| 1 |
A new old kind of R&D lab |
| 2 |
Can LLMs learn from a single example? |
| 3 |
AI and Power: The Ethical Challenges of Automation, Centralization, and Scale |
| 4 |
AI Safety and the Age of Dislightenment |
| 5 |
Is Avoiding Extinction from AI Really an Urgent Priority? |
| 6 |
Mojo may be the biggest programming language advance in decades |
| 7 |
From Deep Learning Foundations to Stable Diffusion |
| 8 |
GPT 4 and the Uncharted Territories of Language |
| 9 |
I was an AI researcher. Now, I am an immunology student. |
| 10 |
1st Two Lessons of From Deep Learning Foundations to Stable Diffusion |
| 11 |
Deep Learning Foundations Signup, Open Source Scholarships, & More |
| 12 |
My family’s unlikely homeschooling journey |
| 13 |
The Jupyter+git problem is now solved |
| 14 |
nbdev+Quarto: A new secret weapon for productivity |
| 15 |
Practical Deep Learning for Coders 2022 |
| 16 |
Masks for COVID: Updating the evidence |
| 17 |
Qualitative humanities research is crucial to AI |
| 18 |
AI Harms are Societal, Not Just Individual |
| 19 |
There’s no such thing as not a math person |
| 20 |
7 Great Lightning Talks Related to Data Science Ethics |
| 21 |
Doing Data Science for Social Good, Responsibly |
| 22 |
Avoiding Data Disasters |
| 23 |
SARS-CoV-2 Spike Protein Impairment of Endothelial Function Does Not Impact Vaccine Safety |
| 24 |
Statistical problems found when studying Long Covid in kids |
| 25 |
Medicine is Political |
| 26 |
Inaccuracies, irresponsible coverage, and conflicts of interest in The New Yorker |
| 27 |
Australia can, and must, get R under 1.0 |
| 28 |
11 Short Videos About AI Ethics |
| 29 |
Getting Specific about AI Risks (an AI Taxonomy) |
| 30 |
fastai A Layered API for Deep Learning |
| 31 |
fastdownload: the magic behind one of the famous 4 lines of code |
| 32 |
Is GitHub Copilot a blessing, or a curse? |
| 33 |
fastchan, a new conda mini-distribution |
| 34 |
20 Years of Tech Startup Experiences in One Hour |
| 35 |
I violated a code of conduct |
| 36 |
Avoiding the smoke - how to breath clean air |
| 37 |
fast.ai releases new deep learning course, four libraries, and 600-page book |
| 38 |
Forward from the ‘Deep Learning for Coders’ Book |
| 39 |
Applied Data Ethics, a new free course, is essential for all working in tech |
| 40 |
Essential Work-From-Home Advice: Cheap and Easy Ergonomic Setups |
| 41 |
Cloth masks can protect the wearer |
| 42 |
Particle sizes for mask filtration |
| 43 |
Introducing the first cohort of USF CADE Data Ethics Research Fellows |
| 44 |
Masks - FAQ for Skeptics |
| 45 |
Masks for all? The science says yes. |
| 46 |
6 Important Videos about Tech, Ethics, Policy, and Government |
| 47 |
Saving The Mask |
| 48 |
Covid-19, your community, and you - a data science perspective |
| 49 |
Disinformation: what it is, why it’s pervasive, and proposed regulations |
| 50 |
Tech Ethics Crisis: The Big Picture, and How We Got Here |
| 51 |
4 Principles for Responsible Government Use of Technology |
| 52 |
Blogging with Jupyter Notebooks |
| 53 |
Your own blog with GitHub Pages and fast_template (4 part tutorial) |
| 54 |
Blogging with screenshots |
| 55 |
Syncing your blog with your PC, and using your word processor |
| 56 |
Your own hosted blog, the easy, free, open way (even if you’re not a computer expert) |
| 57 |
Self-supervised learning and computer vision |
| 58 |
Data project checklist |
| 59 |
nbdev: use Jupyter Notebooks for everything |
| 60 |
Concerned about the impacts of data misuse? Ways to get involved with the USF Center for Applied Data Ethics |
| 61 |
The problem with metrics is a big problem for AI |
| 62 |
8 Things You Need to Know about Surveillance |
| 63 |
Make Delegation Work in Python |
| 64 |
USF Launches New Center of Applied Data Ethics |
| 65 |
new fast.ai course: A Code-First Introduction to Natural Language Processing |
| 66 |
Deep Learning from the Foundations |
| 67 |
A LaTeX add-in for PowerPoint - my father’s day project |
| 68 |
Was this Google Executive deeply misinformed or lying in the New York Times? |
| 69 |
Advice for Better Blog Posts |
| 70 |
Decrappification, DeOldification, and Super Resolution |
| 71 |
16 Things You Can Do to Make Tech More Ethical, part 3 |
| 72 |
16 Things You Can Do to Make Tech More Ethical, part 2 |
| 73 |
16 Things You Can Do to Make Tech More Ethical, part 1 |
| 74 |
fast.ai Embracing Swift for Deep Learning |
| 75 |
A Conversation about Tech Ethics with the New York Times Chief Data Scientist |
| 76 |
Dairy farming, solar panels, and diagnosing Parkinson’s disease: what can you do with deep learning? |
