Nov 17, 2021

6 Posts

Animated image showing different Zillow listings
Nov 17, 2021

Price Prediction Turns Perilous: How Covid Broke Zillow's Pricing Algorithm

The real-estate website Zillow bought and sold homes based on prices estimated by an algorithm — until Covid-19 confounded the model’s predictive power. Zillow, whose core business is providing real-estate information for prospective buyers, shut down its house-flipping division after...
Different types of semaphores
Nov 17, 2021

The Batch: Has AI Become Unaffordable?, Covid Confounds Price Prediction, Face Recognition Algorithms Are Not Equal, This Chatbot Knows How To Google

The physical world is full of unique details that differ from place to place, person to person, and item to item. In contrast, the world of software is built on abstractions that make for relatively uniform coding environments and user experiences.
A graph shows the cost in dollars of training large natural language processing models.
Nov 17, 2021

Who Can Afford to Train AI?: Cost of AI is Too Expensive for Many Small Companies

The cost of training top-performing machine learning models has grown beyond the reach of smaller companies.
Different types of semaphores
Nov 17, 2021

Making Software For a Heterogeneous World

The physical world is full of unique details that differ from place to place, person to person, and item to item. In contrast, the world of software is built on abstractions that make for relatively uniform coding environments and user...
Example comparing a nonaugmented model (left) to a model with internet-augmentation (right)
Nov 17, 2021

This Chatbot Does Its Research: Facebook Chatbot Uses the Internet to Inform its Answers

Chatbots often respond to human input with incorrect or nonsensical answers. Why not enable them to search for helpful information?
Face recognition system working on a person entering a building
Nov 17, 2021

Who Has the Best Face Recognition? U.S. Government Agency Ranks the Best Face Recognition Systems

Face recognition algorithms have come under scrutiny for misidentifying individuals. A U.S. government agency tested over 1,000 of them to see which are the most reliable.

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