Try playing Dungeons & Dragons or Pathfinder (or any number of other systems.) Pathfinder is super deep and complex.
There's also an entire community of people who play Table Top Role-Playing Games (TTRPGs) solo and use the outcomes of their play reports to blog or write fiction.
Also, the tooling around these games is very interesting if you want to build an app: Crafting calculator? Generative hexcrawl maps? Random tables? Statistics tools for dice rolls?
What's to stop someone putting some Terms of Service clause on their site, or creating a license which guarantees the site owners ownership of any content generated by scraping their site?
Any tips or "get your foot in the door" advice on how someone currently in a CS career, but interested in biology could make this career transition? As a simple CS-minded person, I don't see any LeetCode for synthetic biology sites :)
You can slap the buttons hard to get the table to wobble a bit, you can tap the cabinet with your wrists, you can grab the table tightly and move a leg or a hip in the opposite direction while keeping your body rigid, you can even slide the whole table if you're feeling desperate and want to burn a warning.
It's a super physical game if you're taking risky shots and having to recover from bad situations constantly, and the pros make it look like they're barely nudging at all by taking safe shots and making minor corrections with nudges.
I've always wondered if we could get a "good enough" general model, then add plugins for shortcomings.
E.g., Can this model solve math problems? ~%50 of the time. Can this model identify math problems? ~99.9% of the time. Ok, then divert math questions to the math plugin and mathematical-problem-language-parser which has ~99.9% accuracy on supported math problems.
I know it's a stopgap, but it seems like it'd make these models super useful on certain tasks quicker.
Generally my advice when people ask me is as follows:
1. In the beginning, going to the gym is the hardest part. Incentive: if you go to the gym consistently for a while you are rewarded with no more post workout muscle soreness, and easy newbie gains.
2. Do compound lifts if you can (squat, bench, deadlift (warning deadlifts are not for everyone, and may not be all that beneficial), pullups/pulldowns.) Add a bit of weight or reps each week. Aim for 3-6 sets. No one will care if you start with an empty bar. If you add reps, if you get up to around 10-12, add weight instead. These number are flexible and there is no right answer.
3. For accessory exercises or things that target single muscles: try a bunch of stuff and try new stuff often. If you don't like it, don't do it. If you like it, work it into your routine. These are generally fun but unnecessary until you hit a plateau/wall in another lift and do some research on what you want to do to get past that plateau/wall.
4. Good form is more important than adding weight. Don't hurt yourself.
5/Bonus. Try watching some cringey YouTube fitness influencers and see if they're doing anything that looks fun and try that.
Also follow the golden rule: clean up and put your damn weights back.
A VR game where you take a snapshot or ghost of yourself performing some movement or throwing an item, which then repeats itself in the world. Then you can make more snapshots and string them together to create a Factorio-like game which uses the snapshot of those movements to assemble products.
E.g., ghost 1: pick up ore, throw ore -> ghost 2: catch ore, crush ore, throw crushed ore -> ghost 3: put ore into furnace -> ghost 4: pick up metal bar, throw metal bar, etc..
Then the player is running around building interactable buildings with produced resources and that oh so satisfying factory spaghetti starts forming.
I'm also interested in this topic, but can't find anything other than "Top 10 things you should STOP doing as a data engineer" etc. content-mill, clickbait on Medium and other sites.
Sounds pretty dismissive. AI and Big Data are buzzwords that shouldn't be used very often. Data Science is about creating solutions that are right for the size of your data, and the questions being asked of it.
A C++ program with a couple megs on the heap is appropriate, just as an ETL pipeline is appropriate for gigabytes to terabytes.
Why is everyone so concerned with $20/mo? If you're running a business, this should be the least of your concerns. Building on AWS means easy scaling for the future.
Who wants to redesign their entire project if it takes off?
There's also an entire community of people who play Table Top Role-Playing Games (TTRPGs) solo and use the outcomes of their play reports to blog or write fiction.
Also, the tooling around these games is very interesting if you want to build an app: Crafting calculator? Generative hexcrawl maps? Random tables? Statistics tools for dice rolls?