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Artificial Intelligence

Top news of the week: 16.11.2022.

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@xamat shared
On Nov 12, 2022
RT @GoogleAI: As language models increase in scale they sometimes exhibit various useful emergent capabilities. In today’s post, we explore this phenomenon to better understand its dependence on model properties and its potential impact in applications. Read more at https://t.co/QuwRpWWWmM https://t.co/yWNm2xx4ya
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Characterizing Emergent Phenomena in Large Language Models

Characterizing Emergent Phenomena in Large Language Models

For example, the GPT-3 paper showed that the ability of language models to perform multi-digit addition has a flat scaling curve (approximately random performance) for models from …

@peteskomoroch shared
On Nov 10, 2022
RT @petewarden: Genuinely sad to see layoffs in Meta's amazing ML framework teams: https://t.co/d4M0w8wsyp https://t.co/3NOFrub3rj There was always a lot of internet noise about PyTorch/TF beefs, but I've been a longtime fan, and think the world is a better place with multiple library choices.
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Meta layoffs hit an entire ML research team focused on infrastructure

Meta layoffs hit an entire ML research team focused on infrastructure

After today's Meta layoffs, a researcher said entire team focused on applying ML across the infrastructure stack was cut.

@kastnerkyle shared
On Nov 15, 2022
RT @johnrobinsn: DiffEdit - Semantic Image Editing with Stable Diffusion https://t.co/XAc51yYt0e My Impl of the Paper. https://t.co/e20jNj4cbA Special thanks to @jeremyphoward and all his great tips and techniques for understanding academic papers covered in his latest @fastdotai course. https://t.co/aYBgEYChVb
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DiffEdit - Semantic Image Editing with Stable Diffusion

DiffEdit - Semantic Image Editing with Stable Diffusion

My Implementation of the DiffEdit Paper

@peteskomoroch shared
On Nov 11, 2022
RT @xamat: From now on I will be spending much more time on LinkedIn, and at LinkedIn. Very excited about my next play! https://t.co/LOgKamkDig
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I am [in]!

I am [in]!

I am very happy to announce that I have recently joined LinkedIn as their VP of AI Product Strategy. I will be reporting directly to Ya Xu, Head of Data and AI, and indirectly to Tomer ...

@weballergy shared
On Nov 12, 2022
RT @GoogleAI: While most #ML models are trained by collecting data on a central server, federated learning makes it possible to train models without any user's raw data leaving their device. Check out the latest AI Explorable on how federated learning protects privacy→ https://t.co/5hDzyWomiO https://t.co/xwd4xrn4Wi
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How Federated Learning Protects Privacy

How Federated Learning Protects Privacy

Most machine learning models are trained by collecting vast amounts of data on a central server. Federated learning makes it possible to train models without any user's raw data leaving ...

@stanfordnlp shared
On Nov 9, 2022
RT @C3DTI: 📣 Remember to register for tomorrow's #DigitalTransformation colloquium with @Google Brain Research Scientist Nicholas Carlini. Join us for this free talk on "Underspecified Foundation Models Considered Harmful." Details and registration here: https://t.co/9w5MhxBl6u https://t.co/fUUFraJiy1
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Fall 2022 Series

Fall 2022 Series

November 17, 2022, 1 pm PT/3 pm CT Tackling Computational and Data Heterogeneity in Federated Learning Gauri Joshi, Associate Professor of Electrical and Computer Engineering, …

@jeremyphoward shared
On Nov 12, 2022
RT @Angelina_Magr: Is decoupling engineering from data science the ultimate "solution" to MLOps? I went to @HamelHusain and Shreya's deep dive session about "Operationalizing machine learning". Share some thoughts here. https://t.co/5fQR6POOdd
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Operationalizing Machine Learning - Decoupling Engineering from AI

Operationalizing Machine Learning - Decoupling Engineering from AI

Previously I wrote about how today's data science tooling has changed. I recently reviewed several vendor tools all claiming to enable "faster iteration and deployment" for data science ...

@mxlearn shared
On Nov 14, 2022
[N] Awesome AI papers reviewed on Computer Vision News of November 2022 https://t.co/daxpO4sNTG
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[N] Awesome AI papers reviewed on Computer Vision News of November 2022

[N] Awesome AI papers reviewed on Computer Vision News of November 2022

7 votes and 0 comments so far on Reddit

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