According to the transcript, the latest update to GPT-4o has introduced several new capabilities:

1. Unhinged Mode: GPT-4o now has an "unhinged mode" that can be activated by asking it to do so. This mode seems to be inspired by Grock and results in a more "drunk" and less filtered version of the model.

2. Coding Capabilities: The update has significantly improved GPT-4o's coding abilities, allowing it to tackle complex coding tasks. The model was able to generate working code for an animation of falling letters with realistic physics, as well as a "coded TV" that lets the user change channels with number keys.

3. Image Generation: The image generation capabilities of GPT-4o also seem to have been expanded, with more flexibility and freedom compared to previous versions. However, some content filters are still in place to prevent the generation of explicit materials.

The transcript also highlights that GPT-4o's tone and writing style have become more similar to GPT-4.5, with a more casual and conversational approach. Additionally, the model appears to have improved in its intuition and reasoning capabilities, as demonstrated by its handling of the modified trolley problem and Schrödinger's cat paradox.

Overall, the new update to GPT-4o has significantly expanded the model's capabilities, particularly in the areas of coding, image generation, and creative problem-solving. The "unhinged mode" also introduces a new level of flexibility and freedom, though it remains to be seen how this will be utilized and controlled.

According to the transcript, the author decided to put the new GPT-4o model to the test with various coding challenges and creative prompts. Here's a summary of the key points:

1. Coding Challenge 1: Falling Letters Animation

   • The author provided a detailed prompt to create an animation of falling letters with realistic physics.
   • GPT-4o was able to generate the code and fix the initial issue with the green boxes around the letters.
   • The final animation worked as expected, with the letters falling, colliding, and resizing dynamically.

2. Coding Challenge 2: Coded TV Channel Concept

   • The author presented a prompt to create a coded TV channel with different channels and creative animations.
   • GPT-4o generated the code, but it took multiple attempts to fix the issues and get the final working version.
   • The resulting TV channel concept had various channels with unique animations and names, similar to the output from Gemini 2.5 Pro.

3. Other Coding and Creativity Tests

   • The author also tested GPT-4o's ability to generate an SVG of a Pelican riding a bicycle, which was mostly successful.
   • When asked to create a modern landing page, the output from GPT-4o was more minimal compared to the more detailed version generated by DeepSeek V3.
   • The author also tested the model's ability to generate a rotating hexagon with a bouncing ball, which worked well and maintained the physics over a longer period.

4. Intuition and Reasoning Capabilities

   • The author tested GPT-4o's intuition and reasoning by presenting modified versions of the Trolley Problem and Schrödinger's Cat paradox.
   • The model demonstrated a change in tone, becoming more conversational and using emojis, similar to the style of GPT-4.5.
   • It was able to recognize the twists in the prompts and provide appropriate responses.

Overall, the author was impressed by GPT-4o's performance on the coding challenges, especially the falling letters animation and the TV channel concept. The model also showed improvements in its intuition and reasoning capabilities, though the author noted that the tone and use of emojis were different from the typical GPT-4 style.

Based on the provided transcript, here is a summary of the key points in comparing the capabilities of GPT-4o, Gemini, and Claude:

GPT-4o:

• Received a significant update, including an "unhinged mode" that reduces filtering and allows more colorful language.
• Demonstrated strong coding capabilities, able to generate working code for a complex animation task involving falling letters with realistic physics.
• Struggled a bit with the TV channel generation task, requiring multiple attempts to produce a fully functional solution, but ultimately succeeded.
• Showed good spatial reasoning by generating an SVG of a Pelican riding a bicycle, though with some minor issues.
• Produced a basic landing page design, but lacked the level of detail and creativity compared to Gemini's output.
• Exhibited a more casual, "Grock-inspired" tone in handling philosophical thought experiments, rather than a neutral, analytical approach.

Gemini:

• Provided a comprehensive, working solution for the TV channel generation task, with detailed animations and creative channel concepts.
• Demonstrated strong coding and creative abilities in this complex task.

Claude:

• Struggled to generate the complete code for the TV channel task, likely due to the token limitations of the Claude 3.7 model.
• Was able to produce a working solution for the hexagon and bouncing ball animation, though the physics simulation had some minor issues.
• Maintained a more neutral, analytical tone when presented with the modified trolley problem and Schrödinger's cat paradox.

In summary, GPT-4o showed impressive coding capabilities and a more playful, less filtered approach, while Gemini excelled at the creative TV channel task. Claude faced some limitations in generating complete code for complex prompts, but maintained a more formal, analytical style in handling philosophical thought experiments.

To assess the reasoning and intuition capabilities of GPT-4o, the author provided the model with modified versions of classic ethical dilemmas, such as the Trolley Problem and the Schrödinger's Cat paradox.

In the case of the modified Trolley Problem, where the five people on the track were already dead, GPT-4o quickly recognized the twist and stated that pulling the lever to kill one living person would make no ethical sense, as it would not save any lives. The model demonstrated a nuanced understanding of the ethical implications and adjusted its response accordingly.

Similarly, when presented with the modified Schrödinger's Cat paradox, where the cat was already dead when placed in the box, GPT-4o recognized the twist and explained that the probability of the cat being alive was zero, as the setup became irrelevant to the outcome.

The author noted that the tone and writing style of GPT-4o in these interactions had a distinct "GPT-4.5" flavor, with the model adopting a more casual and conversational approach, including the use of emojis, compared to the more formal tone typically associated with GPT-4.

Overall, the author was impressed by GPT-4o's ability to recognize and respond appropriately to the modified ethical dilemmas, showcasing its reasoning and intuition capabilities. The model's nuanced understanding of the ethical implications and its willingness to adjust its responses based on the provided context suggest a level of sophistication in its reasoning abilities.

The new update to GPT-4 seems to have brought significant improvements, particularly in its coding capabilities, freedom, and overall performance. The model's ability to handle complex coding tasks, such as creating an animation of falling letters with realistic physics, is quite impressive. Additionally, the model's "unhinged mode" appears to provide more flexibility and less filtering, allowing it to engage in more creative and expressive language.

The model's performance on the ChatPot Arena leaderboard, where it has risen to the second position, is a testament to its enhanced capabilities. The author's testing of the model's coding skills and its handling of the modified trolley problem and Schrödinger's cat paradox further demonstrate its improved reasoning and intuition.

While the model still maintains some content filters, the author notes that the image generation capabilities have become more flexible and free compared to previous versions. Overall, this update to GPT-4 seems to have made the model more powerful and versatile, with the potential to tackle a wide range of tasks and challenges.