R. Danes

R. Danes is a senior writer for theCUBE, SiliconANGLE Media’s mobile livestreaming studio, who is based on the East Coast. Her fondness for old media and longform journalism converges with an interest in new media and digital content trends. Exploring digital disruption in the realm of publications, articles and writing led her to writing articles about digital disruption everywhere. Find R. Danes on Twitter @DanesRd. Got a news tip? Please tweet us @siliconangle.

Latest from R. Danes

Backup doesn’t move multicloud data, not that anything’s wrong with that

Know a good way to shush a room full of techies? Ask them how to move data in multicloud within cost and time constraints acceptable for analytics. After a long silence, they might venture some suggestions. A few may opine that backup is the snafu solver du jour, and perhaps its newfound powers could prevail ...

Backup brings overdue all-in-one to big-data party

Imagine the things we could all do if we all got our data act together. A startup seeking funding might predict how many 30-year-olds in Maine would buy a scooter on credit. But, alas, the needed homebase, single point of reference, visibility, etc., have eluded us. Oh, wait — data backup had all of those ...

Will quarreling new, legacy tech make friends in on-prem cloud?

These are frustrating times for companies shopping for information technology services. They ogle new products making startup founders millions and billions of dollars. Then they find that their environments, applications and organizations don’t fit in or around them. How do they nail the best value and performance when sticker prices and ratings may not hold? ...

Why cloud migrants can’t leave home without observability

Safely ensconced on-premises, companies may have contemplated observability. Perhaps they built a serviceable observability system for fixing some common issues. They said, “One day, we’ll need always-on, end-to-end, state-of-the-art observability software — but not now.” If they’ve moved to cloud since then, that day may be today. The cloud — and particularly cloud-native applications — ...

We won’t reach enterprise 4.0 without C-level push, says SAP

It seems we’ve been chattering on about technology disrupting work for a while now. Call it enterprise 4.0 or industry 4.0. Supposedly, it’s a workplace where automation, artificial intelligence, robots, etc., have altered the way we produce goods and services. These technologies exist in some form or another today, so how come work feels the same as it did ...
VIDEO EXCLUSIVE

What do fun and games have to do with AI R&D?

Artificial intelligence isn’t all fun, games and entertaining gadgets. When people put trust in AI technologies that aren’t proven 100% reliable, consequences can be tragic. The fatal autonomous Uber crash and it’s fallout have underscored this for the public. But some games, toys and low-stakes experimentation are a great way to help produce AI for prime-time, ...

What’s this agile cloud stuff good for anyway? How about 70% YOY growth

Public cloud was supposed to be cheap and simple. Now, some may say, it’s neither. On-premises holdouts gloat; their peers counter that its long-term digital transformation that counts. DX — plus elasticity, flywheel effect, scalability — are gaseous marketing terms to naysayers. Are there any solids to point to in cloud to convert them? There are indeed ...

Fight to finish: AI-on-AI and dev-on-dev speed up model training

Why would anyone trust artificial intelligence? It’s basically the same reason we trust ourselves to make decisions every day. We examine data, reference historical outcomes, and project into the future. The speed and number of cycles from reference to prediction — and all the data throughout — determine just how good AI can get. “We ...

How does an observability platform help your business innovate?

Why do some businesspeople spend as little time thinking of observability as they can get away with? Maybe they’d rather not dwell on the ugly thought of system problems occurring. Would they warm up to it if it didn’t merely remedy problems, but also had some nifty, value-adding tricks? In fact, the best observability systems do, according to Arijit ...

AWS revs machine-learning train with custom silicon, new SageMaker goodies

Machine-learning models are like pancakes; the first one is usually crummy. In fact, if they fed on models, developers might drop a shirt size before they got one to the table. Speeding up iterations and cutting guesswork as well as cost can expedite an algorithm’s trip to piping hot, accurate insights. ML doesn’t just sit ...