| 77 |
fastec2: AWS computer management for regular folks |
| 78 |
Some thoughts on zero-day threats in AI, and OpenAI’s GPT-2 |
| 79 |
fastec2 script: Running and monitoring long-running tasks |
| 80 |
Five Things That Scare Me About AI |
| 81 |
fast.ai Diversity Fellows and Sponsors Wanted |
| 82 |
Practical Deep Learning for Coders 2019 |
| 83 |
C++11, random distributions, and Swift |
| 84 |
High Performance Numeric Programming with Swift: Explorations and Reflections |
| 85 |
One year of deep learning |
| 86 |
The new fast.ai research datasets collection, on AWS Open Data |
| 87 |
fastai v1 for PyTorch: Fast and accurate neural nets using modern best practices |
| 88 |
Introduction to Machine Learning for Coders: Launch |
| 89 |
AI Ethics Resources |
| 90 |
What You Need to Know Before Considering a PhD |
| 91 |
Practical Deep Learning for Coders, part-time Diversity Fellowships, Fall 2018 |
| 92 |
Now anyone can train Imagenet in 18 minutes |
| 93 |
What HBR Gets Wrong About Algorithms and Bias |
| 94 |
Google’s AutoML: Cutting Through the Hype |
| 95 |
An Opinionated Introduction to AutoML and Neural Architecture Search |
| 96 |
What do machine learning practitioners actually do? |
| 97 |
AdamW and Super-convergence is now the fastest way to train neural nets |
| 98 |
Launching Cutting Edge Deep Learning for Coders: 2018 edition |
| 99 |
Training Imagenet in 3 hours for USD 25; and CIFAR10 for USD 0.26 |
| 100 |
An Introduction to Deep Learning for Tabular Data |
| 101 |
What you need to know about Facebook and Ethics |
| 102 |
A Discussion about Accessibility in AI at Stanford |
| 103 |
Adding Data Science to your College Curriculum |
| 104 |
Practical Deep Learning for Coders 2018 |
| 105 |
International Fellowship applications for Part 2 now open |
| 106 |
New Opportunities For New Deep Learning Practitioners |
| 107 |
Five Trends to Avoid When Founding a Startup |
| 108 |
Deep Learning Diversity Fellowship Applications Now Open |
| 109 |
Making Peace with Personal Branding |
| 110 |
What you need to do deep learning |
| 111 |
How (and why) to create a good validation set |
| 112 |
When Data Science Destabilizes Democracy and Facilitates Genocide |
| 113 |
Credible sources of accurate information about AI |
| 114 |
Can Neural Nets Detect Sexual Orientation? A Data Scientist’s Perspective |
| 115 |
Introducing Pytorch for fast.ai |
| 116 |
International Fellowship applications for Part 1 now open |
| 117 |
Notes on state of the art techniques for language modeling |
| 118 |
Advice to Medical Experts Interested in AI |
| 119 |
Sponsor a Deep Learning Diversity Scholarship |
| 120 |
Diversity Crisis in AI, 2017 edition |
| 121 |
Announcing fast.ai diversity scholarships |
| 122 |
Cutting Edge Deep Learning for Coders: Launching Deep Learning Part 2 |
| 123 |
Thoughts on OpenAI, reinforcement learning, and killer robots |
| 124 |
New fast.ai course: Computational Linear Algebra |
| 125 |
How to Encourage Your Child’s Interest in Science and Tech |
| 126 |
Alternatives to a Degree to Prove Yourself in Deep Learning |
| 127 |
To become a data scientist, focus on coding |
| 128 |
Machine learning hasn’t been commoditized yet, but that doesn’t mean you need a PhD |
| 129 |
How to change careers and become a data scientist - one quant’s experience |
| 130 |
Deep Learning: Not Just for Silicon Valley |
| 131 |
Deep Learning For Coders - Full notes and transcripts now available |
| 132 |
Diversity and International Fellowships for Deep Learning Part 2 |
| 133 |
Practical Deep Learning Part 2 - Integrating Recent Advances and Classic Machine Learning |
| 134 |
Big deep learning news: Google Tensorflow chooses Keras |
| 135 |
Where is AI/ML actually adding value at your company? |
| 136 |
The Deep Learning MOOC is now available! |
| 137 |
(Update - problem resolved!) Azure and AWS’s ‘GPU general availability’ lies |
| 138 |
So you are interested in deep learning |
| 139 |
How should you structure your Data Science and Engineering teams? |
| 140 |
It used to be called big data and now it’s called deep learning |
| 141 |
Additional Diversity Fellowship, New International Fellowships, and Deadline Extended to 10/17 |
| 142 |
New Electricity |
| 143 |
The Diversity Crisis in AI, and fast.ai Diversity Fellowship |
| 144 |
What We Will Cover in the First Deep Learning Certificate |
| 145 |
Providing a Good Education in Deep Learning |
| 146 |
A unique path to deep learning expertise |
| 147 |
The First Certificate in Deep Learning |
| 148 |
Launching fast.ai |
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