What about images, links?
Formatted text like bold or underline?
I also prefer plain text, but in most of my emails I talk about technical stuff, or I send transactional emails that require actions, in which case showing buttons is a much better user experience than plain text.
Every MUA I've used allows the reader to set a font size, so changing font sizes is 100% a feature of plain-text emails. Then they get the link the size they need to read it correctly and it's absolutely easy to read. This here comment is pain text. Is it hard to read this link:
I think the OP app is meant for creating transactional emails (or bulk-send emails like newsletters).
Those templates should account for all types of people and accessibility levels (including things like ADHD, where you need a big red button to click, otherwise you get overwhelmed by a block of text).
Using a URL shortener obviously. But you are right, if they only send plain text, they won't be able to include those 1x1 images at the bottom to track whether you have opened the email. Any sane email client blocks images by default, but whatever.
Yeah, I get it, I unfortunately live in the real world too. I like to keep it plain text whenever possible but it's extremely useful sometimes to have inline screenshots and stuff like that.
I didn't mean to be sarcastic but it's just that to me, philosophically, email is a plaintext technology that had HTML bolted on to it kicking and screaming, and it's always been kind of crap. People like me hate things that are fundamentally ugly and crap even if they are useful. The web was designed for HTML from the start.
Not sure if AI can have clever or new ideas, it still seems to be it combines existing knowledge and executes algoritms.
I am not necessarily saying humans do something different either, but I have yet to see a novel solution from an AI that is not simply an extrapolation of current knowledge.
Speaking as a researcher, the line between new ideas and existing knowledge is very blurry and maybe doesn't even exist. The vast majority of research papers get new results by combining existing ideas in novel ways. This process can lead to genuinely new ideas, because the results of a good project teach you unexpected things.
My biggest hesitation with AI research at the moment is that they may not be as good at this last step as humans. They may make novel observations, but will they internalize these results as deeply as a human researcher would? But this is just a theoretical argument; in practice, I see no signs of progress slowing down.
This is my take as well. A human who learns, say, a Towers of Hanoi algorithm, will be able to apply it and use it next time without having to figure it out all over again. An LLM would probably get there eventually, but would have to do it all over again from scratch the next time. This makes it difficult combine lessons in new ways. Any new advancement relying on that foundational skill relies on, essentially, climbing the whole mountain from the ground.
I suppose the other side of it is that if you add what the model has figured out to the training set, it will always know it.
We call that Standing On The Shoulders Of Giants and revere Isaac Newton as clever, even though he himself stated that he was standing on the shoulders of giants.
The difference people are neglecting to point out is the experiences we have versus the experiences the AI has.
We have at least 5 senses, our thoughts, feelings, hormonal fluctuations, sleep and continuous analog exposure to all of these things 24/7. It's vastly different from how inputs are fed into an LLM.
On top of that we have millions of years of evolution toward processing this vast array of analog inputs.
Jokes aside, imagine you give LLMs access to real-time, world-wide satellite imagery and just tell it to discover new patrerns/phenomens and corrrlations in the world.
It means extending/expanding something, but the information is based on the current data.
In computer games, extrapolation is finding the future position of an object based on the current position, velocity and time wanted. We do have some "new" position, but the sistem entropy/information is the same.
Or if we have a line, we can expand infinitely and get new points, but this information was already there in the y = m * x + b line formula.
Shameless plug: if you think about switching from Google Analytics/Hotjar, check out my project[0] (built in EU, started in Romania, now working on it remotely in Netherlands).
If not, happy to hear any criticism or the alternatives you decided to go with instead.
I've been building my project[0] for 14+ years, but I'm still looking forward to the day I won't have to worry about next month's rent. Customers are happy though. Last week I got messages from two customers that purchased more than 7 years ago, because they wanted to install/use the product again. It was fun to revisit our email conversations and to see how much the product has evolved since. What's funny is that the feeling is the same after 1, 5 or 15 years. There's always stuff to optimize and improve. Unless it's a standalone experience (e.g. game or a movie), most software and tools do need constant updates and improvents to keep up-to-date with the current world.
What's funny, is that I had many other projects attempted over the years, but many rise and die quickly, yet the one that lasted the longest is also the one that is likely to last longest from now.
I tried it, it was fun to get started, but after 3-4 sessions, when you want to start getting good and learning stuff, it's not fun anymore.
I tried playing with Playtomic, with better players, and everyone expects to play the same, go and play at the net as that's the main goal, but I dislike staying close to the net and playing the reflex game, while trying to not get hit by the ball. I have a lot more fun playing back court, and volleying the ball, but apparently that's not the way to play this sport.
Also, the wall part of the game, once you play against better players, is not fun. Most of the balls go in the corner, and you have to wait for the ball/predict and avoid hitting the glass or hit from an uncomfortable position, which is not as fun as the open play game.
Is $249/month something most small brands/shops can afford? Many have a few $ks in total revenue.
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