text
𝐎𝐩𝐞𝐧𝐀𝐈 𝐟𝐢𝐧𝐚𝐥𝐥𝐲 𝐫𝐞𝐯𝐞𝐚𝐥𝐬 “🍓”: 𝐜𝐫𝐚𝐳𝐲 𝐜𝐡𝐚𝐢𝐧-𝐨𝐟-𝐭𝐡𝐨𝐮𝐠𝐡𝐭-𝐭𝐮𝐧𝐞𝐝 𝐦𝐨𝐝𝐞𝐥 >> 𝐆𝐏𝐓-𝟒𝐨 💥
𝐎𝐩𝐞𝐧𝐀𝐈 𝐟𝐢𝐧𝐚𝐥𝐥𝐲 𝐫𝐞𝐯𝐞𝐚𝐥𝐬 “🍓”: 𝐜𝐫𝐚𝐳𝐲 𝐜𝐡𝐚𝐢𝐧-𝐨𝐟-𝐭𝐡𝐨𝐮𝐠𝐡𝐭-𝐭𝐮𝐧𝐞𝐝 𝐦𝐨𝐝𝐞𝐥 >> 𝐆𝐏𝐓-𝟒𝐨 💥
new_line
new_line
text
OpenAI had hinted at a mysterious “project strawberry” for a long time: 𝘁𝗵𝗲𝘆 𝗽𝘂𝗯𝗹𝗶𝘀𝗵𝗲𝗱 𝘁𝗵𝗶𝘀 𝗻𝗲𝘄 𝗺𝗼𝗱𝗲𝗹 𝗰𝗮𝗹𝗹𝗲𝗱 “𝗼𝟭” 𝟭𝗵𝗼𝘂𝗿 𝗮𝗴𝗼, 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗶𝘀 𝗷𝘂𝘀𝘁 𝗺𝗶𝗻𝗱-𝗯𝗹𝗼𝘄𝗶𝗻𝗴.
OpenAI had hinted at a mysterious “project strawberry” for a long time: 𝘁𝗵𝗲𝘆 𝗽𝘂𝗯𝗹𝗶𝘀𝗵𝗲𝗱 𝘁𝗵𝗶𝘀 𝗻𝗲𝘄 𝗺𝗼𝗱𝗲𝗹 𝗰𝗮𝗹𝗹𝗲𝗱 “𝗼𝟭” 𝟭𝗵𝗼𝘂𝗿 𝗮𝗴𝗼, 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗶𝘀 𝗷𝘂𝘀𝘁 𝗺𝗶𝗻𝗱-𝗯𝗹𝗼𝘄𝗶𝗻𝗴.
new_line
new_line
text
🤯 Ranks among the top 500 students in the US in a qualifier for the USA Math Olympiad
🤯 Ranks among the top 500 students in the US in a qualifier for the USA Math Olympiad
new_line
text
🤯 Beats human-PhD-level accuracy by 8% on GPQA, hard science problems benchmark where the previous best was Claude 3.5 Sonnet with 59.4.
🤯 Beats human-PhD-level accuracy by 8% on GPQA, hard science problems benchmark where the previous best was Claude 3.5 Sonnet with 59.4.
new_line
text
🤯 Scores 78.2% on vision benchmark MMMU, making it the first model competitive w/ human experts
🤯 Scores 78.2% on vision benchmark MMMU, making it the first model competitive w/ human experts
new_line
text
🤯 GPT-4o on MATH scored 60% ⇒ o1 scores 95%
🤯 GPT-4o on MATH scored 60% ⇒ o1 scores 95%
new_line
new_line
text
How did they pull this? Sadly OpenAI keeps increasing their performance in “making cryptic AF reports to not reveal any real info”, so here are excerpts:
How did they pull this? Sadly OpenAI keeps increasing their performance in “making cryptic AF reports to not reveal any real info”, so here are excerpts:
new_line
new_line
text
💬 “𝗼𝟭 𝘂𝘀𝗲𝘀 𝗮 𝗰𝗵𝗮𝗶𝗻 𝗼𝗳 𝘁𝗵𝗼𝘂𝗴𝗵𝘁 𝘄𝗵𝗲𝗻 𝗮𝘁𝘁𝗲𝗺𝗽𝘁𝗶𝗻𝗴 𝘁𝗼 𝘀𝗼𝗹𝘃𝗲 𝗮 𝗽𝗿𝗼𝗯𝗹𝗲𝗺. 𝗧𝗵𝗿𝗼𝘂𝗴𝗵 𝗿𝗲𝗶𝗻𝗳𝗼𝗿𝗰𝗲𝗺𝗲𝗻𝘁 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴, 𝗼𝟭 𝗹𝗲𝗮𝗿𝗻𝘀 𝘁𝗼 𝗵𝗼𝗻𝗲 𝗶𝘁𝘀 𝗰𝗵𝗮𝗶𝗻 𝗼𝗳 𝘁𝗵𝗼𝘂𝗴𝗵𝘁 𝗮𝗻𝗱 𝗿𝗲𝗳𝗶𝗻𝗲 𝘁𝗵𝗲 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀 𝗶𝘁 𝘂𝘀𝗲𝘀. It learns to recognize and correct its mistakes.”
