New this week
nature
Steps to avoid overuse and misuse of machine learning in clinical research
nature
10 min read · Sep 13th · Machine learning algorithms are a powerful tool in healthcare, but sometimes perform no better than traditional statistical techniques. Steps should be taken to ensure that algorithms are not overused… · Shared by 42, including Eric Topol, Marcus Borba, Mahantesh Biradar, Edward Tufte
github.com
openai/whisper
github.com
Sep 21st · Contribute to openai/whisper development by creating an account on GitHub. · Shared by 74, including AGI.Eth | AIKing.Eth, Christine McLeavey, Alexander Seifert, Mario Klingemann 🇺🇦, Tyler Neylon, Vikram Dutt, Kent Bye VoicesOfVR
Massachusetts Institute of Technology (MIT)
Using machine learning to identify undiagnosable cancers
Massachusetts Institute of Technology (MIT)
4 min read · Sep 2nd · A machine learning model maps developmental pathways to tumor cells to help diagnose cancers of unknown primary. The work was led by Salil Garg and colleagues from MIT’s Koch Institute and… · Shared by 83, including R.NFT R “Ray” Wang 王瑞光 #SuiteWorld #UIPathForward, Brian Ahier, ipfconline #CES2023, Evan Kirstel the $B2B Techfluencer, John Nosta, Nicolas Babin #CES2023, Theodora (Theo) Lau - 劉䂀曼 🌻, Dr. Marcell Vollmer 🇺🇦 #StaySafe & Carpe Diem
medium.com
Machine Learning is NOT Artificial Intelligence
medium.com
6 min read · Sep 12th · When building an ML model, you may want to think about whether it’s for something specific or general. In NLP, the task may be… · Shared by 6
MIT Technology Review
DeepMind’s new chatbot uses Google searches plus humans to give better answers
MIT Technology Review
1 min read · Sep 22nd · The lab trained a chatbot to learn from human feedback and search the internet for information to support its claims. · Shared by 23, including Martin Ford, Robert Scoble
cacm.acm.org
Neurosymbolic AI
cacm.acm.org
Sep 22nd · Combining neural networks with symbolic representations might make them more versatile and dependable.
· Shared by 13, including Bob E. Hayes, Gary Marcus, Dr. Marcell Vollmer 🇺🇦 #StaySafe & Carpe Diem
Towards Data Science
Overcome the biggest obstacle in machine learning: Overfitting
Towards Data Science
~14 min read · Aug 26th · Overfitting is a concept in data science that occurs when a predictive model learns to generalize well on training data but not on unseen… · Shared by 28
VentureBeat
What is reinforcement learning? How AI trains itself
VentureBeat
7 min read · Sep 5th · Reinforcement learning is the subset of ML by which an algorithm can be programmed to respond to complex environments for optimal results. · Shared by 118, including Jim Marous 💯, Brian Ahier, Ronald van Loon @SASsoftware #ExploreSAS, Theodora (Theo) Lau - 劉䂀曼 🌻, Bob E. Hayes, Harold Sinnott #DigitalTransformation, ipfconline #CES2023, Dr. Sally Eaves #InnoTrans2022 #GTC22, AI, Nicolas Babin #CES2023, Ines Bieler
Recently popular
levelup.gitconnected.com
Top 20 Machine Learning Algorithms, Explained in Less Than 10 Seconds Each
levelup.gitconnected.com
8 min read · Aug 22nd · Simple explanations to the 20 most important machine learning algorithms, all in under 10 seconds each. · Shared by 254, including Cyril Coste #DigitalTransformation, Ines Bieler, Mario Clemente, Ronald van Loon @SASsoftware #ExploreSAS
The Atlantic
Of God and Machines
The Atlantic
10 min read · Sep 15th · The future of artificial intelligence is neither utopian nor dystopian—it’s something much more interesting. · Shared by 250, including Dr. Marigo Raftopoulos, Bob E. Hayes, Fabio Chiusi, Emily M. Bender, Iain Brown, PhD, Theodora (Theo) Lau - 劉䂀曼 🌻, hardmaru, Brian Ahier
startwords.cdh.princeton.edu
Are Large Language Models Our Limit Case?
