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ODSC East 2024 Keynote: DeepMind’s Anna Goldie on Deep Reinforcement Learning in the Real World ODSC East 2024 Keynote: DeepMind’s Anna Goldie on Deep Reinforcement Learning in the Real World
In the evolving landscape of artificial intelligence, reinforcement learning (RL) has transcended its conventional boundaries, showcasing not just theoretical prowess but... ODSC East 2024 Keynote: DeepMind’s Anna Goldie on Deep Reinforcement Learning in the Real World

In the evolving landscape of artificial intelligence, reinforcement learning (RL) has transcended its conventional boundaries, showcasing not just theoretical prowess but practical, scalable solutions across challenging domains. At the forefront of these advancements is Anna Goldie, a senior staff research scientist at Google DeepMind, whose groundbreaking work is reshaping how we think about RL’s application from chip design to large language models (LLMs). You can watch Anna Goldie’s entire keynote here.

Watch this ODSC East 2024 keynote by DeepMind’s Anna Goldie as she discusses the power of reinforcement learning in chip design and LLMs.

In-Person and Virtual Conference

September 5th to 6th, 2024 – London

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The Power of RL in Large Language Models

Reinforcement learning has long been synonymous with gaming scenarios where AI triumphs over human strategy. However, its integration with LLMs marks a significant shift towards more dynamic, responsive AI systems. Anna’s research delves into RL for LLMs, emphasizing scalable supervision techniques that align AI outputs with human preferences. This approach, often referred to as Constitutional AI or Reinforcement Learning from AI Feedback (RLAIF), is pivotal in developing AI that not only performs tasks but does so in a way that resonates with human values and ethics.

Transforming Chip Design with RL

One of the stellar real-world applications of RL under Anna’s belt is chip floorplanning. Traditionally, designing the physical layout of a chip is a time-consuming process, demanding weeks of expert human intervention. However, by harnessing RL, Anna’s team at Google has revolutionized this task, creating chip layouts that either meet or exceed human expertise in mere hours. This method, published in the prestigious journal Nature, has been employed to optimize the design of Google’s flagship AI accelerator, the Tensor Processing Unit (TPU), enhancing performance across its last four generations.

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Anna Goldie: At the Nexus of Innovation

Anna’s journey in AI and machine learning is as impressive as her contributions. With dual bachelor’s degrees in Computer Science and Linguistics and a master’s in Computer Science from MIT, followed by her ongoing PhD at Stanford’s NLP Group, Anna’s academic credentials are robust. Her professional timeline, featuring roles at Anthropic and as the co-founder and lead of the ML for Systems team at Google Brain, showcases a deep commitment to advancing machine learning technologies.

Her work’s impact is recognized globally, earning her a spot among MIT Technology Review’s 35 Innovators Under 35. Moreover, her research has consistently made headlines in major media outlets like CNBC, IEEE Spectrum, and WIRED, underscoring the societal and technological relevance of her work.

Why This Matters

The implications of Anna Goldie’s work in deep reinforcement learning are profound. For data scientists and industry professionals, these advancements are not just theoretical exercises but practical solutions that promise to streamline complex processes, reduce costs, and enhance efficiency in various sectors. Moreover, the ethical alignment of AI with human values through scalable supervision opens a new chapter in responsible AI development, ensuring that as machines learn and evolve, they do so under the guidance of humanistic principles.

In-Person & Virtual Data Science Conference

October 29th-31st, 2024 – Burlingame, CA

Join us for 300+ hours of expert-led content, featuring hands-on, immersive training sessions, workshops, tutorials, and talks on cutting-edge AI tools and techniques, including our first-ever track devoted to AI Robotics!

 

Conclusion

In conclusion, as we stand on the cusp of a new era in AI and machine learning, figures like Anna Goldie remind us of the transformative power of dedicated research and innovation. Her work with deep reinforcement learning not only challenges the existing paradigms in AI but also sets the stage for future technologies that will continue to redefine the boundaries of what machines can achieve. For those immersed in the field of data science and AI, her contributions are both a roadmap and a beacon, guiding the way towards more integrated, ethical, and efficient AI systems.

If you enjoyed this overview, then you won’t want to miss another keynote. Check out ODSC’s next conference, ODSC Europe and enjoy 40 trainings/workshops, 130 hybrid sessions, and more! If you become one of the first attendees to ODSC Europe, you’ll save 75% by buying early. Not far after that is ODSC West this October 29th-31st!

ODSC Team

ODSC Team

ODSC gathers the attendees, presenters, and companies that are shaping the present and future of data science and AI. ODSC hosts one of the largest gatherings of professional data scientists with major conferences in USA, Europe, and Asia.

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