💬 “𝗼𝟭 𝘂𝘀𝗲𝘀 𝗮 𝗰𝗵𝗮𝗶𝗻 𝗼𝗳 𝘁𝗵𝗼𝘂𝗴𝗵𝘁 𝘄𝗵𝗲𝗻 𝗮𝘁𝘁𝗲𝗺𝗽𝘁𝗶𝗻𝗴 𝘁𝗼 𝘀𝗼𝗹𝘃𝗲 𝗮 𝗽𝗿𝗼𝗯𝗹𝗲𝗺. 𝗧𝗵𝗿𝗼𝘂𝗴𝗵 𝗿𝗲𝗶𝗻𝗳𝗼𝗿𝗰𝗲𝗺𝗲𝗻𝘁 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴, 𝗼𝟭 𝗹𝗲𝗮𝗿𝗻𝘀 𝘁𝗼 𝗵𝗼𝗻𝗲 𝗶𝘁𝘀 𝗰𝗵𝗮𝗶𝗻 𝗼𝗳 𝘁𝗵𝗼𝘂𝗴𝗵𝘁 𝗮𝗻𝗱 𝗿𝗲𝗳𝗶𝗻𝗲 𝘁𝗵𝗲 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀 𝗶𝘁 𝘂𝘀𝗲𝘀. It learns to recognize and correct its mistakes.”
new_line
new_line
text
And of course, they decide to hide the content of this precious Chain-of-
And of course, they decide to hide the content of this precious Chain-of-
new_line
text
Thought. Would it be for maximum profit? Of course not, you awful capitalist, it’s to protect users:
Thought. Would it be for maximum profit? Of course not, you awful capitalist, it’s to protect users:
new_line
new_line
text
💬 “We also do not want to make an unaligned chain of thought directly visible to users.”
💬 “We also do not want to make an unaligned chain of thought directly visible to users.”
new_line
new_line
text
They’re right, it would certainly have hurt my feelings to see the internal of this model tearing apart math problems.
They’re right, it would certainly have hurt my feelings to see the internal of this model tearing apart math problems.
new_line
new_line
text
🤔 I suspect it could be not only CoT, but also some agentic behaviour where the model can just call a code executor. The kind of score improvement the show certainly looks like the ones you see with agents.
🤔 I suspect it could be not only CoT, but also some agentic behaviour where the model can just call a code executor. The kind of score improvement the show certainly looks like the ones you see with agents.
new_line
new_line
text
This model will be immediately released for ChatGPT and some “trusted API users”.
This model will be immediately released for ChatGPT and some “trusted API users”.
new_line
new_line
text
Let’s start cooking to release the same thing in 6 months! 🚀
Let’s start cooking to release the same thing in 6 months! 🚀
𝐎𝐩𝐞𝐧𝐀𝐈 𝐟𝐢𝐧𝐚𝐥𝐥𝐲 𝐫𝐞𝐯𝐞𝐚𝐥𝐬 “🍓”: 𝐜𝐫𝐚𝐳𝐲 𝐜𝐡𝐚𝐢𝐧-𝐨𝐟-𝐭𝐡𝐨𝐮𝐠𝐡𝐭-𝐭𝐮𝐧𝐞𝐝 𝐦𝐨𝐝𝐞𝐥 >> 𝐆𝐏𝐓-𝟒𝐨 💥

