Alex Ingerman

I see the eigenvalue in thine eye.
I hear the tender tensor in thy sigh.

[Alex Ingerman @alex_ingerman]

@IasonGabriel @Arianna_Manzini Blog post tl;dr: https://t.co/pqLsGM8EQ2

[Alex Ingerman @alex_ingerman]

New paper our! It was an absolute pleasure working with a ton of talented people across Google Research, DeepMind and multiple universities - to deeply explore what it will mean to have intelligent AI assistants present and integrated in our digital lives.

[Iason Gabriel @IasonGabriel]

1. What are the ethical and societal implications of advanced AI assistants? What might change in a world with more agentic AI?

Our new paper explores these questions:
https://t.co/Z0jlSMBLxq

It’s the result of a one year research collaboration involving 50+ researchers… a🧵

[Alex Ingerman @alex_ingerman]

I also want to say that of all the mega-papers I've worked on, this one is by far the most readable: skimmable from the top, and well-organized for deep-dives. Kudos to the primary authors/editors @IasonGabriel, @Arianna_Manzini, Geoff Keeling!

[Jeff Dean @JeffDean]

Some really great visualizations and demonstrations by @adamrpearce and @nicki_mitch around the key ideas behind Federated Learning, and how it enables learning communally-useful ML models without ever bringing all the raw data together.

[Alex Ingerman @alex_ingerman]

Just dropped: an interactive federated learning+privacy explorable from @GoogleAI PAIR! Don't miss the in-browser simulation of FL and differential privacy being used to protect outlier data points - try the different parameters to get an intuition for privacy/utility trade-offs.

[Adam Pearce @adamrpearce]

Most machine learning models are trained by collecting vast amounts of data on a central server. @nicki_mitch and I looked at how federated learning makes it possible to train models without any user's raw data leaving their device.

https://t.co/qRHqbJ2VNL

[Alex Ingerman @alex_ingerman]

@hibatallahkab @GoogleColab There are lots of example Colab notebooks for TensorFlow Federated, on the TFF site! https://t.co/pdNseYCvUe

[Alex Ingerman @alex_ingerman]

@hibatallahkab HI Hibatallah - I recommend looking at "Advances and open problems in FL" (https://t.co/ux5K9INyt1) for a wide-lens overview, and "A field guide to federated optiomization" (https://t.co/EIuepNXLg8) for practical methods/algorithms overview!

[Google AI @GoogleAI]

Introducing a proof-of-concept production deployment of a next-word-prediction model for Spanish-language #Gboard users that was trained using #FederatedLearning while providing a rigorous #DifferentialPrivacy guarantee. Learn how it was done ↓ https://t.co/HuvpdlGd90

[Melanie Mitchell @MelMitchell1]

"How Close Are We to AI?"

@blaiseaguera & I will discuss/debate this question, especially w/respect to "understanding" in neural network language models.

Town Hall Seattle March 4, 2022, 7:30pm PST.

In person in Seattle or watch livestream.

https://t.co/yY1wenaDtk

[Massimo @Rainmaker1973]

Wild mammal biomass has declined by 85% since the rise of humans. Today, humans represent aproximately 34% of global mammal biomass, while 62% is humans' livestock and pets. Wild mammals are just 4% [read more: https://t.co/IovXG4ZO24]

[Google AI @GoogleAI]

Introducing Federated Reconstruction, an approach that enables scalable partially local #FederatedLearning and thus avoids revealing privacy-sensitive data. Read all about our approach, including how it was successfully deployed to Gboard ↓ https://t.co/dSXrMvgEir

[Brian Wells @bwells80]

#RT @ctisus: RT @whitneyfishman: Yes ⁦@ctisus⁩ !!! EDRN's Pancreatic Cancer Detection Group Teams With Rhino Health to Leverage Federated Learning and Accelerate Medical Research https://t.co/Y2nV6FtWaa

[Google AI @GoogleAI]

Today we describe how we improved the performance of Smart Text Selection on #Android by using #FederatedLearning to train the model on more realistic data while preserving user privacy. Learn all about it below: https://t.co/DuNeouoNgj

[ACM Queue @ACMQueue]

Federated Learning and Privacy
Building privacy-preserving systems for machine learning and data science on decentralized data

Intro to federated learning and analytics, minimizing privacy risks to individuals and data custodians
https://t.co/wSt4sGBE4Z
@kbonawitz @KairouzPeter

[Peter Kairouz @KairouzPeter]

Do you want to master Federated Learning and Analytics, Personalization, Differential Privacy, and @TensorFlow Federated? We are hosting a one-of-a-kind @GoogleAI workshop on Nov 10 with thrilling talks and discussions. Register now to reserve a spot! https://t.co/OY6JSWA3Ks

[Gianclaudio Malgieri @JcMalgieri]

So excited for our second #TechTalk at @privacyhub_bru!
We are honoured to host an interdisciplinary panel w/ #YoninaEldar @WeizmannScience, @fborgesius, @alex_ingerman, Ludmila Georgieva. What's in the (sand)box? #FederatedLearning!
13Apr 5PM
Register at https://t.co/BzrvnViQiy

[Google AI @GoogleAI]

Interested in learning more about an open-source framework for ML and computations on decentralized data? Join researcher @KairouzPeter on July 31st for the Federated Learning Workshop using @TensorFlow Federated, on @YouTube Live. You can register now at https://t.co/0jfawIGUXa

[Peter Kairouz @KairouzPeter]

Exciting news!! Due to high interest in the workshop, we decided to transition our @GoogleAI Federated Learning and @TensorFlow Federated Workshop to take place on @YouTube Live and reopened registration. Please register if you are interested in attending.

[Peter Kairouz @KairouzPeter]

Do you want to master Federated Learning and @TensorFlow Federated (TFF)? We are hosting a one-of-a-kind @GoogleAI Workshop on Federated Learning using TFF. Register for free now! Spots are limited.

@JeffDean @blaiseaguera @Google @TensorFlo @PyTorch

https://t.co/I5UrjUjcFs