AITOPAI热报
How-toMulti-sourceSelected73°

GPT-6 Astra Case Collection

让AI整理了两套资料，方便大家测试Astra： GPT-6 Astra：30 个案例线索与复现提示词 - 飞书云文档 https://t.co/fZ6qNj8FwH ‍​⁡​‌‍‍⁢​‌‌⁣⁤​⁢...

向阳乔木@vista8
Post· 11 sources
View the post
Why we picked it

These prompt collections help developers and users test GPT-6 Astra with ready-made cases, saving time on prompt engineering.

The creator has compiled two sets of resources for testing GPT-6 Astra. One document contains 30 case prompts and reproduction clues. The other offers a panoramic guide to GPT-6 Astra prompts and cases. Both resources are hosted on Feishu cloud documents.

Original · 向阳乔木

让AI整理了两套资料，方便大家测试Astra： GPT-6 Astra：30 个案例线索与复现提示词 - 飞书云文档 https://t.co/fZ6qNj8FwH ‍​⁡​‌‍‍⁢​‌‌⁣⁤​⁢...

让AI整理了两套资料，方便大家测试Astra： GPT-6 Astra：30 个案例线索与复现提示词 - 飞书云文档 xiangyangqiaomu.feishu.cn/docx/ErPhdJD85… ‍​⁡​‌‍‍⁢​‌‌⁣⁤​⁢‌⁡​‌​‌⁢‌‌‍⁡⁢‌⁢⁢‌​‌​​GPT-6 Astra 提示词与案例全景指南 - 飞书云文档 xiangyangqiaomu.feishu.cn/docx/FBFGdBAtP… 💬 0 🔄 0 ❤️ 1 👀 699 📊 1 ⚡

#GPT-6 Astra#prompt engineering#Feishu#testing#AI tools

Keep reading

Recent stories with the same tag or section
ModelsUS vs ChinaMulti-sourceSelected23:55
Claude Sonnet 5.5 and GPT-6 Astra tie on MLCR-AA leaderboard

The split matters more than the tie: Anthropic models dominate completeness, with Claude Sonnet 5.5 at 64.8% versus 42.2% for the best non-Anthropic model, while OpenAI models dominate accuracy, led by GPT-6.1 Sol at 96.7%. Teams deploying models for medical record review should pick based on which failure mode they can tolerate. Even top models still fail more than half of the benchmark's questions, so human review remains necessary.

#Claude Sonnet 5.5#GPT-6 Astra#Wisedocs#Qwen3.8
Event
官方账号Artificial Analysis@ArtificialAnlys11 sourcesSource