Microsoft to Open Source Its Network Replication Software
The cloud is too big to fail. And Microsoft doesn’t want to hoard the emulation technology.
The cloud is too big to fail. And Microsoft doesn’t want to hoard the emulation technology.
The cloud giant also launched a reference architecture that companies can code into their existing marketplace to recommend new content or products.
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If you enjoyed our previous episode about hyper-converged infrastructure, then you’re in for a real treat — the infamous Greg Ferro of Packet Pushers is back for a special BONUS episode of Kernel of Truth! We learned that once you get Greg and JR talking, it’s nearly impossible to get them to stop. So, we let them keep going and recorded an extra episode all about Voyager. Greg’s got questions about our open packet optical platform, and JR’s got answers. You’ll be impressed with how much awesome info and discussion they can fit into a mini episode!
Like what you’re hearing and want to talk about it with fellow Kernel of Truth fans? Good news! We’ve got a new Cumulus community forum for the podcast where you can chat with other podcast and networking aficionados. Be sure to check it out!
As always, you can tweet any questions, feedback or topics you want us to discuss at @cumulusnetworks and use the hashtag #KernelOfTruth — we want to hear from you, and give you content that you want to Continue reading
Oracle open sources protocol for machine learning models; IEEE publishes new fog computing standards; and Cohesity achieves AWS storage competency.
Hey, it's HighScalability time:
The amazing Zoomable Universe from 10^27 meters—about 93 billion light-years—down to the subatomic realm, at 10^-35 meters.
Do you like this sort of Stuff? Please lend me your support on Patreon. It would mean a great deal to me. And if you know anyone looking for a simple book that uses lots of pictures and lots of examples to explain the cloud, then please recommend my new book: Explain the Cloud Like I'm 10. They'll love you even more.
Moore’s Law is effectively boosting compute capability by a factor of ten over a five year span, as Nvidia co-founder and chief executive officer Jensen Huang reminded Wall Street this week when talking about the graphics chip maker’s second quarter of fiscal 2019 financial results. …
Nvidia’s Datacenter Growth Beats Moore’s Law Big Time was written by Timothy Prickett Morgan at .
In this sponsored Network Collective Short Take, Brandon Heller, Co-Founder and CTO of Forward Networks, joins Network Collective to talk about how network verification and modeling are empowering network operators to increase efficiency, reduce mistakes, and shorten the mean-time-to-resolution when troubleshooting network issues.
Forward Networks does this through a complete and accurate mathematical model of the way your network operates, allowing you to quickly assess traffic flows and operational issues in your network without needing to query multiple devices manually.
Having an accurate model of your network also empowers you to validate changes before ever touching your production environment, giving you confidence that the change you are implementing will achieve the desired outcome.
For more technical details, short demo videos, and a chance to try Forward on your network to gain greater insight, head on over to http://forwardnetworks.com/collective.
The post [Sponsored] Short Take – Forward Networks appeared first on Network Collective.
On February 16th this year, MediaNet Works and the Internet Society Kenya Chapter launched “Safe Online, Safe On Land” a 12-month project that seeks to promote safe Internet usage and practices among children in Kenya. With funding from the Internet Society’s Beyond the Net Grants Program the project anticipates to reach 700 children, targeting Koinonia Community, four children’s homes, one secondary school, and three other schools in Ngong, Kajiado County.
In addition, 12 teachers, 15 child protection and social workers, 10 journalists from both the community and mainstream media, including the Bloggers Association of Kenya (BAKE), will benefit from this project.
Justification of the Project
The launch of this project coincided with media coverage of Internet and social media safety issues in the country. Cases of online child abuse and human trafficking have recently featured in local media. Consequently, the National Assembly on 26 April, 2018, passed the Computer Misuse and Cybercrimes Bill which is set to be presented to the president for assent. The Bill’s offenses relevant to this project include publication of fake news, pornography, cyberterrorism, cybersquatting, and child pornography.
To set the ball rolling consultative meetings between representatives of MediaNet Works and Koinonia Community were held Continue reading
You should definitely watch this amazing video from Ben Sigelman of LightStep that was recorded at Cloud Field Day 4. The good stuff comes right up front.
In less than five minutes, he takes apart crazy notions that we have in the world today. I like the observation that you can’t build a system more than three or four orders of magnitude. Yes, you really shouldn’t be using Hadoop for simple things. And Machine Learning is not a magic wand that fixes every problem.
However, my favorite thing was the quick mention of how emulating Google for the sake of using their tools for every solution is folly. Ben should know, because he is an ex-Googler. I think I can sum up this entire discussion in less than a minute of his talk here:
Google’s solutions were built for scale that basically doesn’t exist outside of a maybe a handful of companies with a trillion dollar valuation. It’s foolish to assume that their solutions are better. They’re just more scalable. But they are actually very feature-poor. There’s a tradeoff there. We should not be imitating what Google did without thinking about why they did it. Sometimes the “whys” will apply Continue reading
Five years ago, Hewlett Packard Enterprise let loose the Peregrine supercomputer at the National Renewable Energy Laboratory, a marriage of performance and power efficiency that is based on HPE’s dense Apollo 8000 system and includes warm liquid cooling. …
NREL Set to Soar Higher With Eagle Supercomputer was written by Jeffrey Burt at .
Newisys has been on the NVM-Express for several years, putting the high-profile interface in a growing number of server and storage platforms, including servers with NVM-Express directly attacked to the CPU, a system running NVM-Express over Fabrics (NVMe-oF) and a storage expansion flash array (JBOF, or Just a Bunch of Flash). …
Negotiating The NVM-Express Land Rush was written by Jeffrey Burt at .
Companies are always concerned about cloud security, but may overlook other factors in cloud adoption, such as the impact on performance.
Welcome to Technology Short Take 103, where I’m back yet again with a collection of links and articles from around the World Wide Web (Ha! Bet you haven’t seen that term used in a while!) on various technology areas. Here’s hoping I’ve managed to include something useful to you!
Nothing this time around, sorry!
Fairness without demographics in repeated loss minimization Hashimoto et al., ICML’18
When we train machine learning models and optimise for average loss it is possible to obtain systems with very high overall accuracy, but which perform poorly on under-represented subsets of the input space. For example, a speech recognition system that performs poorly with minority accents.
We refer to this phenomenon of high overall accuracy but low minority accuracy as a representation disparity… This representation disparity forms our definition of unfairness, and has been observed in face recognition, language identification, dependency parsing, part-of-speech tagging, academic recommender systems, and automatic video captioning.
For systems that are continually trained and evolved based on data collected from their users, the poor performance for a minority group can set in place a vicious cycle in which members of such a group use the system less (because it doesn’t work as well for them), causing them to provide less data and hence to be further under-represented in the training set…
… this problem of disparity amplification is a possibility in any machine learning system that is retrained on user data.
An interesting twist in the problem is that the authors assume neither the Continue reading