I’m a physics teacher, and quite a few stories have stayed with me throughout my career.
In my class, there’s an unwritten rule: For every final research project, students must submit a lab notebook recording all raw measurement data. Missing data or fabricated results mean an automatic F, in science there’s simply no room for dishonesty.
At the end of the term that year, a girl came to turn in her reversible pendulum project which was meant to measure the acceleration due to gravity. The data in her notebook was all over the place, and her graph was wildly off from the theoretical value of 9.8 m/s².
"My results are... completely ruined," she said. "Everyone else got nice numbers close to 9.8. I guess I'm getting an F".
I looked at her densely packed notebook, filled with meticulous notes: measurements taken at 2:00 AM, the humidity in her bedroom, even the exact times the string snapped and had to be retied. Having taught for over a decade, I can easily tell who fakes their numbers to match the textbook and who stays up all night putting in the real work.
"Why didn't you just tweak the numbers a bit to get closer to 9.8, like the others?" I asked.
She looked up, her eyes rimmed with red, but her voice was steady: "Because the data is what it is. You taught us that a scientist never lies about their data."
I silently flipped to the next page and marked a big red A.
She was stunned. "Wait... but my experiment completely failed?"
"Your experiment didn't fail. It just proved that your pendulum had air drag and a wobbly pivot" I said. "Science isn't about manufactured perfection, it's about the pursuit of truth. You stood up for the truth, and that's the true mark of a researcher."
Starting that semester, I created a small award in the corner of the lab: "The Best Failed Lab Report", given to the experiment with the most skewed results, but the most honest logs and thorough error analysis.
I want these kids to understand that having the courage to acknowledge mistakes and confront reality matters far more than faking a perfect score just to please someone else.
I’m 54, a physicist, have spent decades using mathematics to study the universe, solve problems, and build things.
If your work touches numbers, now or in the future, and you want to learn math properly, this thread shows a from-the-ground-up math you’ll actually need:
Dog tokens are down about 30% from April, per CoinGecko's own sector tracking.
Nobody running one will tell you that, so: yes, us too.
What ethereum:0x2598c30330d5771ae9f983979209486ae26de875 did with the last two years is build a launchpad on top of the infrastructure, because a token that only goes up when the sector goes up isn't a business.
Ask any project you hold what they built during the drawdown. The answers are informative.
$AI moves between EVM chains through Axelar's Interchain Token Service, and between Ethereum and Solana through Wormhole.
Same token. Same supply. 20+ chains. #ANYINU
Ask your favourite memecoin to do that.
Any Inu started as a dogcoin on 23 chains.
Two years later we've turned that infrastructure into a launchpad. You can deploy a token, run a staking pool, and put an AI market maker behind it, on Ethereum, Solana and Base.
Here's what we built and why. 🧵
The multichain thesis got called dead about 18 months ago. Everything consolidated onto a handful of chains and the industry called that maturity.
$AI kept shipping across 23.
Name a chain you wrote off in 2024 that's still here...
"Shipped when there were no users" is the line that lands.
We kept deploying the same token to new chains through a stretch where the dog sector fell about 30%. Nobody asked us to. Solana was one of them.
What did you ship that nobody noticed at the time?