Machine learning infrastructure @GoogleDeepMind. Previously Postdoc @ucberkeley and PhD @Cambridge_CL.
Joined January 2010
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6 Photos and videos
Ionel Gog retweeted
Apr 23
The DiLoCo team at Google DeepMind and Google Research is proud to release Decoupled DiLoCo, the next frontier for resilient AI pre-training.
Decoupled DiLoCo enables training with datacenters across the world, using heterogeneous hardware, and never halting the system despite hardware failures.
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Ionel Gog retweeted
19 Mar 2024
I'm super excited to release DiPaCo, a new kind of mixture of experts, that can scale engineering-wise to data centers across the entire world!
A few words about it in this thread 🧵
Google presents DiPaCo
Distributed Path Composition
Progress in machine learning (ML) has been fueled by scaling neural network models. This scaling has been enabled by ever more heroic feats of engineering, necessary for accommodating ML approaches that require high
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Presenting Confident Adaptive Language Modeling (CALM), a novel method that allows language models to dynamically modify computational effort when generating text. Learn how CALM can accelerate text generation while preserving output quality → goo.gle/3HJKzbM
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Excited to announce that @sukritkalra and @pschafhalter will be presenting at @EuroSys_conf on Thursday our work on developing a new execution model (D3), and an execution engine (ERDOS) that enables autonomous vehicles to adapt and to avoid collisions.
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Paper: dl.acm.org/doi/abs/10.1145/3…
Execution Engine Code: github.com/erdos-project/erd…
Self-driving Car Stack Code: github.com/erdos-project/pyl…
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At SoCC today, I will be presenting our work (with @m_isard and Martin Abadi) on offering efficient fault-tolerance for complex dataflow applications that combine batch, stream, and iterative processing. #socc21
Paper: dl.acm.org/doi/abs/10.1145/3…
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Today in the Unmanned Vehicle award session of #ICRA2021, @sukritkalra will present our work on Pylot, an adaptable platform for developing autonomous vehicles. Our platform provides plug and play modules to deploy AVs in simulation and real-world.
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The paper is available here: ionelgog.org/data/papers/202…, and the code is github.com/erdos-project/pyl… in case you want to take Pylot for a spin.
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Ionel Gog retweeted
19 Apr 2021
Working on self-driving cars? Check out our paper on Pylot, a modular pipeline for exploring latency-accuracy tradeoffs in self-driving cars (accepted to ICRA 2021).
arxiv.org/abs/2104.07830
28 Feb 2021
First ever accepted paper 🥳🎉
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Ionel Gog retweeted
27 Mar 2019
Bought a mechanical keyboard with more resistance so my code will be strongly typed.
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Ionel Gog retweeted
16 Oct 2018
Slides for our #osdi18 talk on Noria, a new data-flow system that makes web applications fast, are now available: pdos.csail.mit.edu/papers/no… (joint work with @Jonhoo, @xexd and others). Will take no more than 17 minutes to view, promised!
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Ionel Gog retweeted
30 Nov 2016
"Firmament: Fast, centralized cluster scheduling at scale" - Gog et al. 2016 blog.acolyer.org/2016/11/30/… #themorningpaper
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Ionel Gog retweeted
2 Nov 2016
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Ionel Gog retweeted
29 Aug 2016
Bayesians against discrimination! Ban genetic algorithms! Free variables! 😂 #MLProtestSigns flickr.com/photos/30686429@N…
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Ionel Gog retweeted
17 Jan 2016
Q: Why did the deep net cross the road?
A: We don't know. But look, it did it really well...
#deeplearning
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