Blunt truth: LLM deployments are quietly bleeding money. A wrong config can make the same model 8× slower and 25× pricier.
With MaverIQ, we fix it by auto-deploying LLMs to meet each user’s intent—at a fraction of today’s cost
@dimliak99
@prasoon_sinha25
Tianrui Hu
@NeerajaJY
With MaverIQ, we fix it by auto-deploying LLMs to meet each user’s intent—at a fraction of today’s cost
@dimliak99
@prasoon_sinha25
Tianrui Hu
@NeerajaJY
Dimitris presenting our work on Intent-based LLM inference serving, MaverIQ, at SC'25, earlier this week!
@UT_SysML
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Congrats, @prasoon_sinha25 👏
Looking forward to @ACMSoCC'25!
Our group, @UT_SysML, will present 2 papers.
@prasoon_sinha25 will present ALAP, our intent-based serverless computing platform.
@li_ruihao will present Oneiros, a parameter remapping engine that accelerates multi-tenant LLM inference serving.
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Congrats, @li_ruihao!
My second Ph.D. student, co-advised with Lizy John, Ruihao Li, defended successfully! Ruihao is headed to Meta Research soon.
Congrats @li_ruihao, really proud of you :)
@UT_SysML @UTAustin @utexasece
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Congrats, Susy!! @esalcorta
A proud moment as my first co-advised PhD student, Erika Alcorta, graduates 🎓
It was an honor to hood her with Prof. Gerstlauer (@AGerstlauer). She’s now advancing ML for Systems at Ampere Computing. Excited to see all that lies ahead! 🚀
Congrats, Susy! @esalcorta
@UT_SysML
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