AI Contents Archive

(1/4) Writing is often a collaborative process: We start with a draft, ask for suggestions & repeatedly make changes. Today we’re introducing PEER, a model trained to mimic this process, enabling it to incrementally write texts and to collaborate with humans in more natural ways. https://t.co/J92hIq8oRe

Interested in an AI job, but unsure what different roles entail? Informal chats with working professionals can help you narrow your job search. Read my tips on informational interviews (which are different from job interviews) in The Batch. https://t.co/nl324moHnd

Users world-wide rely on Google Meet for work and personal communication, often using #ML powered features to blur or replace their background. Today we discuss our improved video segmentation model that makes such effects sharper than ever. Read more at https://t.co/lRyEzLENj7 https://t.co/Ke9hEAJZxS

In partnership with us, @Siemens introduced the era of the #IndustrialMetaverse for customers to create physically accurate #digitaltwins with Siemens Xcelerator and @NVIDIAOmniverse. https://t.co/llezDtGzge

How to Speed up Pandas by 4x with one line of code #KDnuggets https://t.co/UXfnVqhbA3

This #Robot cleans windows for high-rise buildings and skyscrapers by @gigadgets_ #AI #ArtificialIntelligence #MI #Robotics #RPA #Automation #FutureOfWork cc: @ronald_vanloon @pbalakrishnarao @chr1sa https://t.co/tomaRWOVnD

Explore #DigitalTwins at #GTC22: https://t.co/wxMr4pW7gf

Using #KnowledgeGraphs to Understand Enterprise Information — @Mindbreeze shows how to gain insights by pulling & linking data from across the enterprise: https://t.co/Abk2p0OjmI ——— #BigData #LinkedData #Knowledgebase #GraphDB #DataScience #AI #MachineLearning #InsightsDiscovery https://t.co/Ee0vcCYNES

Machine Learning vs Artificial Intelligence: Key Differences #MachineLearning #Industry40 #Python #DataScience #BigData #NeuralNetworks #IoT #100DaysOfCode #robots #technology #ArtificialIntelligence #RPA #cloud #5G #IIoT #cybersecurity https://t.co/BhqogtoONT https://t.co/wLOyjhJctg

(2/4) PEER can write drafts, add suggestions, follow instructions, perform edits, correct itself and provide explanations for all its actions. Trained mostly on Wikipedia's edit history, PEER clearly outperforms much larger models on a collection of different editing tasks.

#AI Created 3x As Many Jobs As It Killed Last Year by @AlisonDeNisco @TechRepublic Read more: https://t.co/p751w1urfE #IoT #BigData #MachineLearning #ArtificialIntelligence #ML #MI #InternetofThings #DataScience #Analytics cc: @tamaramccleary @ianljones98 @nathealings https://t.co/8pJUWjZuqD

How can security teams manage risk if they can’t measure it? #DataSecurity #Privacy #100DaysOfCode #Cloud #Security #MachineLearning #Phishing #Ransomware #Cybersecurity #CyberAttacks #DataProtection #Malware #Hacked #Infosec https://t.co/VUclHWJbrR https://t.co/8nROx82ncc

Put your deep learning skills with R into action! @ManningBooks https://t.co/hqXMgOCKUM https://t.co/b70CEkw9su

(4/4) PEER was developed by @timo_schick, @JaneDwivedi, Zhengbao Jiang, @Fabio_Petroni, @PSH_Lewis, @gizacard, @qingfeiyou, @christofernal, @EXGRV, @riedelcastro. Read our paper here: https://t.co/PTrOeajTt8

I was today years old when I realized that df.stack() makes dataframes *taller*. I always used to be confused which one was stack and which one was unstack.