Edit: Is the below information incorrect or y’all just have a stick up your asses over LLMs?
Marie Curie’s notebooks are still radioactive due to the presence of radium-226, which has a half-life of about 1,600 years. To make her notebook non-radioactive or significantly reduce its radioactivity, the following methods could theoretically be used:
Chemical Removal or Neutralization:
Chemical Extraction: This involves using chemicals to extract the radioactive elements from the paper. This process would be complex and potentially damage the paper.
Neutralization: This would involve converting the radioactive materials into stable, non-radioactive elements. However, there are no practical methods currently available for neutralizing radium in situ.
Encapsulation:
Instead of making the notebook non-radioactive, it could be permanently encapsulated in a material that blocks radiation, such as lead-lined containers or specialized glass. This wouldn’t make the notebook safe to handle without protection, but it would contain the radiation.
Decay Time:
Given the long half-life of radium-226, waiting for the radioactivity to decay to safe levels is impractical since it would take thousands of years for the radioactivity to diminish significantly.
Advanced Radiation Mitigation Techniques:
There are experimental methods like targeted transmutation, where the radioactive elements are bombarded with particles to induce decay into stable elements. This is highly theoretical and not feasible with current technology for something as delicate as a notebook.
Practically, due to the historical and scientific value of Marie Curie’s notebooks, they are preserved and stored in controlled environments where they can be studied safely using appropriate radiation protection measures. The best approach currently is to handle and store them with care rather than attempting to decontaminate them.
I wonder what the issue is? Is it that is can provide wrong information?
Is it that you don’t see any legitimate use cases for them? As I work as a software developer and CoPilot in Visual Studio has saved us countless hours in writing boiler plate stuff and just solving problems in general.
Furthermore, the owner has created some pretty amazing tooling utilising LLMs and again, it saves us countless hours in the boring things. Like now if I make a new model in C#. We have something watching the code and that will use LLMs and some custom methods to scaffold changes to about 10-15 files and also create UI components in the client ready for us. All we need to do is update the schema doc for graphQL, run the migrations and update the DB. Then we are good to go. Saves about an hour every time a model is added or changed.
Content below provided by ChatGPT.
Edit: Is the below information incorrect or y’all just have a stick up your asses over LLMs?
Marie Curie’s notebooks are still radioactive due to the presence of radium-226, which has a half-life of about 1,600 years. To make her notebook non-radioactive or significantly reduce its radioactivity, the following methods could theoretically be used:
Chemical Removal or Neutralization:
Encapsulation:
Decay Time:
Advanced Radiation Mitigation Techniques:
Practically, due to the historical and scientific value of Marie Curie’s notebooks, they are preserved and stored in controlled environments where they can be studied safely using appropriate radiation protection measures. The best approach currently is to handle and store them with care rather than attempting to decontaminate them.
You should preface a comment if you used AI to write it
You’re right. I was being lazy, but I will edit to let people know.
There should be a rule to label ai output in posts and comments. Maybe spoiler tag the comments too, de-clutter a little bit.
Yes, everyone with some common sense hate LLM generated texts.
Care to elaborate?
I wonder what the issue is? Is it that is can provide wrong information?
Is it that you don’t see any legitimate use cases for them? As I work as a software developer and CoPilot in Visual Studio has saved us countless hours in writing boiler plate stuff and just solving problems in general.
Furthermore, the owner has created some pretty amazing tooling utilising LLMs and again, it saves us countless hours in the boring things. Like now if I make a new model in C#. We have something watching the code and that will use LLMs and some custom methods to scaffold changes to about 10-15 files and also create UI components in the client ready for us. All we need to do is update the schema doc for graphQL, run the migrations and update the DB. Then we are good to go. Saves about an hour every time a model is added or changed.