61
Challenges you’re going to face when building a chatbot
Developing your own medical chatbot? Challenges and lessons learned from developing Symptomate.
Topics /
AI & Machine Learning
The most popular blog posts about ai & machine learning on Hacker News. 326 posts.
62
Principal Component Analysis Explained Visually (2015)
Principal component analysis (PCA) is a technique used to emphasize variation and bring out strong patterns in a dataset. It's often used to make data easy to explore and visualize.
63
Attacking machine learning with adversarial examples
Adversarial examples are inputs to machine learning models that an attacker has intentionally designed to cause the model to make a mistake; they’re like optical illusions for machines. In this post we’ll show how adversarial examples work across different mediums, and will discuss why securing systems against them…
64
Teaching Machines to Draw
Posted by David Ha, Google Brain ResidentAbstract visual communication is a key part of how people convey ideas to one another. From a young age, c...
65
66
How Adversarial Attacks Work
Emil Mikhailov is the founder of XIX.ai [http://XIX.ai] (YC W17). Roman Trusov is a researcher at XIX.ai. Recent studies by Google Brain have shown that any machine learning classifier can be tricked to give incorrect predictions, and with a little bit of skill, you can get them to give pretty much any result you…
67
68
I ask 100 information questions to four digital assistants
After seeing the poor feedback of Watson in Bridge Crew, I decided to take my four digital assistants for a spin. After 21 questions across four assistants, I learned that Alexa cannot give basic information about Amazon Prime videos, none of them can properly understand which movie you're looking f
69
70
Making Visible Watermarks More Effective
Posted by Tali Dekel and Michael Rubinstein, Research ScientistsWhether you are a photographer, a marketing manager, or a regular Internet user, ch...
71
72
Patrick Winston Explains Deep Learning
Patrick Winston is one of the greatest teachers at M.I.T., and for 27 years was Director of the Artificial Intelligence Laboratory (which later became part of CSAIL ).
73
Augmented reality with Python and OpenCV
You may (or may not) have heard of or seen the augmented reality Invizimals video game or the Topps 3D baseball cards. The main idea is to render in the screen of a tablet, PC or smartphone a 3D mo…
74
Tacotron 2: Generating Human-Like Speech from Text
Posted by Jonathan Shen and Ruoming Pang, Software Engineers, on behalf of the Google Brain and Machine Perception TeamsGenerating very natural sou...
75
How Bayesian Inference Works (2016)
Bayesian inference is a way to get sharper predictions from your data. It’s particularly useful when you don’t have as much data as you would like and want to juice every last bit of predictive strength from it.
76
Prodigy: A new tool for radically efficient machine teaching
Machine learning systems are built from both code and data. It's easy to reuse the code but hard to reuse the data, so building AI mostly means doing annotation. This is good, because the examples are how you program the behaviour – the learner itself is really just a compiler. What's not good is the current…
77
PhotoScan: Taking Glare-Free Pictures of Pictures
Posted by Ce Liu, Michael Rubinstein, Mike Krainin and Bill Freeman, Research ScientistsYesterday, we released an update to PhotoScan, an app for i...
78
AlphaGo's next move
With just three stones on the board, it was clear that this was going to be no ordinary game of Go.
79
A novel approach to neural machine translation
Visit the post for more.
80
A Zero-Math Introduction to Markov Chain Monte Carlo Methods
For many of us, Bayesian statistics is voodoo magic at best, or completely subjective nonsense at worst. Among the trademarks of the…
81
Transformer: A Novel Neural Network Architecture for Language Understanding
Posted by Jakob Uszkoreit, Software Engineer, Natural Language Understanding Neural networks, in particular recurrent neural networks (RNNs), are n...
82
Word vectors are awesome but you don’t need a neural network to find them
When I started playing with word2vec four years ago I needed (and luckily had) tons of supercomputer time. But because of advances in our understanding of w...
83
84
85
86
Learning a hierarchy
Stay up to speed on the rapid advancement of AI technology and the benefits it offers to humanity.
87
Building a Poor Man’s Deep Learning Camera in Python
Streaming a webcam to a deep learning model the hacker’s way
88
89
Open sourcing Sonnet – a new library for constructing neural networks
It’s now nearly a year since DeepMind made the decision to switch the entire research organisation to using TensorFlow (TF). It’s proven to be a good choice - many of our models learn significantly faster, and the built-in features for distributed training have hugely simplified our code. Along the way, we found that…
90
