Solving visual analogy puzzles with Deep Learning

Bongard problmes are named after their inventor, Soviet computer scientist Mikhail Bongard, who was working on pattern recognition in the 1960s. He designed 100 of this puzzles, to be a good benchmark for pattern recognition abilities, and they seem to be challenging for both people and algorithms. Here is an example: Source: github

Your Data Is Crucial to a Robotic Age. Shouldn’t You Be Paid for It?

The idea has been around for a bit. Jaron Lanier, the tech philosopher and virtual-reality pioneer who now works for Microsoft Research, proposed it in his 2013 book, “Who Owns the Future?,” as a needed corrective to an online economy mostly financed by advertisers’ covert manipulation of users’ consumer choices. Source: nytimes

What’s it like to ride in a self-driving car?

I’ve spent the past few months working on a 10,000-word special report on AVs for The Economist, which was published in this week’s issue. The focus of my report is mostly on the long-term implications of AVs, based on the assumption (a reasonable one, I think) that the technology can be made to work reliably […]

Machine Learning Workflow on Diabetes Data : Part 02

In my last article of this series, we discussed about the machine learning workflow on the diabetes data set. And discussed about topics such as data exploration, data cleaning, feature engineering basics and model selection process. You can find the previous article below. Source: towardsdatascience

This Neural Net Hallucinates Sheep

If you’ve been on the internet today, you’ve probably interacted with a neural network. They’re a type of machine learning algorithm that’s used for everything from language translation to finance modeling. One of their specialties is image recognition. Several companies—including Google, Microsoft, IBM, and Facebook—have their own algorithms for labeling photos. But image recognition algorithms […]

The forgetting curve explains why humans struggle to memorize

Learning has an evolutionary purpose: Among species, individuals that adapt to their environments will succeed. That’s why your brain more easily retains important or surprising information: It takes very little effort to remember that the neighbor’s dog likes to bite. Remembering the dog’s name is harder. One ensures safety, the other is just a random […]

World War II carrier “Lady Lex” found 2 miles under sea by Allen expedition

Paul Allen, the co-founder of Microsoft, has put his money into many passion pursuits. Underwater archaeology—specifically, finding ships sunk during World War II—is one of the most prominent. Last August, Allen’s research vessel Petrel discovered the wreckage of the USS Indianapolis, the cruiser that delivered components of the two nuclear bombs dropped on Japan to close the […]

Open Avalanche Project – Using ML to Improve Avalanche Forecasting

The Goal of the Open Avalanche Project is to reduce avalanche-related deaths and impacts across the world. By using machine learning and experimentation to improve the accuracy and efficacy of avalanche forecasts, we are setting out to cover the world with the best Avalanche and Snow data possible. Source: openavalancheproject

The Building Blocks of Interpretability

In 2015, our early attempts to visualize how neural networks understand images led to psychedelic images. Soon after, we open sourced our code as DeepDream and it grew into a small art movement producing all sorts of amazing things. But we also continued the original line of research behind DeepDream, trying to address one of […]