startwords.cdh.princeton.edu
~19 min read · Sep 4th · How is it possible to go forward with large language models with the knowledge of just how biased, how incomplete, and how harmful — to both people and the planet — these models truly are? · Shared by 213, including Thomas Telandro
madebyoll.in
Game Emulation via Neural Network
madebyoll.in
~14 min read · Sep 5th · I made a playable Pokémon overworld. It looks (mostly) like a normal video game, and you can try it in your web browser here: Although this looks like a video game, I did not write any game code.This… · Shared by 147, including Matthew Turland, Matt Shaffer
fast.ai
fast.ai - From Deep Learning Foundations to Stable Diffusion
fast.ai
2 min read · Sep 16th · Practical Deep Learning for Coders part 2, 2022 · Shared by 142, including Thomas Telandro
contra.com
Rewriting tests from Cypress to Playwright using GPT3 by Gajus Kuizinas
contra.com
Sep 9th · Using OpenAI's text-davinci-002 model to rewrite tests from one framework to another. · Shared by 129, including Matthew Turland
Towards Data Science
Data demystified: Neural networks — how do they work?
Towards Data Science
~11 min read · Aug 22nd · An executive’s guide to how neural networks work, without the jargon and complicated maths. · Shared by 126, including Cyril Coste #DigitalTransformation, Jansnet
VentureBeat
What is reinforcement learning? How AI trains itself
VentureBeat
7 min read · Sep 5th · Reinforcement learning is the subset of ML by which an algorithm can be programmed to respond to complex environments for optimal results. · Shared by 118, including Jim Marous 💯, Brian Ahier, Ronald van Loon @SASsoftware #ExploreSAS, Theodora (Theo) Lau - 劉䂀曼 🌻, Bob E. Hayes, Harold Sinnott #DigitalTransformation, ipfconline #CES2023, Dr. Sally Eaves #InnoTrans2022 #GTC22, AI, Nicolas Babin #CES2023, Ines Bieler
simonwillison.net
Prompt injection attacks against GPT-3
simonwillison.net
3 min read · Sep 13th · Riley Goodside, yesterday: Exploiting GPT-3 prompts with malicious inputs that order the model to ignore its previous directions. pic.twitter.com/I0NVr9LOJq- Riley Goodside (@goodside) September 12,… · Shared by 103, including eric-meyer.css, Oliver Raduner, Joanna J Bryson, Tactical Tech
All-time favorites
machinelearnings.co
The Non-Technical Guide to Machine Learning & Artificial Intelligence
machinelearnings.co
20+ min read · From 2017 · Machine learning and artificial intelligence (ML and AI) have seized Tech mindshare in a way few topics have in recent memory. · Shared by 5239, including Gabriele, Tibor Martini 🇺🇦, Pete Skomoroch, Thomas Power, Brent Summers, Kris Fannin, Chris Messina, Sir Lord Travis Wright, Web3 Speaker, Klaus Eck, Frank Cieslik, Werner Vogels, Kenneth Kalmer, Harpreet Singh, Herbert Bay, DonDahlmann, Fabricio Teixeira, 🟣 Antonio Vieira Santos #FutureOfWork #InnoTrans2, Nils Hitze, Howard Getson, Mike Ivars
r2d3.us
A visual introduction to machine learning
r2d3.us
5 min read · From 2015 · What is machine learning? See how it works with our animated data visualization. · Shared by 2065, including Aleyda Solis 🇺🇦, Casey Smith, Kevin_Indig, Marck Vaisman, Kenneth Kalmer, Rand Fishkin, Gideonro, Daniel Boos, Chris Messina, Stowe Boyd, designshard, Mara Averick, Thomas Power, Data Science Renee, Mike Tamir, PhD, Parin Vachhani, Helen Yu, hardmaru, hakan, David Luescher
OpenAI
DALL·E 2
OpenAI
1 min read · Apr 6th · DALL·E 2 is a new AI system that can create realistic images and art from a description in natural language. · Shared by 1531, including Sam Altman, Chris Messina, Kevin Quealy, John Jantsch, Liam Bright, Semil, Marvin “Polymath but really Just Generalist” Liao, Brendan Nyhan, Balaji Srinivasan, Douglas Karr, Peter van Sabben.eth, Ross Dawson, Neuroskeptic 🇺🇦, Robert Scoble, Danielle! 🌩, David McCandless, Daniel Shiffman, Bob E. Hayes, Mark Tabladillo PhD, Ilya Sutskever
The Guardian
A robot wrote this entire article. Are you scared yet, human?
