B1shop Chicago @GregStaskowski

Solid-state batteries have been plagued by the formation of metallic cracks called dendrites that cause them to short circuit. MIT researchers used a new visual technique to measure stress in a material as a dendrite crack grows. news.mit.edu/2026/why-solid…

6-7 decades of computer systems research in a nutshell

@omgsidewalks Perovskite count?

“NUCLEAR FUSION Half a Century of Magnetic Confinement Fusion Research” by C M Braams and P E Stott A really interesting deep dive into the first 50 years of magnetic confinement fusion research and covers plasma physics and tokamaks pretty decently too. I found it also online for free if you want to read it, it is a little long though, enjoy. Source ☢️: library.psfc.mit.edu/catalog/online…

@seankiv Yeah no.

@abmoneyxo Oak Park.

Time (and squad cars) go by so fast. A Salute to Jake, Elwood, and "The Blues Brothers," released on June 20th, 1980. #ChicagoHistory

Got a ticket to check out the Obama Presidential Center? Here's where you should eat before or after your visit blockclubchi.co/3SeQVXU

R.E.M.'s (Don't go back to Rockville) summer vibe.

Once you've been homeless, you'll always be at risk. It haunts us. I have that fear now

Giving some thought to this mild reassessment of remote work and considering if a more viable balance might be, home office, some in office meetings and a makerspace for ones own projects and transitional time?

I have fallen into a rabbit hole, listening to the great physicist John Wheeler reminisce about his former student Richard Feynman, their meeting with Albert Einstein, etc. Here he discusses hiding entropy in a black hole w Jacob Bekenstein youtu.be/Bti2_qwJkTA?is… via @YouTube

Chicago’s Music Box Theatre will unveil a new 98-seat theater June 26, marking the first time the venue will have three screens in its nearly 100-year history. blockclubchi.co/4eueiUS

@sqwabb @engineers_feed It's the anisotropy that makes this special Stan. Utterly different properties in different crystallographic orientation.

@dschwa8059 There's some problems with the underlying description of Cantor and set theory and Wallace wasn't a mathematician. While a kind of dorm room bull session with smart examples it wouldn't pass muster beyond undergrad.

Attending the Obama Center opening watch party was a full-circle moment for three coworkers taking a Metra train to Hyde Park. They scored tickets through their philanthropic workplace—just as they had nearly two decades ago when they attended Obama's 2008 Grant Park party...

@damlabilgenn SISU. One word. The Finns have it. Get some.

Y'know the life of a heat treat metallurgist is always intense. #repoEngineer

Note, another low cost hack when Uber and Lyft are jammed is the Divvy Bike and bus trip to areas you wouldn't otherwise reach. I haven't seen that in the wild but I do think it's doable.

A naval officer built a program that let computers understand words instead of numbers and was told for three years that what she had already built was impossible. She shipped it anyway and modern programming was born from it. Her name was Grace Hopper. She did not start as a programmer. She started as a mathematician. She had a PhD from Yale and a teaching post at Vassar, and she was 37 years old when she left it to join the Navy in the middle of the Second World War. They almost rejected her. She was too old and too small, fifteen pounds under the minimum weight. She pushed until they let her in anyway. The Navy assigned her to a machine called the Harvard Mark I. It was one of the first programmable computers on Earth. Fifty feet long, eight feet tall, a wall of relays and switches that clattered like a room full of typewriters. Most of the officers around it saw a giant calculator. Hopper saw something else. She spent the war writing instructions for it and ended up writing the first manual anyone had ever written for a computer, five hundred pages explaining how to make the machine think. Here is the part almost nobody knows. In those early years, programming a computer meant writing in raw machine code. Long strings of numbers that mapped directly to the switches inside the hardware. Every program was a wall of digits. To change one thing you rewrote the numbers by hand. It was slow, brutal, and almost impossible to teach. The people who could do it were a tiny priesthood, and they liked it that way. Hopper looked at this and asked a question that sounds obvious now and sounded insane then. Why are we writing in the computer's language. Why can't the computer translate our language into its own. Her idea was a program that would take human-readable instructions and turn them into the machine code automatically. You write the words. The program does the translation. She built it. By 1952 she had a working version running on the machine. She called it a compiler. And then nothing happened. Not because it failed. Because nobody believed it. She would explain what she had built, and people would tell her, flatly, that it was not possible. Her own words later were almost too plain to be dramatic. She said she had a running compiler and nobody would touch it. They carefully told her that computers could only do arithmetic. They could not do programs. Sit with that. She was standing next to a machine that was, at that moment, translating words into code, and the people looking at it were explaining to her that the thing in front of them could not be done. The proof was running. They preferred the assumption. It took about three years to break that wall down. Three years of demonstrations and arguments and slow conversion, one skeptic at a time, while the idea she had already proven sat there waiting for permission to matter. She kept pushing past it. If a machine could be taught to translate symbols, she reasoned, it could be taught to translate something closer to plain English. Most of the field thought that was a step too far. Mathematicians liked symbols. Symbols were precise. English was for people who could not handle real programming. Hopper's insight was that most of the people who would one day need computers were not mathematicians. They ran businesses. They managed inventory and payroll and records. They thought in words, not notation. So she built a language oriented around English instructions, a thing called FLOW-MATIC, where you could write a line that almost read like a sentence and the machine would understand it. That language became the direct foundation for COBOL, released at the end of the decade. COBOL ran the banks. It ran the insurance companies. It ran the government. Decades later, long after Hopper was gone, it was still quietly running underneath the financial system, billions of lines of it, processing transactions on machines she never lived to see. The deeper thing she gave the world was not any single language. It was the idea underneath all of them. That a program could be written once, in something a human could read, and translated by the machine into whatever code the hardware needed. Every high-level language written since stands on that idea. Every time you write a line of code in plain words instead of raw binary, you are using the thing she was told could not exist. There is one story everyone does know about her, and it is the smallest one. In 1947, a team working on a later Harvard machine found a moth trapped in a relay, causing a fault. They taped it into the logbook and wrote that they had been debugging the system. Hopper loved telling that story for the rest of her life. It is the thing she is most remembered for, a literal bug in a computer. It is strange that the most famous moment of her career is a dead moth in a notebook, and the thing that actually changed the world, the idea that machines should meet humans halfway, is the part most people have never heard. She retired from the Navy as a rear admiral. She was the oldest serving officer in the fleet when she finally stepped down, in her late seventies, on the deck of the oldest commissioned ship in the Navy. She spent her last working years doing the thing she said mattered most to her, which was not the compiler at all. It was teaching young people that the most dangerous phrase in any language is we have always done it this way. She spent her whole life proving that sentence wrong. She built the thing they said could not be built, stood next to it while they denied it was real, and waited three years for the rest of the world to catch up to a machine that was already doing the impossible in front of them. The machines understand our words now. They have for seventy years. Someone had to be told it was impossible first.