8 posts tagged

Tech

A case for a new blog engine

Bear with me here. I’m trying to convince myself that it’s worth it to write my own blog engine.

As a clever man said:

In the past few years I’ve been trying to store my writing locally, but writing in public is powerful. It is excruciating to keep writing on the web (especially with inline images, like here) up to date with local notes. And “local” here doesn’t mean “stored in a repo”, like for a static site, because a repo is separate from where I’m writing: it has been Evernote, then Notational Velocity, then nvALT, now Bear, and soon, hopefully, my own open-source project.

I offer a new paradigm: own your writing, publish everywhere. Now it’s usually backwards, you’re writing on the internet somewhere and then maybe, if the service lets you, export what you’ve written.

What does this have to do with a blog engine? It’s a start, where the CMS, or the publishing platform, will only be a container for published writing, not its master location.

My current engine, Aegea, is woefully inadequate due to it being closed-source. And Wordpress and the like are either too cumbersome to setup the way I need (I have a small, but _opinionated_ (as they say) set of necessary features) or don’t have what I need at all.

A static site would fit the bill but it doesn’t have comments, and no, Disqus won’t cut it.

In the end, I _want_ to write one. I’ve been learning some Go and this is a great opportunity to write a medium-sized web-service, which I have never done before. And it’s very motivating because I want to keep my writing published. I’m quite sure a minimal version can be done in a week, so that I can migrate to it, and its incompleteness should motivate me to work on it further.

I have already compiled a minimal list of features to implement first and it’s manageable, so there’s hope.

Can’t wait to share what I come up with.

2018   Product Ideas   Spisali   Tech

64 kilobytes of fast RAM

 

Ads are the best thing about old computer magazines. These are from the August 1979 issue of the BYTE magazine about LISP.

At the time those computers were considered powerful, or at least capable, and now, 40 years later, we buy chips with similar specs wholesale for $1 or $2 to power some kind of IoT device, and they’re considered severely underpowered for any real embedded work. Our WiZ Wi-Fi connected lamps use a chip with similar specs, an ESP8266, made popular because of a free RTOS and low price, but even that has 96 KB RAM, a 50% increase.

High end servers have RAM in the terabytes, a hundred million percent increase from these 1978 chips.

What I wonder, looking at the present-day magazine ads, praising laptops to be thin, light, and powerful, is just how peddling, thick and underpowered they will seem in forty years’ time. Even more suprising is that we do feel they are genuinely light (just under one kilo!) and thin (just 9 mm thick!), exactly the same as we felt about laptops of ten years ago, which have been twice as thick and twice as heavy.

The only constant thing about consumer computers is that a good one always costs $2000.

 No comments   2017   Tech

Superintelligence: The Next Big Thing?

Some fascinating reading this week!

First, the New York Times asking “Why are the corporations hoarding trillions?” where they claim Apple, Google and other giants don’t spend or convert their cash, as if expecting something just beyond the horizon. Something that would need an insane amount of money.

Second, Ben Goertzel with “Superintellingence: fears, promises and potentians”, a through and in-depth review and criticism of current literature by Bostrom, Yudkowsky and others.

This struck me as amusing:

As Peter Norvig of Google has noted (personal communication), quite suddenly we’ve gone from outrage at the perceived failure of AI research, to outrage at the perceived possible success of AGI (Artificial General Intelligence) research!

For the last decade, AI research and theory is booming, and it’s very hard to ignore the fact that every other app or service now has some form of machine learning or AI-like capabilities, the most common example being Siri on iOS. There are many more examples, like Google Now or various personal assistants like AlfaSense, X.ai or even something as simple as a blog layout system.

Very excited to see the progress.

 No comments   2016   Books   Tech
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