This month we have gathered tweets about some interesting talks, reads, and tutorials relating to AI.
As artificial intelligence becomes integrated into daily life, #AI literacy becomes vital. In this @TEDTalks, PhD student and science communicator, @JordanBHarrod, explains how a basic understanding of AI has become a necessary part of everyday life. https://t.co/zXFI8M7h3U
— AI4ALL (@ai4allorg) May 19, 2020
JAMA Fishbein Fellow, @angeldesaimd, speaks with scientist and entrepreneur Gary Marcus, PhD, about the potential of artificial intelligence in health care and the current #coronavirus #pandemic https://t.co/01GyRbrrOY
— JAMA (@JAMA_current) June 4, 2020
“We need to measure the well-being impact of COVID-19, and we need to think about scalable mental health care. Now is the time to mobilize resources to make that happen.” – @JEichstaedt https://t.co/0k00ducfEH
— Stanford HAI (@StanfordHAI) April 11, 2020
#AI tools can help us write emails and texts, and maybe soon our cover letters and resumes. But these tools could also build in bias. @jeffhancock explains how. https://t.co/LObYw1NOcX
— Stanford HAI (@StanfordHAI) May 13, 2020
Have you heard the word "attention" thrown around in both neuroscience & machine learning? Have you wondered if/how its different uses relate to each other? My new review aims to summarize how this giant topic is studied & modeled across different domains! https://t.co/240M0KKDXq pic.twitter.com/OZDDght9cN
— Grace Lindsay (@neurograce) April 16, 2020
New #TFHub tutorials page!
Explore the object detection, text classification, and image generation tutorials runnable with @GoogleColab
Check it out → https://t.co/0JjYk5rPi4
— TensorFlow (@TensorFlow) May 29, 2020
From teaching AI to AI that teaches, Microsoft researcher Sid Sen is interested in a plethora of ways that we can build innovative and trustworthy AI. Hear how he’s working on HAIbrid algorithms that aim to balance human & AI solutions on the #MSRPodcast: https://t.co/f9urv1CWxk
— Microsoft Research (@MSFTResearch) May 28, 2020
The two most common AI career transitions that I've seen in the past four years:
1. Software Engineer -> Software Engineer-ML -> Machine Learning Engineer
2. Business Analyst -> Data Analyst -> Data ScientistHave you seen other successful career transitions? pic.twitter.com/k9MC39O82r
— Kian Katanforoosh (@kiankatan) May 21, 2020
Today we’re introducing federated analytics, the practice of applying data science methods to the analysis of data stored on devices, while maintaining user privacy and security. Learn more about this approach below: https://t.co/XAwPLfzfY6
— Google AI (@GoogleAI) May 27, 2020
*UPDATE* Super Duper NLP Repo
Added 41 new notebooks bringing us to 181 total!
Several interesting topics from infromation retrieval to knowledge graphs included in this update. Enjoy.#NLProc #AI #ArtificialIntelligence #MachineLearninghttps://t.co/lF6FkYyKXj— ̷̨̨̛̛̲͎̣̞̘͈̯͚͂̈́̂̄̽̎́̽̔͑̄̏̽̏͒̾́̅̐̈́̾̎̆͆̽́͌̽̀̚̕̚̕͠͝͝ (@Quantum_Stat) June 3, 2020