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Turing at ICML 2025
Turing is accelerating AGI research for frontier AI labs—and we’re bringing that vision to ICML 2025. Visit us at Booth #407 to explore our latest demos, model improvement strategies, and cutting-edge research in machine learning.
Don’t miss our CEO & Co-Founder, Jonathan Siddharth, as he shares practical strategies for improving LLM benchmarks using real-world data for real-world use cases. Meet with our technical leaders and join us at our exclusive AGI networking event in Vancouver.
Tell us about your data goals
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Stop by to view hands-on demos, meet our AGI experts, and learn about our latest post-training advancements.
Learn how we close performance gaps through domain-specific testing and human-in-the-loop feedback.
Speaker: Jonathan Siddharth, CEO, Turing
Date & Time: 8:00 am
Location: West Meeting Room 220-222
Tuesday Jul 15, 2025 5:00-7:00pm
Wrap up your ICML day with Turing. Join fellow researchers and industry professionals at our ICML 2025 Happy Hour in Vancouver, 2 minutes from the Convention Centre. Network, share insights, and unwind over food and drinks while exploring collaborative opportunities in multimodal AGI and scalable machine learning. Space is limited. The location will be provided once your registration is approved.
From reasoning and robotics to RL gyms and multimodal agents, see how Turing is accelerating AGI research and deployment.
The top model scored just 56.8% across 700+ real-world tasks in business and STEM domains. Get the full breakdown of failure modes and domain-level gaps.
Request sample data packs with expert prompts, CoT traces, and verified outputs across STEM, finance, and competitive programming—built by domain experts, scored for logic, and aligned to GPQA, AIME, MMLU-Pro, and more.
Transition from legacy vendors without disrupting quality, tooling, or timelines. As a neutral data partner, Turing migrates your SFT, RLHF, eval, and RL workflows with clean compatibility and research-grade precision.
Join a global team of PhDs and experts tackling complex STEM challenges to improve reasoning, safety, and performance in cutting-edge LLMs.
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Capabilities built for frontier models
