haruki zaemon

(via Ron Jeffries)

I almost quit this year’s New York City Half Marathon. I’d been running for nearly two hours in freezing temperatures, straight into the wind. All I wanted was to beat last year’s time, even by just one millisecond. If it weren’t for a well-timed cheer from a friend around mile 10, I probably would’ve called it a day.

[…]

All I wanted from this year’s NYC Half was to run it faster than last year. I wanted that because, last year, I ran the race — my first half-marathon — as part of Team ALS. I joined on a whim mere weeks after my mom died from the incurable disease. It felt like rebellion after a year defined by ALS.

[…]

I’ve come to accept that, at the heart of it, I didn’t really want to do better this year. For all the impressive tech it [the Apple Watch Ultra] packs in its titanium case, it cannot measure grief. Mental health is also health, and as they say, the body keeps the score. It just so happens that the mental side of the equation is much harder for wearables to meaningfully quantify.

[…]

All that’s left is to take these lessons and apply them going forward. I’ve already signed up for my next race. I will 1,000 percent be testing no less than four devices — including the Ultra — while training. But for once, I have no time goal. I’m trying not to make a narrative of the data. I think I’ll simply run and see what that feels like.

1. #health-wellbeing
2. #technology

(via The Sizzle)

Texas A&M University–Commerce seniors who have already graduated were denied their diplomas because of an instructor who incorrectly used AI software to detect cheating.

Texas A&M University-Commerce said they were investigating the incident and developing policies related to AI in the classroom. The university denied that anyone had received a failing grade.

I can’t wait to never find out about all the other stuff that’s going on that negatively impact our lives.

(p.s. go subscribe to The Sizzle)

1. #artificial-intelligence
2. #technology

(via The FLUX Review, Ep. 98)

One crowdfunding campaign has raised enough money to build remote-operated mounted machine guns that can be controlled with a Steam Deck, a portable gaming computer with joysticks and buttons on the sides (similar to the Nintendo Switch). They’ve given these guns to Ukrainian soldiers, who will be able to swivel the guns around and shoot while not being exposed to gunfire themselves.

1. #technology
2. #ukraine

It’s great for rental agents, but not so great for vulnerable renters who find themselves on the wrong end of the algorithms that are can determine who does, and doesn’t, win a tenancy in a tough rental market.

[…] some of the technology already in use is programmed to filter through the data and arrive at what the platform determines are the best prospects. 

It’s a process that leaves people who rent at the mercy of automated decision-making over which they have no control.

In many ways, online rental applications circumvent existing tenancy laws, effectively serving as a tenants check, in much the same way as tenant databases or ‘blacklists’.»

1. #data
2. #privacy
3. #technology

These scenarios certainly resonated with me as in many ways they speak to reducing cycle time.

All organisations waste a huge amount of time believing that they are making progress on decisions, when in fact they’re just involved in the theatre of decision making. This happens through indirect actions that feel like progress is being made, but in fact contribute nothing to it. Small changes can speed up progress dramatically.

Tangentially related, I often need to emphasise with my Aikido students the importance of reducing intervals between techniques. Reducing a 15 second changeover to 5 seconds could mean getting in another 10 practice runs.

If, like me, you believe in iterating to learn, reducing cycle time is critical.

1. #decision-making
2. #leadership
3. #software-engineering
4. #technology

A quantum computer in the next decade could crack the encryption our society relies on using Shor’s Algorithm.

1. #privacy
2. #technology
3. #video

the models tended to produce images of people that look white and male, especially when asked to depict people in positions of authority.

the models’ output overwhelmingly reflected stereotypical gender biases. Adding adjectives such as “compassionate,” “emotional,” or “sensitive” to a prompt describing a profession will more often make the AI model generate a woman instead of a man. In contrast, specifying the adjectives “stubborn,” “intellectual,” or “unreasonable” will in most cases lead to images of men.

In almost all of the representations of Native Americans, they were wearing traditional headdresses, which obviously isn’t the case in real life.

image-making AI systems tend to depict white nonbinary people as almost identical to each other but produce more variations in the way they depict nonbinary people of other ethnicities.

1. #artificial-intelligence
2. #diversity-equity-inclusion
3. #technology