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Generative AI digs the graves of traditional search engines and virtual assistants

The latest advances are aimed at creating more human-like systems that are capable of planning and executing complex tasks as well as, or better than, people

Stanford universityUnited statesMountain viewSouth koreaSundai pichaiSam altmanSergey brinSergey shykevichMinsu jangGoogle deepmindChirag shahMichelle bakLarry pageJan leikeLiz reidDemis hassabis

ETRI Develops An Automated Benchmark for Language-based Task Planners

ETRI research team has developed a technology that automatically evaluates the performance of task plans generated by Large Language Models (LLMs), which paves

Jaehong kimMinsu jangGoogle saycanRobotics labInstitute for informationTechnology planning evaluationMassachusetts institute of technologyInternational conference on learning representationsDevelopment of uncertaintyAllen instituteRobotics research sectionMinistry of scienceTelecommunications research instituteLarge language modelsLanguage oriented taskInternational conference

ETRI Unveils Automated Benchmark for Task Planners

ETRI Unveils Automated Benchmark for Task Planners
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Jaehong kimMinsu jangGoogle saycanMassachusetts institute of technologyInternational conference on learning representationsAllen instituteRobotics research sectionTelecommunications research instituteRobotics labLarge language modelsLanguage oriented taskInternational conferenceLearning representationsMassachusetts instituteIn context example selection

Researchers develop an automated benchmark for language-based task planners

Researchers develop an automated benchmark for language-based task planners
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Jaehong kimGoogle saycanMinsu jangInternational conference on learning representationsRobotics labAllen instituteRobotics research sectionMassachusetts institute of technologyTelecommunications research instituteCase studyProcedural generation followingLarge language modelsInternational conferenceLearning representationsMassachusetts instituteIn context example selection

Open-source training framework increases the speed of large language model pre-training when failures arise

Open-source training framework increases the speed of large language model pre-training when failures arise
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Rheinland pfalzUnited statesMosharaf chowdhuryUniversity of michiganMinsu jangOperating systems principlesResilient distributed trainingLarge models using pipeline templates