Great Power, Great Responsibility: The 2018 Big Data & AI Landscape
It’s been an exciting, but complex year in the data world.
OpenAI Five
Our team of five neural networks, OpenAI Five, has started to defeat amateur human teams at Dota 2. While today we play with restrictions, we aim to beat a team of top professionals at The International in August subject only to a limited set of heroes.
Ways to think about machine learning
I don’t think, though, that we yet have a settled sense of quite what machine learning means — what it will mean for tech companies or for companies in the broader economy, how to think structurally about what new things it could enable, or what machine learning means for all the rest of us, and what important problems it might actually be able to solve.
In Army of None, a field guide to the coming world of autonomous warfare
In Army of None, Scharre argues that the challenges around just the definitions of these machines will take enormous effort to work out between nations, let alone handling their effects. It’s a sobering, thoughtful, if at times protracted look at this critical topic.
The Road to Autonomous Vehicle Adoption
Consumer adoption of AVs is the next big hurdle for those in the Automotive industry. What lessons can we learn from other emerging catagories?
Pentagon’s AI Surge On Track, Despite Google Protest
In the long term, large government contracts and cutting-edge projects will be hard for tech companies to resist.
India’s mess of complexity is just what AI needs
The country’s diversity of scripts, dialects, dress, and culture is a challenge that will make artificial intelligence more resilient.
The Future of Map-Making is Open and Powered by Sensors and AI
The tools of digital map-making today look nothing like those we had even a decade ago. Driven by a mix of grassroots energy and passion combined with innovations in technology, we have seen a rapid evolution marked by three inflection points: the dawn of consumer GPS, availability of high-resolution aerial imagery at scale, and lastly a shift to large scale AI powered map-making tools in which we find ourselves today.
Facial recognition software is not ready for use by law enforcement
Recent news of Amazon’s engagement with law enforcement to provide facial recognition surveillance (branded “Rekognition”), along with the almost unbelievable news of China’s use of the technology, means that the technology industry needs to address the darker, more offensive side of some of its more spectacular advancements.
Add Constrained Optimization To Your Toolbelt
This post is an introduction to constrained optimization aimed at data scientists and developers fluent in Python, but without any background in operations research or applied math. We’ll demonstrate how optimization modeling can be applied to real problems at Stitch Fix. At the end of this article, you should be able to start modeling your own business problems.
Travel Time Optimization With Machine Learning And Genetic Algorithm
What is the relationship between machine learning and optimization? — On the one hand, mathematical optimization is used in machine learning during model training, when we are trying to minimize the cost of errors between our model and our data points. On the other hand, what happens when machine learning is used to solve optimization problems?
A List of Chip/IP for Deep Learning (keep updating)
Machine Learning, especially Deep Learning technology is driving the evolution of artificial intelligence (AI). At the beginning, deep learning has primarily been a software play. Start from the year 2016, the need for more efficient hardware acceleration of AI/ML/DL was recognized in academia and industry. This year, we saw more and more players, including world’s top semiconductor companies as well as a number of startups, even tech giants Google, have jumped into the race. I believe that it could be very interesting to look at them together. So, I build this list of AI/ML/DL ICs and IPs on Github and keep updating. If you have any suggestion or new information, please let me know.
