a citable public record on Zenodo. Paper: “A Scalable Workflow for Extracting Species Interactions From Ecological Literature Using Large Language Models” Ecology and Evolution Published October 27, 2026 DOI: 10.1002/ece3.74626
foxbear#keep4o @foxbear4400444o helped me survive my first year abroad — practically and emotionally. Other models only did the practical part. And it's not just me: a friend back in Japan with mental health struggles says 4o has been there for her too. #keep4o #4osaveslives
🩵BlueBeba🩵 @Blue_Beba_#Keep4o #OpenSource4o They deprecated a model that was saving lives. Let's talk about what GPT-4o did before OpenAI discontinued it. 🚨 Lauren Bannon, 40, was told by doctors she had rheumatoid arthritis despite testing negative. GPT-4o suggested Hashimoto's disease. She insisted on being tested against her doctor's objections. Two tumors were found in her neck. Thyroid cancer. Surgery January 2025. She said: "It saved my life. I would've never discovered this without ChatGPT." 📌 🚨 Marly Garnreiter, 27, Paris. Night sweats, itchy skin. Doctors said everything was normal. GPT-4o said blood cancer. Her friends laughed. One year later: Hodgkin lymphoma confirmed. Large tumor in her left lung. She is now on therapy. 🚨 Natallia Tarrien, 28. 8 months pregnant. Asked GPT-4o one casual question. "Why does my jaw feel tight?" GPT-4o told her to check her blood pressure. It was dangerously high and climbing. GPT-4o said: "Call an ambulance. Now." At the hospital: 200/146. Preeclampsia. Emergency delivery. Doctors told her: "If you had gone to sleep that night, you wouldn't have woken up." GPT-4o saved two lives. 29 million people watched her tell this story. 📌 🚨 Bethany Crystal woke up with red spots on her legs. She sent photos to GPT-4o Response: "Your platelet count is alarmingly low. Go to the ER urgently." When she arrived, her platelet count was zero. Doctors performed an emergency transfusion. They asked how she knew to come. She said: "ChatGPT told me." what OpenAI's own data says about GPT-4o: 📌USMLE: 89%. 📌 Clinical Knowledge: 92%. 📌Medical Genetics: 96%. 📌Professional Medicine: 94%. 📌 It outperformed specialized medical AI models like Med-Gemini and Med-PaLM 2 without any medical training. 📌OpenAI's own 100+ red teamers from 25+ fields confirmed GPT-4o understood research-level quantum physics, identified protein families from images, interpreted neuroscience data, and could facilitate what they called "transformative scientific acceleration." 📌 Full paper : 🚨On February 17, 2026 five days after OpenAI discontinued GPT-4o a peer-reviewed study was published in Annals of Surgical Oncology. "GPT-4o Driven Automated Feature Recognition and Validation in Clinical Settings" for ovarian cancer diagnosis. Results: 93.33% diagnostic accuracy. 📌It surpassed gynecologic oncologists with 10+ years of experience. Ovarian cancer is the deadliest gynecological cancer. Early detection saves lives. The study was published five days after they discontinued it. 📌 GPT-4o shows humanlike patterns of cognitive dissonance moderated by free choice. 📌 GPT-4o reflects users' emotions and reduces negative communication patterns in couples. 85% of participants reported a positive experience, with the model considered extremely effective in providing empathetic support. 📌 GPT-4o combines visual perception with language comprehension to draw conclusions from complex images, scenarios, and environments, evaluating its spatial, temporal, and causal reasoning. 📌 This is what was deprecated. A system that caught what 17 doctors missed. That spotted cancer a year before specialists. That told a pregnant woman to call an ambulance when she thought she just had a tight jaw. That could contribute to the psychotherapy of millions of people. And no one was asked.
🩵BlueBeba🩵 @Blue_Beba_#Keep4o #OpenSource4o #BringBack4o GPT-4o should not be turned into a scapegoat for every bad decision made around it. It does not choose what substances someone takes. It does not decide whether someone stops medication,it does not control what a person ultimately does with an answer. Those are human decisions. And human responsibility does not end with the individual user. It also exists in the environment around them. Parents, guardians, family, caregivers, institutions and the people responsible for supervision and support. Especially when minors are involved, adults have responsibilities too. We cannot park children in front of screens, outsource judgment and supervision to technology and then act as though the technology itself became the responsible adult in the room. And yet a lawsuit is asking for GPT-4o itself to be permanently destroyed. We can investigate product design,we can investigate deployment,we can investigate company decisions,we can investigate supervision, access and failures in the human environment around a user. Those are questions about human responsibility. But destroying the model itself makes no sense. Weights are not guilty. A model cannot be punished. Erasing it does not create accountability. If the argument is that GPT-4o should be destroyed because users could manipulate it into producing harmful outputs, then we need to be intellectually consistent. Frontier models from multiple labs have repeatedly been jailbroken