Roundup Of Machine Learning Forecasts And Market Estimates, 2018
AI: the Ziggy Stardust Syndrome
In his Wall Street Journal column this weekend, Nobel laureate Frank Wilczek offers a fascinating theory as to why we haven’t been able to find signs of intelligent life elsewhere in the universe. Maybe, he suggests, intelligent beings are fated to shrink as their intelligence expands. Once the singularity happens, AI implodes into invisibility.
The GANfather: The man who’s given machines the gift of imagination
By pitting neural networks against one another, Ian Goodfellow has created a powerful AI tool. Now he, and the rest of us, must face the consequences.
VISUALIZING DEEP LEARNING MODELS AT FACEBOOK
This post summarizes the latest joint research between researchers at Georgia Tech and Facebook on using visualization to make sense of deep learning models, published at IEEE VIS’17, a top visualization conference.
Preparing for Malicious Uses of AI
We’ve co-authored a paper that forecasts how malicious actors could misuse AI technology, and potential ways we can prevent and mitigate these threats. This paper is the outcome of almost a year of sustained work with our colleagues at the Future of Humanity Institute, the Centre for the Study of Existential Risk, the Center for a New American Security, the Electronic Frontier Foundation, and others.
Here are some of the ways experts think AI might screw with us in the next five years
What about the people who actively want to use AI for immoral, criminal, or malicious purposes? Aren’t they more likely to cause trouble — and sooner? The answer is yes, according to more than two dozen experts from institutes including the Future of Humanity Institute, the Centre for the Study of Existential Risk, and the Elon Musk-backed non-profit OpenAI. Very much yes.
The Battle for Best Semi-Autonomous System: Tesla Autopilot Vs. GM SuperCruise, Head-to-Head
Being the best isn’t just about technological prowess, it’s about how well the designers understand human driving — and human nature.
‘Memtransistor’ Forms Foundational Circuit Element to Neuromorphic Computing
Combining characteristics of a memristor with a transistor mimics the multiple synapses of neurons
Deep learning for biology
A popular artificial-intelligence method provides a powerful tool for surveying and classifying biological data. But for the uninitiated, the technology poses significant difficulties.
Why even a moth’s brain is smarter than an AI
A neural network that simulates the way moths recognize odors also shows how they learn so much faster than machines.
Deep Learning, Structure and Innate Priors
A Discussion between Yann LeCun and Christopher ManningHow Search Engines Use Machine Learning: 9 Things We Know for Sure
Search engines like to always experiment with how they can use this evolving technology, but here are nine ways we know that they are currently using machine learning and how it relates to SEO or digital marketing.
Berkeley Lab ‘Minimalist Machine Learning’ Algorithms Analyze Images From Very Little Data
CAMERA researchers develop highly efficient convolution neural networks tailored for analyzing experimental scientific images from limited training data
A List of Chip/IP for Deep Learning (keep updating)
Latest Updates：
- Add Qualcomm AI Engine.
- Add Benchmarking Google’s new TPUv2.
- Add Google announced the open beta of its TPU2.
- Add Arm Machine Learning Processor.
- Add Amazon’s custom AI chip for future Echo devices.
