Chatgpt - Seriously good potential (or just some Internet fun)

[RxR]

I just uploaded a few of my working papers to deepseek and queried them using its reasoning engine. The results were pretty impressive - eg. inferring and giving reasonably accurate 'how to' procedures when these were only implied in the texts.

There was a semi-hallucination / overgreedy inference though. Which brings me to the point: using a reasoning engine to output descriptions and how-to's (for example) can indicate where the original text needs some sharpening or emphasis added (to prevent the hallucination). So they have a use as a prepublication editing aid.

 

[D.P.]

You can get output that rivals ChatGPT, and it can run locally on a 6GB laptop GPU - that isn't a big deal to you?

Deepseek r1 is a 671 billion parameter model. It isn't small by any means. The largest model from Meta is only 450bn.


R1 is.not going to run on your laptop, i'm not sure where you get that idea.

 

[adam cool dude]

Surely this is the call for us as a country to ditch America and cuddle up with the Chinese.

I think it is pretty obvious that China are the way forward in the next 30 years.

 

[darkgen]

Deepseek r1 is a 671 billion parameter model. It isn't small by any means. The largest model from Meta is only 450bn.


R1 is.not going to run on your laptop, i'm not sure where you get that idea.

You can run the distilled models with varying degrees of success and accuracy on a moderately powered nvidia GPU PC. The higher the vram plus system ram will increase your success. I've been playing with the 14b models via ollama and open webui with a 3080 (10gb) + 16gb of system ram. It's not fast but usable and I've been suitable impressed with various maths. logic and coding queries.

The reasoning and thinking output is rather interesting.

 

[pre]

Probably not quite the situation but...

 

[arknor]

chatgpt is so stupid...

been trying to solve the same problem for hours, chatgpt goes around in circles the whole time, makes stuff up on it's own, you tell it to read a link and it just ignores all info on there...

and t hen suddenly the penny drops....

If you're working with video instead of images, the prediction format and processing need adjustments.

​

• Label Studio sends video URLs, not images.
• You need to extract frames from the video, run YOLO on them, and return a prediction for each frame.
• The response format must match what Label Studio expects for video annotations.

I told it in the first place it was a video..... yet again making assumptions instead of actually listening to instructions.

I hope deep whatever kills of these crap american AIs, it seems to have a memory span of about 10 minutes too..

it's like its senile or something... it can lose track of what your doing, or info you gave it is totally irrelevant.

chatgpt always knows better than you do.

 

[Hagar]

Surely the logical conclusion of all the claims of distillation and training of various AI engines is that there will not be one best answer but a variety of samie's all producing similar if not identical output.

There can only be one correct solution to most problems.

 

[sityeuropa]

chatgpt is so stupid...

been trying to solve the same problem for hours, chatgpt goes around in circles the whole time, makes stuff up on it's own, you tell it to read a link and it just ignores all info on there...

and t hen suddenly the penny drops....



I told it in the first place it was a video..... yet again making assumptions instead of actually listening to instructions.

I hope deep whatever kills of these crap american AIs, it seems to have a memory span of about 10 minutes too..

it's like its senile or something... it can lose track of what your doing, or info you gave it is totally irrelevant.

chatgpt always knows better than you do.

What chatgpt model are you using exactly?

 

[NickK]

Yeah I don't think people understand this - there's lots of handwaving about censorship but it's not really sunk in that this is an open model, it doesn't have to be hosted in China, it doesn't require a censorship API, other third parties will host it (it's not just China vs do it yourself). Lots of buzz surrounding AI but plenty of people misunderstand it.

If the enc to weights diffused to text then the pretrained weights will recreated problematic text (ie bad code). Ie the weight drives the output.

You can remove the RAGs, APIs and everything else but the weight will cause a problem.

yes you can remove everything and use a MoE with opensourced code with no chinese connections or data but your need to dump the weights.

 

[arknor]

What chatgpt model are you using exactly?

gpt4o on the plus plan.

actually I found a really easy way to do what I wanted when I stopped being lazy and it meant editing one whole file.
then replacing a model that already existed.



this is what I was trying to do

Label Studio Documentation — Write your own ML backend

Set up your machine learning model to output and consume predictions in your data science and data labeling projects.

labelstud.io

ChatGPT4o literally found it impossible to write me a script compatible with that backend.

it couldn't figure out how to reply to predict() calls from label-studio properly.


I linked chatgpt the example yolo

label-studio-ml-backend/label_studio_ml/examples/yolo at master · HumanSignal/label-studio-ml-backend

Configs and boilerplates for Label Studio's Machine Learning backend - HumanSignal/label-studio-ml-backend

github.com

I told chagpt

label-studio-ml-backend/label_studio_ml/examples/yolo/control_models/video_rectangle.py at master · HumanSignal/label-studio-ml-backend

Configs and boilerplates for Label Studio's Machine Learning backend - HumanSignal/label-studio-ml-backend

github.com

seemed to translate yolo formar > studio label json

I linked chatgpt https://github.com/HumanSignal/labe...bel_studio_ml/examples/yolo/README_DEVELOP.md

I even linked it the studio label sdk at one point....


surely it should have been able to figure it out?

I ended up editing video_rectangle.py so it points to
model_path = "best.pt"

my own model..



chatgpt couldn't figure out how to export with interpolated frames bounding boxes either.
I googled and figured out how to do it my self... I think I just copy and pasted the code after googling too...

from label_studio_sdk import Client
# Connect to Label Studio
ls = Client(url='http://localhost:8080', api_key='MYKEY')
# Get your project
project = ls.get_project(1)
# Create an export snapshot with keyframe interpolation enabled
export_result = project.export_snapshot_create(
title='Export with Interpolated Keyframes',
interpolate_key_frames=True
)
# Get the export ID
export_id = export_result['id']
# Wait for the export to complete (you may need to implement a waiting mechanism)
# Download the export
status, filename = project.export_snapshot_download(
export_id, export_type='YOLOv8', path='.'
)

the one thing chatgpt did manage after dozens of attempts was how to convert that json snapshot to yolo format. (export to yolo_obb seems bugged with video files)
finally after many days I have label studio set up with a custom trained model that can pre-annotate, and I can easily retrain.


sometimes itr's brilliant but then its like it secretly switches to a dumb model and literally becomes senile.

I literally ask if it remembers what we ared oing? how can it ask for debug output then when it;s provided, it acts like your starting a whole new topic?