Author: paschmann

Do Things That Don’t Scale

paschmann

http://www.paulgraham.com/ds.html#f1n

One of the most common types of advice we give at Y Combinator is to do things that don’t scale. A lot of would-be founders believe that startups either take off or don’t. You build something, make it available, and if you’ve made a better mousetrap, people beat a path to your door as promised. Or they don’t, in which case the market must not exist.

Bookmark: Quantum Links

paschmann

Good practical Python Quantum workbook

https://livebook.manning.com/book/learn-quantum-computing-with-python-and-q-sharp/chapter-1/v-8/

QCodes Github is what a lot of experimenters are using to control machines.

https://github.com/QCoDeS/Qcodes

Quantum Jobs

https://medium.com/qiskit/the-hitchhiking-cats-guide-to-getting-a-job-in-quantum-computing-da7e3bb9ff64

UC Berkley Course – Vazirani

MIT Open Course on Quantum

https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-845-quantum-complexity-theory-fall-2010/lecture-notes/

Qiskit Hello

https://mybinder.org/v2/gh/QISKit/qiskit-tutorial/master?filepath=community/games/Hello_Qiskit.ipynb read more

Bookmarks: Emerging Architectures for Modern Data Infrastructure

paschmann

As an industry, we’ve gotten exceptionally good at building large, complex software systems. We’re now starting to see the rise of massive, complex systems built around data – where the primary business value of the system comes from the analysis of data, rather than the software directly. We’re seeing quick-moving impacts of this trend across the industry, including the emergence of new roles, shifts in customer spending, and the emergence of new startups providing infrastructure and tooling around data.

In fact, many of today’s fastest growing infrastructure startups build products to manage data. These systems enable data-driven decision making (analytic systems) and drive data-powered products, including with machine learning (operational systems). They range from the pipes that carry data, to storage solutions that house data, to SQL engines that analyze data, to dashboards that make data easy to understand – from data science and machine learning libraries, to automated data pipelines, to data catalogs, and beyond. read more

Giant Trinity Build

paschmann

This was a fun build on a Aero bike frame that a buddy gave me. Since I now had a bike, it got me into doing my first 70.3 Ironman event in 2021 (Augusta). It took a lot of searching and scouring the web, eBay and local sellers on Craigslist, but aside from a couple mistakes here and there, it turned out great. The bike is really light compared to my more modern Canyon Speedmax.

Below is a list of part numbers, references, purchases and photos I was using during the build.

To figure out what crank lengths I should by my inseam is 85cm (33.5”) & a second remeasure was roughly 33 – 33 & 1/3. Using this a general crank length formula is: 1.25 * inseam (in cm) + 65 = 171.25. Majority of cranks coming in 170cm and 172.5. So I decided on the slightly longer 172.5cm cranks. read more