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| Google DeepMind Scholars Program | |
|---|---|
| Name | Google DeepMind Scholars Program |
| Established | 2018 |
| Type | Fellowship |
| Sponsor | Google DeepMind |
| Location | London |
Google DeepMind Scholars Program
The Google DeepMind Scholars Program was a fellowship initiative providing financial support, mentorship, and networking for emerging researchers and practitioners in artificial intelligence and machine learning. Founded to increase representation and foster talent from underrepresented communities, the program connected scholars with industry researchers, academic institutions, and professional networks. Recipients engaged with research projects, workshops, and conferences spanning theoretical and applied topics.
The program operated at the intersection of technology companies and academic research, drawing participants from institutions such as University of Cambridge, University College London, Imperial College London, Oxford University, Stanford University, Massachusetts Institute of Technology, Carnegie Mellon University, University of Toronto, ETH Zurich, and Tsinghua University. Partners and collaborators included organizations like Google Research, DeepMind Technologies, OpenAI, Microsoft Research, Facebook AI Research, Allen Institute for AI, Vector Institute, CIFAR, Alan Turing Institute, and Montreal Institute for Learning Algorithms. Events and venues associated with the program featured conferences and workshops such as NeurIPS, ICML, CVPR, ACL, ICLR, KDD, AAAI, and EMNLP.
The initiative was launched amid broader industry programs modeled after fellowships such as the Rhodes Scholarship, the Fulbright Program, and corporate fellowships from Facebook Fellowship Program and Microsoft Research Fellowship. Founders and early proponents included researchers affiliated with Demis Hassabis, Shane Legg, Mustafa Suleyman, key figures in DeepMind's leadership and advisory circles. The program timeline intersected with major industry milestones like DeepMind's acquisition by Alphabet Inc., breakthroughs such as AlphaGo, AlphaZero, AlphaFold, and policy debates with institutions including European Commission, UK Research and Innovation, and National Science Foundation.
Eligible applicants were typically graduate students, postdoctoral researchers, and early-career professionals from institutions including Harvard University, Princeton University, Yale University, Columbia University, University of California, Berkeley, University of Washington, Peking University, Seoul National University, University of Melbourne, and University of Sydney. The fellowship package included stipends, conference travel funds, and mentorship from researchers at DeepMind Technologies, Google Brain, IBM Research, Huawei Noah's Ark Lab, Baidu Research, and Tencent AI Lab. The program emphasized inclusivity with outreach efforts coordinated with Black in AI, Women in Machine Learning, Latinx in AI, Queer in AI, NeurIPS Diversity Scholarships, and university diversity offices such as those at Columbia University and University of Toronto.
Selection panels comprised academics and industry researchers from organizations like DeepMind Technologies, Google Research, Stanford University, University of Oxford, Yoshua Bengio, Geoffrey Hinton, Yann LeCun, Fei-Fei Li, Gary Marcus, Ian Goodfellow, Richard Sutton, David Silver, Sergey Levine, Pieter Abbeel, Ruslan Salakhutdinov, and representatives from Royal Society. Evaluation criteria included research potential evidenced by publications in venues such as NeurIPS, ICML, CVPR, ICLR, ACL, and EMNLP, contributions to open-source projects like TensorFlow, PyTorch, JAX, and community involvement with organizations including OpenAI Scholars and Mozilla Foundation.
Scholars accessed mentorship from principal investigators and research scientists associated with labs and centers including DeepMind Technologies, Google Brain, MILA (Quebec AI Institute), Vector Institute, Alan Turing Institute, Berkeley Artificial Intelligence Research Lab, Stanford AI Lab, MIT Computer Science and Artificial Intelligence Laboratory, and CMU Robotics Institute. The curriculum covered topics reflected in canonical works and datasets tied to projects like ImageNet, COCO (dataset), GLUE, SQuAD, and methods rooted in research from authors such as Ian Goodfellow, Yoshua Bengio, Andrew Ng, Christopher Bishop, Judea Pearl, Stuart Russell, Peter Norvig, Michael Jordan, and Daphne Koller. Computational resources and cloud credits leveraged platforms including Google Cloud Platform, high-performance compute clusters at institutions like University of Cambridge and ETH Zurich, and community tools promoted by Kaggle and GitHub.
Alumni progressed to positions at companies and labs such as DeepMind Technologies, Google Research, OpenAI, Microsoft Research, Facebook AI Research, Amazon Research, Apple Machine Learning Research, NVIDIA Research, and startups incubated in ecosystems like Silicon Valley, Cambridge (UK), Toronto (city), Montreal (city), and Beijing (city). Notable career outcomes included roles in research science, applied machine learning engineering, and academic appointments at University of Oxford, Imperial College London, University of Toronto, Columbia University, University of California, Berkeley, and Peking University. Alumni publications appeared in proceedings of NeurIPS, ICLR, ICML, and collaborations with consortia such as CIFAR and policy bodies including OECD.
Critiques mirrored concerns raised in debates involving OpenAI, Facebook, Google, and other tech entities over issues like corporate influence on research agendas, conflicts noted in analysis by commentators at The New York Times, The Guardian, Wired, MIT Technology Review, and investigative reports referencing regulatory interest from Competition and Markets Authority and European Commission. Academic critics from institutions such as University of Cambridge, Princeton University, University of Oxford, and Harvard University argued about transparency, diversity metrics, and ethics, paralleling controversies around models like GPT-3, DALL·E, PaLM, and governance discussions in forums including UNESCO and PCAST.
Category:Scholarships