ML   46547

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Gyana
Location-based insights for physical businesses and real assets
location  ai  data  ml  UK 
3 hours ago by shalmaneser
Neural networks as Ordinary Differential Equations
Recently I found a paper being presented at NeurIPS this year, entitled Neural Ordinary Differential Equations, written by Ricky Chen, Yulia Rubanova, Jesse Bettencourt, and David Duvenaud from the University of Toronto. The core idea is that certain types of neural networks are analogous to a discretized differential equation, so maybe using off-the-shelf differential equation solvers will help get better results. This led me down a bit of a rabbit hole of papers that I found very i...
neural-network  differential-equations  ml  ai 
12 hours ago by clehene
Applied machine learning at Facebook: a datacenter infrastructure perspective
Lots of cool details into how they've productized and scaled up their prod ML infrastructure.
As we looked at last month with Continuum, the latency of incorporating the latest data into the models is also really important. There’s a nice section of this paper where the authors study the impact of losing the ability to train models for a period of time and have to serve requests from stale models. The Community Integrity team for example rely on frequently trained models to keep up with the ever changing ways adversaries try to bypass Facebook’s protections and show objectionable content to users. Here training iterations take on the order of days. Even more dependent on the incorporation of recent data into models is the news feed ranking. “Stale News Feed models have a measurable impact on quality.” And if we look at the very core of the business, the Ads Ranking models, “we learned that the impact of leveraging a stale ML model is measured in hours. In other words, using a one-day-old model is measurably worse than using a one-hour old model.” One of the conclusions in this section of the paper is that disaster recovery / high availability for training workloads is key importance.
machine-learning  facebook  ml  training  ops  models  infrastructure  prod  production 
19 hours ago by jm
Home - MetaMetrics Inc.
Bringing meaning to measurement by matching students to resources using a scientific, universal scale.
education  software  ml  USA 
yesterday by shalmaneser
A new general computation model for Dune
Dune is fast. However, if you try to use Dune to develop in a big workspace such as the OCaml platform repository, you will notice...
ml  ocaml  build 
yesterday by vipom
2018 in Review: 10 AI Failures – SyncedReview – Medium
Google Photo confuses skier and mountain
Google Photos includes a relatively unknown AI feature that can automatically detect images with the same backgrounds/scenes and offer to merge them into a single panoramic picture. In January Reddit User “MalletsDarker” posted three photos taken at a ski resort: two were landscapes, the other shot of his friend. When Google Photos merged the three a weird thing happened, as his friend’s head was rendered as a peak-like giant peering out from the forest.
ai  ml 
yesterday by libbymiller

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