Dwelling in unlived lives
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NEW YEAR
A piece of advice that applies to the beginning of every new year:
Every time we close a year and start a new one we go through a transition phase: Closure, reset, and restart.
This phase leads to introspection. But introspection has two sides to it: it can be useful, or it can be useless.
You can observe the past for what it was, or you can think about what could have been.
Thinking about what something could have been is a double-edged sword.
Yes, you can learn from it to better adjust your aim in the future, but you can also be stuck in it and not move forward.
My advice is to be mindful of not dwelling in unlived lives.
Focus on the life in front of you.
I like thinking about speculative futures, and I do it for the sake of joy and exploration. But one has to also be careful to not be sucked into this other form of unlived lives. Be it writing, drawing, gaming, reading, etc. Each activity should help you enjoy and experience the present, regardless of whether is taking you to another time, real, or reality.
I wish you health, joy, and work for the year ahead.
JFM
👁️ Omnirealities
Augmented Reality for Remote Worker Training and Collaboration
Lorne Fade writes for ARPost about the common misconception that the gaming industry is the primary beneficiary of AR solutions, and shares observations on the core benefits that AR brings to companies:
Augmented reality training can save companies time, money, and reputation. Regardless of sector, training individuals is a necessary step in the onboarding process. No matter how experienced or knowledgeable individuals may be, there will be hiccups along the way as the individual adjusts to a new environment. One way to reduce the impact of costly errors is to train staff with AR.
🔮 Future Scenarios
The computational protein designers
Jeffrey M. Perkel writes for Nature about the role of protein engineers dedicated to finding ways to create molecules from scratch. This is a long-read from 2019, but I found it a great primer on learning about the latest in the challenges and advancements in the de novo protein design industry.
[…] by making proteins from scratch, researchers can design proteins to be more forgiving. They can build enzymes with activities unknown to nature, using co-factors and amino acids that are not part of the standard macromolecular toolkit. And scientists can test their understanding of protein biology, to ensure that they truly grasp the fundamentals.
David Baker, Ph.D. and Director of the Institute for Protein Design at the University of Washington:
“We’re making everything up from scratch,” […] “And that’s a very strict rule in the lab: you’re not allowed to start with anything that exists in nature, because we wanted to be able to be sure we understand everything and design everything from first principles.”
De novo protein engineering takes weeks of computational time and months of iteration. So they created an online gaming interface, FoldIt, to challenge players to help with protein folding. The platform has been providing useful results, that matched or outperformed algorithmically computed solutions.
💀 Not a Cylon
Alycia Rainaud, @maalavidaa
Alycia Rainaud, @maalavidaa
Alycia Rainaud, @maalavidaa
🧠 Common Enemy
GPT-3 Creative Fiction
Gwern Branwen is an American writer and researcher who created a series of experiments in creative fiction using GPT-3, the infamous autoregressive language model that uses deep learning to produce human-like text.
The following is a piece created by an AI model using as an input only a brief excerpt from one of Paul Graham’s articles.
Again, the following was created by an AI:
Another alternative is to make an assertion and then prove it false. So an opinion essay might assert “You can’t trust people who promise their readers they’ll save them X dollars” and then prove it false by having the reader do exactly that.
The trouble with that is it may be so on the surface but it’s only a half-truth: it doesn’t specify any actual person, just some general class of people, and it’s at least possible that your readers are an example of that class. It’s also possible that your readers are a special case.
Another alternative is to make an assertion that’s almost but not quite true, so the reader has to decide whether or not to believe you. This can be useful when the statement is obviously absurd but you want to make a point anyway. But I don’t think it’s useful for essays.
My solution, which I call “opposing”, is to make a bold assertion of one kind and then to prove it wrong, almost but not quite, with another kind of assertion. These can be quite different assertions and still be opposed.
What I find fascinating here is not only how human it sounds, but how it managed to propose its own premise to challenge readers of essays, and it even named it (opposing).
When we think about how difficult will be to identify synthetic data, texts like this one make me feel like it may not even be possible to differentiate human-made text from AI-made text in the near future.
Are you hacking with futures and other realities? Do you have comments, stories, or suggestions? I’d like to hear from you. Reach out: heyfffutures@gmail.com
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