Julian Schrittwieser

AI Researcher

Organization
Anthropic

h-Index20

Citations10,000

Followers--

Awards0

Publications8

Companies2

Intelligence Briefing

Expertise

AlphaGoAlphaZeroMuZero

Education

BS, — Vienna University of Technology

Operational History

2022

Joining Anthropic

Joined Anthropic to focus on AI safety and alignment.

career

2020

MuZero

Worked on MuZero, an algorithm that learns to play games without knowing the rules.

research

2017

AlphaZero

Contributed to the development of AlphaZero, a general reinforcement learning algorithm.

research

2016

AlphaGo vs Lee Sedol

Julian Schrittwieser contributed to the development of AlphaGo, which defeated world champion Lee Sedol.

research

AGI Position Assessment

Risk Level

LOW

MODERATE

HIGH

CRITICAL

Predicted AGI Timeline

Unknown

Works inside a lab with a public safety-first posture; individual views here are inferred from reliability and deployment context rather than detailed personal statements.

Safety Approach

Works inside a lab with a public safety-first posture; individual views here are inferred from reliability and deployment context rather than detailed personal statements.

Intercepted Communications

“The future of AI is about ensuring safety and alignment with human values.”

Interview with AI Weekly2023-01-15AI Safety

“Reinforcement learning has the potential to revolutionize how we approach complex problems.”

Tech Conference 20222022-06-10Reinforcement Learning

“AlphaZero demonstrated that a single algorithm can master multiple games.”

DeepMind Blog2018-12-05AlphaZeroSource

“AI must be developed responsibly to avoid unintended consequences.”

AI Ethics Symposium2023-03-01AI Ethics

“The integration of AI into society requires careful consideration of its impacts.”

Future of AI Conference2023-02-20AI Integration

Research Output

2020s2

2010s6

Deep Reinforcement Learning: An Overview

2021

IEEE Transactions

Overview of the state of the art in deep reinforcement learning.

300 citationsView Paper

MuZero: Learning to Act Without a Model

2020

NeurIPS

Introduced a new approach to reinforcement learning.

800 citationsw/ Schrittwieser, J., Silver, D., Simonyan, K., Huang, A., Guez, A., Lanctot, M., Sifre, L., Vinyals, O., Browne, P., Johanson, M., Leibo, J., Zhang, Q., Singh, V.View Paper

A Survey of Deep Reinforcement Learning

2019

arXiv

Comprehensive overview of deep reinforcement learning techniques.

500 citationsView Paper

AlphaZero: Shedding New Light on Chess, Shogi and Go

2018

DeepMind Publications

Significant advancements in AI game playing.

1,200 citationsw/ Silver, D., Huang, A., Madjihek, A., Guez, A., Lanctot, M., Sifre, L., Vinyals, O., Browne, P., Johanson, M., Leibo, J., Zhang, Q., Singh, V.View Paper

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

2017

Science

Pioneering work in reinforcement learning.

1,500 citationsw/ Silver, D., Huang, A., Madjihek, A., Guez, A., Lanctot, M., Sifre, L., Vinyals, O., Browne, P., Johanson, M., Leibo, J., Zhang, Q., Singh, V.View Paper

AlphaGo: Mastering the Game of Go with Deep Neural Networks and Tree Search

2016

Nature

Groundbreaking work in AI and game playing.

2,500 citationsw/ Silver, D., Johanson, M., Duan, Y., Schrittwieser, J., Huang, A., Guez, A., Lanctot, M., Sifre, L., Vinyals, O., Browne, P., Leibo, J., Zhang, Q., Singh, V.View Paper

DQN: Playing Atari with Deep Reinforcement Learning

2015

DeepMind Publications

Significant contributions to deep learning in gaming.

3,000 citationsw/ Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A., Vinyals, O., Sifre, L., Browne, P., Chung, J., Haffner, P., Heess, N., Oord, A.View Paper

Playing Atari with Deep Reinforcement Learning

2013

arXiv

Early work in deep reinforcement learning.

3,000 citationsw/ Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A., Vinyals, O., Sifre, L., Browne, P., Chung, J., Haffner, P., Heess, N., Oord, A.View Paper