discipline == execution
ideas are worthless, its all about the execution
1,475 karma · joined July 22, 2017
discipline == execution
ideas are worthless, its all about the execution
1. How things are made: This is your programming language/core concepts/DSA/Problem solving. Don't start with two languages. Start with 1 along with design/psds/algo.
2. Why things are made: These are the tools like nginx/jenkins/aws/terraform etc. Understand their purpose. Think of how you would have solved the problem (#1), and then go in depth one by one into their detail.
If you are not using what you learn regularly, then you will quite easily forget it. So mix 1 and 2 to keep things interesting.
As for blogging, start taking private notes first. Eventually you will have a note detailed enough for someone else to read. Then you start to blog.
A person who does not know how to code without access to AI tools means they will consistently push bugs generated by AI, affecting the teams productivity, if any.
I tried setting up the filter, Frets 0-3 and string 1/2/3, but either I am doing something wrong or it doesnt respect the filter, the next note would still go outside the filter range.
Have bookmarked it.
VLC ~22 years
There is nothing to try out, it sends me to a calendly link, why ask for feedback ?
- Let a new user try the experience without the signup/sign-in flow (single try ? i know it gets hard keeping track to avoid abuse but the signin/signup flow is sort of long)
- Put a template text in the main text-area instead of "Write something"
- Don't persist the pop-up modals (eg choosing the sentiment) when user clicks somewhere else
- Change the color of the "Save" button, right now it looks like disabled.
- On clicking the "Save" button, user needs to indicated what needs to be done. Something like a workflow is needed, otherwise this feels like a simple chatgpt "improve this" prompt response. I feel lost after clicking the save button. (show a saved list ?)One challenge is that AI research is a rapidly evolving field, and new developments can quickly outpace existing regulations. It can be difficult to anticipate the risks and implications of new AI technologies before they are widely deployed.
Another challenge is that AI research is often conducted by private companies or organizations, and they may prioritize commercial interests over ethical considerations. Regulating AI research could limit innovation and economic growth, which is a concern for many policymakers.
Furthermore, there is a lack of consensus on what exactly should be regulated in AI research. Different stakeholders have different opinions on what types of AI applications are ethical and safe, and what types of regulations are appropriate.
Its kind of like rubber ducking with a fairly smart duck. Plus the variety of topic one can ask it is infinite (as opposed to Wikipedia)
It also responds in a very humanly way (tell it you are feeling anxiety for example)
In the last 10 or maybe even 20 years it's one of the few new tech that has had me stunned.
Sometimes I make it create poems too, very simple ones on things very contextual.
Its not for generating visual structure, but just defining the structure with the constraints like you mentioned
[1] https://www.ribbonfarm.com/2009/10/07/the-gervais-principle-...