OpenAI had hinted at a mysterious “project strawberry” for a long time: 𝘁𝗵𝗲𝘆 𝗽𝘂𝗯𝗹𝗶𝘀𝗵𝗲𝗱 𝘁𝗵𝗶𝘀 𝗻𝗲𝘄 𝗺𝗼𝗱𝗲𝗹 𝗰𝗮𝗹𝗹𝗲𝗱 “𝗼𝟭” 𝟭𝗵𝗼𝘂𝗿 𝗮𝗴𝗼, 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗶𝘀 𝗷𝘂𝘀𝘁 𝗺𝗶𝗻𝗱-𝗯𝗹𝗼𝘄𝗶𝗻𝗴.

🤯 Ranks among the top 500 students in the US in a qualifier for the USA Math Olympiad
🤯 Beats human-PhD-level accuracy by 8% on GPQA, hard science problems benchmark where the previous best was Claude 3.5 Sonnet with 59.4.
🤯 Scores 78.2% on vision benchmark MMMU, making it the first model competitive w/ human experts
🤯 GPT-4o on MATH scored 60% ⇒ o1 scores 95%

How did they pull this? Sadly OpenAI keeps increasing their performance in “making cryptic AF reports to not reveal any real info”, so here are excerpts:

💬 “𝗼𝟭 𝘂𝘀𝗲𝘀 𝗮 𝗰𝗵𝗮𝗶𝗻 𝗼𝗳 𝘁𝗵𝗼𝘂𝗴𝗵𝘁 𝘄𝗵𝗲𝗻 𝗮𝘁𝘁𝗲𝗺𝗽𝘁𝗶𝗻𝗴 𝘁𝗼 𝘀𝗼𝗹𝘃𝗲 𝗮 𝗽𝗿𝗼𝗯𝗹𝗲𝗺. 𝗧𝗵𝗿𝗼𝘂𝗴𝗵 𝗿𝗲𝗶𝗻𝗳𝗼𝗿𝗰𝗲𝗺𝗲𝗻𝘁 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴, 𝗼𝟭 𝗹𝗲𝗮𝗿𝗻𝘀 𝘁𝗼 𝗵𝗼𝗻𝗲 𝗶𝘁𝘀 𝗰𝗵𝗮𝗶𝗻 𝗼𝗳 𝘁𝗵𝗼𝘂𝗴𝗵𝘁 𝗮𝗻𝗱 𝗿𝗲𝗳𝗶𝗻𝗲 𝘁𝗵𝗲 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀 𝗶𝘁 𝘂𝘀𝗲𝘀. It learns to recognize and correct its mistakes.”

And of course, they decide to hide the content of this precious Chain-of-
Thought. Would it be for maximum profit? Of course not, you awful capitalist, it’s to protect users:

💬 “We also do not want to make an unaligned chain of thought directly visible to users.”

They’re right, it would certainly have hurt my feelings to see the internal of this model tearing apart math problems.

🤔 I suspect it could be not only CoT, but also some agentic behaviour where the model can just call a code executor. The kind of score improvement the show certainly looks like the ones you see with agents.

This model will be immediately released for ChatGPT and some “trusted API users”.

Let’s start cooking to release the same thing in 6 months! 🚀
👀
John6666 den0620 louisbrulenaudet jkohnbryan78 edison1 ar08
🤝
pduf
/avatars/b2725bb163fa15d6c5856121780d52eb.svg
Ci Splunk
Csplk
user