Positive users praise the BEHAVIOR challenge's honest focus on failure recovery and real-world household reliability, while negative users feel humbled by the low 12.4% success rates exposing robotics limits beyond AGI hype.
Based on 8 visible X reactions from 11 accounts; directional sample.
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@drfeifei @wensi_ai @stefyfren @cgokmenAI @yalcintur36 @minyeongkim_ @BrndaHere2Chl @AndiXu1111 @RavenHuang4 @RuohanZhang76 @jiajunwu_cs @EvansXuHan @jin_lynn808 @Hang_Yin_ @ChengshuEricLi @josiah_is_wong @sanjana__z @YunfanJiang @wenlong_huang @RobobertoMM @YunzhuLiYZ @ManlingLi_ @Weiyu_Liu_ @silviocinguetta @hyogweon @SimovationInc @nvidia @IMDAsg @StanfordHAI @SchmidtFutures Big ups to the sponsors, this stuff could go big fr!
@drfeifei @wensi_ai @stefyfren @cgokmenAI @yalcintur36 @minyeongkim_ @BrndaHere2Chl @AndiXu1111 @RavenHuang4 @RuohanZhang76 @jiajunwu_cs @EvansXuHan @jin_lynn808 @Hang_Yin_ @ChengshuEricLi @josiah_is_wong @sanjana__z @YunfanJiang @wenlong_huang @RobobertoMM @YunzhuLiYZ @ManlingLi_ @Weiyu_Liu_ @silviocinguetta @hyogweon It is always great to see team leaders recognize those people who have helped them realize their goals including their collaborators, well done doc
@drfeifei "Where do today's models fail to generalize" is the one that matters most imo — household tasks have so much long-tail variation that benchmark performance rarely translates to real homes. Excited to see what BEHAVIOR surfaces this year.
@drfeifei failure recovery is the part that separates demos from real deployment. most systems just retry the same grasp three times. would love to see how BEHAVIOR handles novel error states.
@drfeifei @wensi_ai @stefyfren @cgokmenAI @yalcintur36 @minyeongkim_ @BrndaHere2Chl @AndiXu1111 @RavenHuang4 @RuohanZhang76 @jiajunwu_cs @EvansXuHan @jin_lynn808 @Hang_Yin_ @ChengshuEricLi @josiah_is_wong @sanjana__z @YunfanJiang @wenlong_huang @RobobertoMM @YunzhuLiYZ @ManlingLi_ @Weiyu_Liu_ @silviocinguetta @hyogweon @SimovationInc @nvidia @IMDAsg @StanfordHAI @SchmidtFutures Big ups to the sponsors, this stuff could go big fr!
@drfeifei @wensi_ai @stefyfren @cgokmenAI @yalcintur36 @minyeongkim_ @BrndaHere2Chl @AndiXu1111 @RavenHuang4 @RuohanZhang76 @jiajunwu_cs @EvansXuHan @jin_lynn808 @Hang_Yin_ @ChengshuEricLi @josiah_is_wong @sanjana__z @YunfanJiang @wenlong_huang @RobobertoMM @YunzhuLiYZ @ManlingLi_ @Weiyu_Liu_ @silviocinguetta @hyogweon It is always great to see team leaders recognize those people who have helped them realize their goals including their collaborators, well done doc
@drfeifei "Where do today's models fail to generalize" is the one that matters most imo — household tasks have so much long-tail variation that benchmark performance rarely translates to real homes. Excited to see what BEHAVIOR surfaces this year.
@drfeifei failure recovery is the part that separates demos from real deployment. most systems just retry the same grasp three times. would love to see how BEHAVIOR handles novel error states.
@drfeifei Kind of humbling that the winning solution got 12.4%. We talk about AGI constantly but a robot still can't reliably pour a drink in a diner.
@drfeifei The 12.4% success rate says a lot. The hardest part of robotics isn’t intelligence anymore—it’s reliability in the real world.
1/N Long horizon, complex tasks that truly matter in everyday life are not solved problems by today’s robotics, requiring planning, object detection, object manipulation, and failure recovery. That's why Stanford's BEHAVIOR Challenge is back for year 2! Last year, the winning solution reached only 12.4% full task success. This year, the BEHAVIOR challenge has more tasks, better evaluation, and is easier to use. 🚨 ⏰ Submission deadline: 10/16/2026 📣 Winners announced: 11/04/2026 🏆 Prize pool: $11,000
BEHAVIOR is a really cool benchmark, these kinds of long horizon tasks are I think much more representative of what we would like robots to do https://twitter.com/drfeifei/status/2076729080679186849
Positive users praise the BEHAVIOR challenge's honest focus on failure recovery and real-world household reliability, while negative users feel humbled by the low 12.4% success rates exposing robotics limits beyond AGI hype.
Based on 8 visible X reactions from 11 accounts; directional sample.
Ask a question below.
Published answers will appear here.
@drfeifei The 12.4% success rate says a lot. The hardest part of robotics isn’t intelligence anymore—it’s reliability in the real world.
1/N Long horizon, complex tasks that truly matter in everyday life are not solved problems by today’s robotics, requiring planning, object detection, object manipulation, and failure recovery. That's why Stanford's BEHAVIOR Challenge is back for year 2! Last year, the winning solution reached only 12.4% full task success. This year, the BEHAVIOR challenge has more tasks, better evaluation, and is easier to use. 🚨 ⏰ Submission deadline: 10/16/2026 📣 Winners announced: 11/04/2026 🏆 Prize pool: $11,000