Benson’s ears are ridiculous.
But it’s kind of true.
I recently finished reading Homo Deus: A Brief History of Tomorrow by Yuval Noah Harari, which imagines what the lives of our children, grandchildren, and beyond will be like and how technology will affect them.
We generate copious amounts of data each day and give our personal electronic devices and social networks almost unfettered access to all of it. Everything from how long we sleep, how often we exercise, where we go each day to the types of songs, movies and books we like.
There was one passage from the book that I found both amazing and frightening:
A recent study commissioned by Google’s nemesis – Facebook – has indicated that already today the Facebook algorithm is a better judge of human personalities and dispositions than even people’s friends, parents and spouses. The study was conducted on 86,220 volunteers who have a Facebook account and who completed a hundred-item personality questionnaire.
The Facebook algorithm predicted the volunteers’ answers based on monitoring their Facebook Likes – which webpages, images and clips they tagged with the Like button. The more Likes, the more accurate the predictions. The algorithm’s predictions were compared with those of work colleagues, friends, family members and spouses.
Amazingly, the algorithm needed a set of only ten Likes in order to outperform the predictions of work colleagues. It needed seventy Likes to outperform friends, 150 Likes to outperform family members and 300 Likes to outperform spouses. In other words, if you happen to have clicked 300 Likes on your Facebook account, the Facebook algorithm can predict your opinions and desires better than your husband or wife!
This is one of the main reasons why both Google and Facebook have some of the largest (and most effective) advertising networks on the internet.
They fundamentally know who you are and what you like and know us better than we know ourselves.
Indeed, in some fields the Facebook algorithm did better than the person themself. Participants were asked to evaluate things such as their level of substance use or the size of their social networks. Their judgements were less accurate than those of the algorithm.
Excerpts from “Homo Deus: A Brief History of Tomorrow” by Yuval Noah Harari.
November is traditionally “National Novel Writing Month.” The goal is to write a short novel that is 50,000 words in length. I always have grand plans to attempt it and have started a number of times over the years but have never actually finished. (One day, I swear!)
Recently, I stumbled across a geekier take on it, called National Novel Generation Month. The goal of this particular project is to write code that can generate a 50,000 word novel instead. Hey, why not?
I published my code at the beginning of November for my project: The Complete Encyclopedia on 1,449.5 Random Ways to Make a Sandwich.
It uses data parsed from a 1909 book, entitled “The Up-To-Date Sandwich Book: 400 Ways to Make a Sandwich”, written by Eva Greene Fuller and now available for free in the public domain.
For this particular book, new sandwich recipes were generated using Markov chains created from the above text.
Please don’t try to actually make any of the sandwich recipes created with this process. However, if you do, please contact me and show me pictures.
Disclaimer: I cannot be held responsible for any health issues that may arise from eating any of these sandwiches.
There are definitely some interesting ones…
BUTTERED CHEESE AND OLIVE SANDWICH NO. 3
Use three slices of Swiss cheese, spread fresh butter and two tablespoonfuls of olive oil, the juice of two oranges and knead the mixture.
On Friday, we did a family trip to The Color Factory in San Francisco. It’s a really fun interactive exhibit and is especially fun for the tiny humans.
I’ve tried to get into audiobooks in the past, but never found them enjoyable.
That changed earlier this summer ahead of our epic road trip to Wyoming to see the total solar eclipse (oh hey, I never wrote about that experience). I saw an offer for new Audible memberships that sounded like a pretty good deal, so I jumped on it.
The first book I ended up download was The Power Broker, which ended up totaling over 60 hours of audio! And you know what?
It. Was. Awesome.
I think I’ve finally found out why I could never get into audiobooks in the past. It’s because I listened to them at normal 1x speed. The narrators read the stories so so so slow. If I speed things up to 1.5x or 1.75x, it sounds much more interesting to me and I find that I’m able to keep focus.
Plus, it turns a 66 hour story into a 50 hour story. Saves time (for more audiobooks). I really recommend it. It’s been a nice break from listening to my standard array of podcasts, which have focused on depressing news as of late.
Since I subscribed in August, I’ve now listened to:
- The Power Broker (66 hours)
- Al Franken: Giant of the Senate (12 hours)
- An Odyssey: A Father, a Son and an Epic (10 hours)
- Hyperion (20 hours)
- American Gods (20 hours)
- Hillbilly Elegy: A Memoir of a Family and Culture in Crisis (7 hours)
And I’m currently working through Washington (41 hours) by Ron Chernow (he wrote the recently popular biography about Alexander Hamilton, which the musical is based on).
At the moment, something like 3,000 homes have been lost in the North Bay. It’s hard to even fathom the thousands of tragedies unfolding in the North Bay this week and how people who’ve lost their homes, pets, friends, loved ones, or all of it are even coping right now. ❤️
In 2003, a meth addict trying to burn down a house started the Old Fire in the mountains near our house in Southern California. At the time, my dad worked for San Bernardino County and helped maintain their emergency communications system.
When the fires broke out, he was tasked with heading up the hill and bringing some emergency generators and other supplies to an *old* AT&T communications bunker on Strawberry Peak. It was built in the 1950’s and allegedly hardened to withstand a nuclear war. I ended up making the trip up with him.
For two days, we sat on top of the bunker and watched the fires slowly climb the mountain toward us. They were far enough away that we couldn’t hear trees burning, nor hear the bombers dropping Phos-Chek, nor smell smoke due to the wind blowing in a different direction, nor hear the sirens of firetrucks passing below on Highway 18.
At night, we watched the eerie glow of the flames play off the constantly changing patterns of smoke. Fortunately for us, the flames never reach the communications bunker.
Down below, 90,000 acres and 1,000 homes would ultimately be lost.
We had a few close calls growing up, but we were always lucky. I can’t even pretend to imagine the pain and suffering our friends and their families are going through right now.
A friend of mine recently asked for some suggestions on which language she should use to learn to code.
I find Python to be super fun and easy to pick up. Plus there’s tons of neat libraries available for manipulating data. One bonus: down the road, you can start playing with some of the many machine learning libraries that are available. Then you can build a model that will predict names of Android phones.
I’ve played only a little bit with Swift. I like it and I think Apple is doing some good work trying to provide tools to help people learn. For now, you’re mostly going to be limited to building mobile apps, though there are more tools being built that expand its uses (e.g., servers).
We’ll be road tripping to Wyoming to see the total solar eclipse. Apparently, experiencing one is really weird.
During a solar totality, animals usually fall silent. People howl and weep. Flames of nuclear fire visibly erupt like geysers from the sun’s edge. Shimmering dark lines cover the ground.
I can’t wait!
Here’s a random little side project that I’ve been working on: Emoji Say What?
It’s like a game of telephone, but using the latest in human communication technologies,
Basically, you visit the site and get a completely out of context sentence or set of emoji and it’s your job to decipher it. And so on and so on. It evolves over time and eventually you get something like this.