I think this perspective makes sense but a few points miss the mark in my opinion.. In this case, I learned a LOT about how to make an LLM operate outside of a purely virtual environment. In the meantime I also learned some robotics fundamentals that will assist me on my next part of the journey. The idea that LLMs are not a useful learning tool is something that I don't agree on, I can't imagine a better teaching tool than an LLM when used in the correct way.
I think my approach to learning most things I'm interested in is to set a basic goal and learn exactly enough info to get me to that goal. If the goal is too ambitious, I'll set a more reasonable goal and try again. If I'm able to achieve the goal, set a more ambitious goal and learn more during that process. Trying to learn everything about robotics is not a reasonable goal at this time so I'm doing my best to set myself up for success.
This is very useful info! I've added the additional 45 degree camera and so far it's seems like there is a regression on skill but I think it's because it wasn't available in the earlier parts of the training.
Can you elaborate on the calibration variables comment? This sounds useful but how would I apply these observations?
If the days of software engineering are over, then there is very little we can do and other jobs will quickly follow suit. I contend that this will not be the case but corporations are operating under the assumption that workers will be replaced quickly and cheaply. We largely missed the opportunity to organize during the covid pandemic when the balance of power swung towards workers and now it's time to remedy that mistake.
There is no attempt to hide it, corporations are rapidly attempting to replace technology workers of all skill levels as soon as possible. We need to protect ourselves as well as we can to secure our futures. Join up and let's act together to better our work lives.
this is incredible, I have been thinking about this exact project for quite some time but a little wary of which approach I might take. Thanks for posting this.
Don't give money to amazon that is better spent on an amazingly efficient postal service. Amazon is subsidized by imaginary money until they put all their competition out of business(including USPS).
I really can't tell to be honest, so if it's satire it's very good. If it's not then I don't really know what it's saying, humans are bad at stuff too? Many humans are not well educated and are not great conversationalists? Does this somehow make LLMs better in our perspective somehow?
Why does air-gapped environment require rolling your own CI/CD solution? Plenty of examples of air-gapped Jenkins and/or Argo Workflows. Was this just an educational exercise?
The big issue with LLMs is that they’re usually right — like 90% of the time — but that last 10% is tough to fix. A 10% failure rate might sound small, but at scale, it's significant — especially when it includes false positives. You end up either having to live with some bad results, build something to automatically catch mistakes, or have a person double-check everything if you want to bring that error rate down.