There’s a good reason for the “@“ character in the middle of your email address. It separates the two parts: your user name and your web site. Someday you might see something similar on social networking sites – Mark Zuckerberg could write on Facebook and mention Jack Dorsey “hey email@example.com” and Jack could write back from Twitter “hi firstname.lastname@example.org!” — that would be the Silicon Valley equivalent of Alexander Graham Bell and Thomas Watson’s first telephone call. When small social networks like Twitter and Google Plus start to interoperate with open source networks and blogs, they could eventually form a large enough base of users to “flip the iceberg” and have more usage than the dominant, non-interoperable player: Facebook.
New York Times published an opinion article yesterday that suggests ethereum may take over bitcoin as the gold standard of cryptocurrencies. I disagree. And the proof is in the technical details.
Ethereum is a currency that’s vulnerable to hacks. Any cryptocurrency is, but with ethereum, it is more so. In fact, ethereum was hacked once in its less than three years long history. $80MM worth of ethers were stolen, and the Ethereum Foundation decided to change the source code so that the thieves would not be able to use the money. The idea was, this way, the heist would be contained. But, to some, this was no different than governments seizing individuals’ properties, hence against the decentralized spirit of blockchains. As a result, the ethereum-classic hard-fork was born.
There’s no doubt that IBM is not the sexiest company in tech right now and it’s an easy target for bullying. But anyone who has spent some time on cloud-based AI platforms will admit IBM has one of the best offerings in the market right now. IBM’s acquisitions of SoftLayer, AlchemyAPI, Cloudant put them in a strong position in terms of cloud and AI, but especially the intersection of the two.
As we grow more comfortable with social networking, we are learning to create multiple networks of friends. We can find people to follow on LinkedIn, Instagram, Twitter – there is a seemingly endless supply of new places to connect. Some of these use actual open web infrastructure to spread data and control to the edges and form a true network, while others take a hybrid approach. Micro-blogging at Mastodon is an example of a true network where friends are made between Web sites. Micro.blog and WordPress publish their feeds to the open web but require a feed reader if you want to aggregate feeds from friends on multiple networks. Slack alternatives like Matrix, Rocket Chat and Mattermost support fully private, real networks.
You may have never heard of CUDA or OpenCL, and that’s no surprise. Only a very limited number of AI, VR researchers, and programmers use them. However, the AMD graphic cards of your Mac, your XBox games, Google searches, and Facebook newsfeed rely on these technologies, and you’re inadvertently reaping the benefits.
CUDA and OpenCL are gateways to your computers’ GPU. Once used for gaming mainly, GPUs are today the main components of AI servers, VR machines and blockchain miners. With Moore’s Law’s demise, they’re increasingly replacing CPU in the ranking of importance in computer architecture.
The state-of-the-art in feed readers was frozen in place sometime around 2010, if not before. By that time most of the format wars between RSS and Atom had long since died down and were all generally supported. The only new features to be added were simple functionalities like sharing out links from readers to social services like Facebook and Twitter. For fancier readers they also added the ability to share out to services like Evernote, OneNote, Pocket, Instapaper and other social silos or silo related services.
AI is hot, and it’s real. There’s no doubt. And when it comes to openness in AI, we are lucky. Thanks to Berkeley University, Google, and Facebook, we have great libraries one can use to form convolutional neural networks that will solve the world’s biggest problems; like “hot dog or not” 😃
Joke aside, this article is intended to give you a quick introduction to the hottest convolutional neural network frameworks available. For those of you who don’t know, convolutional neural networks are brain replicas in software form, literally. They were invented by Yann LeCun at NY University -now Director of AI Research at Facebook- by examining the biological structure of cat brains and replicating them in software.