Neural networks use immense datasets to train against. While these are very sophisticated, they also prove to be brittle against outliers. A recent piece by researcher Janelle Shane shows just how problematic the presence (or lack thereof) of humble sheep can prove.
It’s become common now for IT companies to list deep learning algorithms as a major platform feature, from analytics to automation. But home does deep learning compare to actual human intelligence? Ray Lucchesi looked at some of its issues in the context of the MIT Intelligence Quest.
Ray Lucchesi highlighted some exciting new research in a recent blog post: sub-nanometer, atomic layer memristors! ?
When creating the On-Premise IT Roundtable podcast, we had a lot of inspiration. Here are some of our favorite IT podcasts that keep motivating us to make our own content even better!
Tom Hollingsworth and Rich Stroffolino discuss the IT news of the week. This week they discuss Microsoft’s Q#, Broadcom’s impact on 5G rollout, Samsung investing in DRAM fabs, and AWS partnering to reengage the Chinese cloud market.
In this iteration of Gestalt Cloud News:
– The Gestalt IT Rundown discusses AWS re:Invent announcements
– Chris Evans discusses the potential death of the private cloud
– We interview Eyvonne Sharp for our IT Origins series
Blockchain is about verification. Ray Lucchesi recently shared how the IXO Foundation is applying the technology to the UN’s Global Goals for Sustainable Development.
Ray Lucchesi considers the implications of Mesosphere now supporting Kubernetes. He also points out why Mesosphere’s own Marathon orchestrator will probably stay relevant in the enterprise for the foreseeable future.
In this iteration of Gestalt Server News:
– A look at AMD and Intel’s surprisingly competitive server platforms
– HyperGrid’s on-demand on-site solution
– How VMs are still more portable than Docker containers
Checkers is the game I played to kill time waiting for tables at restaurants. But solving checkers turns out to be a fascinating exercise. Recently, Alphabet’s AlphaGo team has made a lot of headlines with their neural network-based ability to beat human Go masters. But Ray Lucchesi looks back at earlier days trying to solve checkers with much more limited hardware and fundamentally different approaches.