Research
Together AI Showcases Research at ICML 2026
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Why it matters
- →Together AI's research spans the entire AI stack, ensuring comprehensive optimization.
- →Their DSGym framework standardizes agent evaluation, promoting fair and consistent measurement.
- →Aurora's adaptive speculative decoding enhances throughput, directly impacting production efficiency.
Together AI presented nine papers at ICML 2026, emphasizing their research across the AI stack from agents to GPU kernels. Their work includes the DSGym framework, which standardizes the evaluation of data-science agents, and the Aurora paper on adaptive speculative decoding, which improves throughput in production environments. These advancements demonstrate Together AI's commitment to integrating research with practical applications, ensuring that each layer of the AI stack is optimized for efficiency and performance.
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MIT News AI
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