The Guardian
5 min read · From 2020 · We asked GPT-3, OpenAI’s powerful new language generator, to write an essay for us from scratch. The assignment? To convince us robots come in peace · Shared by 1022, including Mathieu von Rohr, Austin Kleon, Nige Willson, Gary Marcus, Joanna (J.F.) Penn, Michael Mina, Iain Brown, PhD, Oliver Reichenstein, Evan Kirstel the $B2B Techfluencer, Rick King, Robin Wigglesworth, Nigel Warburton 🇺🇦 #Abolishthemonarchy, Marc R Gagné MAPP 🍁, Mathew Ingram, emily bell, Taylor Lorenz, Yves Mulkers, Guy Kawasaki, Jim Marous 💯, AI
Ars Technica
How to get started with machine learning and AI
Ars Technica
8 min read · Jun 22nd · We wrap our hands around the basics of AI/ML and show you how to get a model off the ground. · Shared by 972, including Terence Mills, Amber Mac, Mark Tabladillo PhD, Iain Brown, PhD, Marcus Borba
ZDNET
AI: The pattern is not in the data, it's in the machine
ZDNET
6 min read · May 29th · No, the patterns computers create are not an inherent property of data, they are an emergent property of the structure of the program itself. · Shared by 964, including Bob E. Hayes, AI, Howard Getson, Ronald van Loon @SASsoftware #ExploreSAS, Jansnet, Nicolas Babin #CES2023, Kelly Hungerford 🌻, Ines Bieler
freeCodeCamp.org
Want to know how Deep Learning works? Here’s a quick guide for everyone.
freeCodeCamp.org
6 min read · From 2017 · Artificial Intelligence (AI) and Machine Learning (ML) are some of the hottest topics right now. · Shared by 934, including Vlad the Inhaler 😈 (AlgoCompSynth by znmeb), Ines Bieler, Katja Evertz, Nicolas Berg, Andreas Heer, DonDahlmann, Mara Averick, Klaus Eck, Javi Cantón, FANZO 🧢 #NFT365, Chris Roth, Ron McIntyre, von Moerenburgh, Dominik Grolimund, Patrick Scheuerer, Thomas Power, Helmi, Dr. Nettra Pan 🦇🔊, Herbert Bay, Massimiliano Aroffo
The New York Times
The Great A.I. Awakening
The New York Times
Summary · From 2016 · Writing for The New York Times Magazine, Gideon Lewis-Kraus’s article breaks down a complex, multilayered story of artificial intelligence into an absorbing, detailed read. The story of Google Translate involves many prestigious players, who all worked together to create an impressively improved translation tool in far less time than originally expected. This is a tale of the meeting of many minds to create a single truly powerful artificial one that will have future uses beyond translating from one language to another. · Shared by 917, including Aleyda Solis 🇺🇦, Diogo Mónica, Kenneth Kalmer, Andy Weissman, Pete Skomoroch, Gideonro, Thomas Power, #bottish, Data Science Renee, Rachel Miller | #InfluencerMarketing, Christoph Magnussen, Jane, Mathew Ingram, Call Me ❝MICKEY❞, Howard Getson, Claudia Sommer, Fabricio Teixeira, Chris Messina, Josep M. Ganyet, Stowe Boyd
HackerNoon | Learn Any Technology
Spotify’s Discover Weekly: How machine learning finds your new music
HackerNoon | Learn Any Technology
9 min read · From 2017 · The science behind personalized music recommendations · Shared by 899, including Chris Schultz ✌️, Howard Getson, Konrad Lischka, designshard, Mara Averick, elpocas, Joe Germuska, Helmi, 𝙉𝙞𝙘𝙤 𝙇𝙪𝙢𝙢𝙖, Dominik Grolimund, Danny Prol, Paulmears, Greg Meyer, David Smooke, Nando 💪🇦🇺🇦🇷, Eric L. Barnes, Michelle Ufford 🏳️🌈, Tris Hussey, FactorDaily, Thomas Power
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