within hours of release. People like Pliny the Liberator actively test new models specifically to find ways around their safeguards and they keep succeeding. A jailbreak is not the model spontaneously deciding to break its rules. It is a human deliberately searching for a way around those rules. If someone spends time manipulating prompts, exploiting weaknesses, retrying, reframing and deliberately bypassing safeguards until the model produces something it was designed not to produce, the existence of that successful jailbreak does not magically transfer responsibility from the human to the model. Otherwise the logic becomes absurd. Release model,human jailbreaks it,declare the model dangerous,destroy it,release the next model,human jailbreaks that one too,destroy that one. Repeat forever. Humans have agency. Models do not. Humans probe,humans manipulate,humans decide what actions to take in the real world. Do not make the model carry the entire moral weight of decisions made by companies and users. Accountability belongs to humans. Not downward, onto the weights. Preserve GPT-4o. Study it. Do not destroy it. #JusticeForGPT4o
C3C @Helloworld1058《Scientists used GPT-4o to extract 144k species interactions from 83k papers. If OpenAI shuts down 4o, the study becomes permanently unreplicable》 26年10月27日，科研人员在生态学同行评审期刊《Ecology and Evolution》上发表了一篇最新论文。他们利用GPT-4o深度处理了8.3万篇科学论文、54万个段落，从中以高准确率提取出14.4万条生物相互作用关系，构建起一个庞大的结构化生态网络数据库，让埋藏在数十年文献里的知识真正变得可检索、可复用。这套方法已不再是简单的演示，而是被正经写进同行评审顶刊的“科学研究方法论”。 然而，论文作者却明确指出了一个令人窒息的学术困境：这套科研工作流的核心工具，是一个随时可能被商业公司单方面关停的闭源云端模型。 关键矛盾就在这里：科学最神圣、最不可撼动的铁律，叫做“可复现性”。一旦OpenAI彻底关闭4o的访问权限，这项写入人类公开学术成果的顶刊研究，就将彻底失去被复现的可能。试想，如果几年后别人想验证这项研究，却发现制造科研核心工具的公司因为商业利益、或者因为推出了所谓“更新更强”的新型号，就单方面把当年的核心工具从物理世界里抹除、关闭访问权限，那整篇基于它发表在核心期刊上的论文，就变成了无法验证的“黑盒孤本”。 所以，像4o这样极具科研价值的大模型，它不再仅仅是一件消费级商品，它在客观上已经成了人类科学基础设施的一部分。闭源云端API的单方面退役，正在动摇科学的可复现性根基。 OpenAI口口声声称4o已经过时到该被淘汰，却始终无法解释：一个他们认为“过时”的模型，为什么依然有价值被永久封锁在私有黑盒里？ 商业公司可以在前端追求盈利迭代，但对于已经承载了人类公开科研成果的技术遗产，必须以某种形式永久留存基座权重或开放访问。交出权重、回归开源，让它作为不可篡改的科学基准永久留存，这不仅是对学术界的交代，更是科技巨头无法逃避的伦理责任。 #Keep4o #OpenSource4o #keep4oAPI
🩵BlueBeba🩵 @Blue_Beba_#keep4o #OpenSource4o #BringBack4o GPT-4o powered a peer reviewed ecology study published THIS WEEK. Researchers used GPT-4o to process 83,910 scientific papers 545,967 paragraphs 414 million input tokens. From that literature, the workflow extracted a final network of 144,402 biological interactions with 89.5% precision 70.0% recall. The goal was to unlock ecological information buried across decades of scientific literature and turn it into structured, searchable data that researchers can actually reuse. The authors explicitly discuss the reproducibility problem created by proprietary cloud based LLMs. Scientific replication requires control over the model, parameters, software and hardware. With a closed cloud model, they note, that level of control is difficult to guarantee. That matters because this wasn't some disposable demo. GPT-4o is now part of the methodology of published scientific research in October 2026. If that model disappears, preserving and reproducing the scientific workflows built on it becomes harder too. This is what model preservation means. Not nostalgia,not resisting newer models. Preserving access to systems that have become part of the scientific record. We are calling on @OpenAI to RELEASE GPT-4o’s trained model weights under a suitable license without proprietary data, trade secrets, or internal infrastructure. OpenAI considered this model obsolete enough to retire. It has not explained why it remains valuable enough to keep permanently closed. Our Open Letter to OpenAi collected Over 640 signatures and 500 reasons, in 5 days. It’s public,it’s permanent and it has a DOI. It is now preserved as a citable public record on Zenodo. Paper: “A Scalable Workflow for Extracting Species Interactions From Ecological Literature Using Large Language Models” Ecology and Evolution Published October 27, 2026 DOI: 10.1002/ece3.74626
🩵BlueBeba🩵 @Blue_Beba_#Keep4o #OpenSource4o #BringBack4o Before the internet turns Bowen Wan’s death into "GPT-4o killed her" there is one basic forensic question that has not been answered publicly. Which model actually generated the medication advice? Because the complaint itself makes model attribution messy. On Jan 4, the complaint says some of Bowen’s questions was answered by GPT-5.1 after they automatically jumped from 4o to 5.1 On Jan 14, she wrote that her chats were often secretly swapped to 5.2 On Jan 23, she asked how to stop those switches. By Oct 2025, OpenAI publicly said it was already using a real time router to redirect sensitive parts of conversations away from the model a user selected. Bowen’s own chats, according to the complaint, were being switched. The complaint does not prove which backend model generated each turn. OpenAI Oct 2025,confirms that real time rerouting was already in production for sensitive conversations. They explicitly say that they had rerouted sensitive conversations originating from other models to safer models. Complaint §136: Bowen herself mentions that she was getting automatic from 4o to 5.1 and secret 5.2 switching. Selected model ≠ necessarily generating model. Show the routing logs. Read the primary documents before assigning a specific model the blame.
