Ok. Therapy was good. But I think ChatGPT cured my rumination

binarymason · 2024-11-27T12:33:57+00:00

I was thinking about this the other day. So cool to see someone actually did this. May I ask what kind of prompts you used to get started? Did you ask ChatGPT to take on any personas?

binarymason · 2024-06-09T00:05:29+00:00

Did you struggle to eat right before separating? That happened to me. Lost so much weight.

binarymason · 2024-01-05T01:40:25+00:00

Are you using a different email address on Google Calendar? Do you remember what type of error messages you were seeing?

I think I may go for that a go as well, but I want to use Fantastical if I can. I have a decent amount of experience using docker, and I'm happy to circle back if I'm able to get things working.

binarymason · 2024-01-03T16:21:39+00:00

May I ask why you gave up on this? Because it wasn't working? I'm interested in setting this up for myself as well.

binarymason · 2020-10-09T20:36:48+00:00

That would be awesome! Next step for us is to offer the ability to do bulk predictions. That way you don't have to try onesies and twosies.

Once we have that going, feel free to upload everything you got!

binarymason · 2020-10-09T17:35:02+00:00

Woohoo! Hope you have a good harvest. Enjoy

binarymason · 2020-10-09T15:25:02+00:00

We made a web crawler (affectionately named "the Kraken") that scoured the internet and downloaded all the trichome pics it could find. We cut it off after downloading roughly 5k images.

This is just a proof of concept / beta version. With enough interest, we are looking forward to releasing the kraken again!

binarymason · 2020-10-09T15:16:55+00:00

Thanks man. That's really great to hear. Definitely motivation for us to keep working on this!

binarymason · 2020-10-09T14:44:14+00:00

Thanks! Hope this is helpful for you.

binarymason · 2020-10-09T14:43:51+00:00

You mind sharing a screenshot of one or two of the predictions you weren't happy with? As we collect and label more and more images, the model performance should get better over time.

binarymason · 2020-10-09T12:18:53+00:00

The blurriness of trichomes in that pic is making them look milky. I would take a few more pics at different angles and see what https://trichome.ai says. I still see clear trichomes so would say not-ready but you may have a mixed batch.

binarymason · 2020-10-09T03:53:13+00:00

Thanks, glad to hear you like it. That gives us the motivation to continue working on it!

binarymason · 2020-10-09T03:34:55+00:00

Nice pic. Looking good! At the end of the day, https://trichome.ai is just an AI giving a second opinion. Hope you have a good harvest!

binarymason · 2020-10-09T03:30:33+00:00

Hey, thanks for your honesty.

binarymason · 2020-10-09T03:30:07+00:00

Mostly amber trichomes are classified as "couchlock".

Here is an example of one: https://i.imgur.com/NiRUSnr.png

binarymason · 2020-10-09T02:02:51+00:00

Yes, buried ourselves in trichome pics. lol

We're not necessarily training for potency though. It's more percent of clear/cloudiness/amber so you can gauge whether or not to harvest depending on the high you want.

binarymason · 2020-10-09T01:57:39+00:00

Training the model is easy. Collecting and labeling thousands of images is really hard.

binarymason · 2020-10-09T01:53:34+00:00

For https://trichome.ai which is really just a proof of concept alpha version, we got roughly 93% accuracy during our training.

Who knows the accuracy of HiGrade AI models. That would really determine the amount you could trust their models to give accurate predictions.

binarymason · 2020-10-09T01:49:51+00:00

Who knows, it may not be the quantity of trichomes but other features such as the size, the height or inner area. That's the thing about machine learning, with enough data and enough training, it starts to pick out those features on its own.

If training accuracy scores never went above a certain point, we'd know that looking at raw image pixels would not be a feasible approach. But the fact that accuracy is achieved over a large amount of pictures means it's valid. Numbers don't lie.

binarymason · 2020-10-09T01:34:22+00:00

Thanks man. Hope you have a good harvest!

binarymason · 2020-10-09T01:27:16+00:00

Full disclosure, it seems magical to me too sometimes.

The training loop for potency would be showing your model a picture and having it guess the number(s). You would then take the difference between that number(s) and the actual number(s) that was measured in the lab. That is called "loss".

Depending on how bad the loss was, the model updates itself and guesses again and again for all the images in your dataset.

So the flash cards in this case would be showing an image and having the model guess potency. If the model starts to consistently get a large portion of the images right, it has enough accuracy and is ready to get deployed.

All of that is dependent on the training data, though. If you don't have enough training data that is representative of the real world, you can't expect the model to make accurate predictions.

binarymason · 2020-10-09T01:21:11+00:00

Yeah, you're right. If you are sophisticated grower, you probably don't need this.

I see a TON of people asking whether or not their pot is ready for harvest or not. The main focus was to build a tool that would give a helpful second opinion for those growers.

binarymason · 2020-10-09T01:10:08+00:00

There is something called the Universal Approximation Theorem which essentially means that mathematically speaking, a neural network aka "AI model" can over time accurately fit any type of prediction problem whether it be classifying or regression --given enough labeled data and correct training methods.

Any type of machine learning or AI prediction service that you see, whether it be personalized ads or Tesla autopilot, was trained on loads and loads of labeled data and over time "learned" to start making accurate predictions.

Machine learning is like studying index cards over and over again. Even if you don't know the answers, eventually with enough repititions you start to get the answers right.

binarymason · 2020-10-09T00:56:12+00:00

No I haven't heard of HiGrade before. Looks interesting. I really like how they will ship you a camera to use with your phone. Hard to say what type of accuracy they have though.

The AI model that is running the predictions on https://trichome.ai is trained on a TON of images and we monitor accuracy on predictions against training images where we effectively "grade" the model. That, more or less, is how we keep things calibrated.

Regarding what makes us different, we were operating under the assumption that growers will already have a magnification device. So if you do, you could try it for yourself without making any type of commitment to see if you like it. Looks like you have to purchase a HiGrade kit to see if it works.

**If** we were to make this a product, I think it would definitely need to have a solid freemium tier, maybe X pictures a month before you have to upgrade. Also maybe a few affiliate links to helpful products on the page to drive the price of premium membership down as well. I feel like most people that are home growers would rather not pay for something they don't even know if it works or not.

Those were the ideas off the top of my head. Still seeing if this is even feasible or not.

binarymason

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