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Following the MLCommons Q3 MLPerf Inference results announcement on the morning of Tuesday 9th September on the keynote stage, MLCommons Founder & Executive Director David Kantar will deliver a detailed analysis of the results followed by a Q&A session from the audience. 

Author:

David Kanter

Founder & Executive Director
MLCommons

David co-founded and is the Head of MLPerf for MLCommons, the world leader in building benchmarks for AI. MLCommons is an open engineering consortium with a mission to make AI better for everyone through benchmarks and data. The foundation for MLCommons began with the MLPerf benchmarks in 2018, which rapidly scaled as a set of industry metrics to measure machine learning performance and promote transparency of machine learning techniques. In collaboration with its 125+ members, global technology providers, academics, and researchers, MLCommons is focused on collaborative engineering work that builds tools for the entire AI industry through benchmarks and metrics, public datasets, and measurements for AI Safety. Our software projects are generally available under the Apache 2.0 license and our datasets generally use CC-BY 4.0.

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David Kanter

Founder & Executive Director
MLCommons

David co-founded and is the Head of MLPerf for MLCommons, the world leader in building benchmarks for AI. MLCommons is an open engineering consortium with a mission to make AI better for everyone through benchmarks and data. The foundation for MLCommons began with the MLPerf benchmarks in 2018, which rapidly scaled as a set of industry metrics to measure machine learning performance and promote transparency of machine learning techniques. In collaboration with its 125+ members, global technology providers, academics, and researchers, MLCommons is focused on collaborative engineering work that builds tools for the entire AI industry through benchmarks and metrics, public datasets, and measurements for AI Safety. Our software projects are generally available under the Apache 2.0 license and our datasets generally use CC-BY 4.0.

Large language models can now power capable software agents, yet real‑world success comes from disciplined engineering rather than flashy frameworks. Most reliable agents are built from simple, composable patterns instead of heavy abstractions.


The talk will introduce patterns to add complexity and autonomy only when it pays off. Attendees should leave with a practical decision framework for escalating from a single prompt to multi‑step agents, also keeping in mind guardrails for shipping trustworthy, cost‑effective agents at scale. 

Author:

Sushant Mehta

Research Engineer
Google Deepmind
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Sushant Mehta

Research Engineer
Google Deepmind

Author:

Sherman Ikemoto

Group Director
Cadence

Sherman Ikemoto is the Sales Development Group Director at Cadence Design Systems, where he leads global business development for the innovative Reality DC Digital Twin solution. With a passion for addressing challenges in data center design, performance, and sustainability, Sherman brings extensive expertise to the forefront of this critical industry. Previously, Sherman served as Managing Director and Board Member at Future Facilities, the pioneer of the original data center Digital Twin, and as North America Sales and Marketing Director at Flomerics, where he helped introduce computational fluid dynamics modeling to electronics cooling design. During his tenure at Future Facilities, Sherman was a sought-after speaker at prominent industry events like ITW, Data Center World, Uptime Symposium, and Data Center Dynamics. Sherman holds a Bachelor of Science in Mechanical Engineering (BSME) from San Jose State University, where he was a member of the Tau Beta Pi engineering honor society, and a Master of Science in Mechanical Engineering (MSME) from Santa Clara University. His career reflects a deep commitment to advancing sustainable and efficient technologies for the data center industry.

... read more

Sherman Ikemoto

Group Director
Cadence

Sherman Ikemoto is the Sales Development Group Director at Cadence Design Systems, where he leads global business development for the innovative Reality DC Digital Twin solution. With a passion for addressing challenges in data center design, performance, and sustainability, Sherman brings extensive expertise to the forefront of this critical industry. Previously, Sherman served as Managing Director and Board Member at Future Facilities, the pioneer of the original data center Digital Twin, and as North America Sales and Marketing Director at Flomerics, where he helped introduce computational fluid dynamics modeling to electronics cooling design. During his tenure at Future Facilities, Sherman was a sought-after speaker at prominent industry events like ITW, Data Center World, Uptime Symposium, and Data Center Dynamics. Sherman holds a Bachelor of Science in Mechanical Engineering (BSME) from San Jose State University, where he was a member of the Tau Beta Pi engineering honor society, and a Master of Science in Mechanical Engineering (MSME) from Santa Clara University. His career reflects a deep commitment to advancing sustainable and efficient technologies for the data center industry.