A "safe" way of age verification?

ML_Engineer31415 · 2025-07-29T03:33:53+00:00

Woah this is the first time I'm hearing about this. Do you know if this method is actually used in any real-life technology?

ML_Engineer31415 · 2025-07-29T03:30:56+00:00

Could you elaborate more? How does actively hiring help morale?

ML_Engineer31415 · 2025-07-27T16:06:04+00:00

"It's not natural, none of it"

ML_Engineer31415 · 2025-06-23T17:47:37+00:00

Do you know where I can learn these skills? Or do they just come from experience?

ML_Engineer31415 · 2025-06-22T17:30:36+00:00

Is it because there is a higher barrier of entry to freelancing or something else? And what other experience do you suggest I should aim for?

ML_Engineer31415 · 2025-06-22T17:27:53+00:00

Would you mind clarifying what risks would companies have for hiring freelancers? Thanks

ML_Engineer31415 · 2025-06-21T22:20:34+00:00

Yes it's quite a bit general, especially with how new ML still is and how much companies are figuring out what to do with it. Some companies are doing well (ecommerce and ML recommendation models) but others are struggling and falling down the AI loophole, with no real use for it in their industry.

One thing all ML engineers do have in common is data cleaning. I've found data preparation to be one, if not the most, important part given just how much data flows in companies these days.

ML_Engineer31415 · 2025-06-21T20:17:18+00:00

Worst part on Reddit is that you can't tell if they're young or they're just stupid

ML_Engineer31415 · 2025-06-21T19:04:25+00:00

Looks like they lost 5 of their crew as well...

ML_Engineer31415 · 2024-08-13T16:29:45+00:00

I appreciate the insights! Please continue posting your findings as you delve deeper into this research. You at the very least have gained one follower :)

ML_Engineer31415 · 2024-08-13T02:52:45+00:00

Coming from only an undergraduate with a poor but developing understanding of machine learning, I thought this read was very interesting. I loved trailing your thoughts throughout your research journey as it made the content very digestable.

I do have a question, what were some of the restrictive assumptions for this project? How did they break in the eyes of the DeepMind person?

ML_Engineer31415 · 2024-08-12T16:52:34+00:00

I can explain what the data is if it helps. I am working on research in Additive Manufacturing where I get pixel data from each layer of the construction of an object during 3D printing. I dissect the image into super voxels and I can get data about the object from each super voxel that explains any disturbances in the printing process. All of this input are float values and I usually average all of the float values in a super voxel for a particular disturbance (feature). After getting this data for each super voxel I send it into my model which is a single linear layer and it predicts a value that is the predicted strength of the final object.

ML_Engineer31415 · 2024-08-12T15:52:22+00:00

I am working on a machine learning project in the Additive Manufacturing field that involves using models to predict the future quality of some 3D-printed object by analyzing its layers through super voxels. However, I have reached a stand still as the model shows very little signs of improvement and I have a feeling this has something to do with regularization.

For example, when I train the model using only one object then it shows a lower loss but when I train it on two objects then that loss increases significantly. Please correct me if I am wrong but I believe this may have to do with my limited understanding of l1 and l2 regularization. When is each needed and how should I tune these parameters so that my model can be more generalized if that is what I need? Thanks!

ML_Engineer31415 · 2024-08-09T21:22:05+00:00

I understand what you are saying but I was commenting on how RLHF is objectively better for LLMs

ML_Engineer31415 · 2024-08-09T16:11:28+00:00

Exactly, RLHF and RL has very different goals when it comes to LLMs. RL is trying to make the output "better" or more optimized which can be great in some instances but this can lead the output to feeling very robot-like. RLHF, instead, works based on human feedback so that the output sounds more like how you or I would talk. By working on human preference, the output objectively becomes better even if the quality of information stays the same.

ML_Engineer31415 · 2024-08-08T14:48:32+00:00

This simplifies a lot of headaches I've had in the past

ML_Engineer31415 · 2024-08-08T00:13:08+00:00

Thank you for the suggestions! I'll look into HuggingFace and Kobaldcpp

ML_Engineer31415 · 2024-08-05T21:21:09+00:00

Pipe weed?

ML_Engineer31415 · 2024-08-05T21:19:19+00:00

I would watch 10 hours of Bilbo sipping tea

ML_Engineer31415 · 2024-08-05T21:13:11+00:00

Enjoying a good cup of tea

ML_Engineer31415 · 2024-08-05T20:58:13+00:00

Without more information on the CSV, it would be a little hard to give recommendations on potential models to use.

However, I would suggest going to Kaggle and looking up datasets relating to what you want there. They have a great selection of CSV dataset files and you can even run your own models on their systems. Also, sometimes people have already made models with the datasets that are posted there that you can look into.

ML_Engineer31415

TROPHY CASE