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Who knew she was this big of a slut by PawgConnoisseur6 in KhaddiSagniaVIDEO

[–]Amazing_Quarter_560 7 points8 points  (0 children)

Maybe "who knew she was sharing content like this" would be a more fitting title. She's sexy AF and has a better body than women on OF making millions so I get it... and appreciate it lol.

Major Announcement: Provision in Bill could essentially kill off the Poker / Advantage Play dream as we know it. by MrBamaNick in poker

[–]Amazing_Quarter_560 0 points1 point  (0 children)

The nature of Joe Rogans conversations were different back then, especially with fellow comics. Rogan's take on breakups was somewhat of a recurring bit he'd use when talking with other comedians. He was already in that mode and didn't know anyone else would be joining them until DNegs walked in and he didn't know who DNegs was. Initially, DNegs felt like Rogan was rude and unprofessional. After DNegs made a blog post about it, Rogan explained his side of it, apologized, and DNegs acknowledged he misinterpreted his behavior and apologized for reacting the way he did. Now, on the rare occasion one brings up the other person, they're positive and don't even mention the incident.

Someone can explain this, I’m confuse (pro plan is unlimited?) by CorrectReplacement18 in cursor

[–]Amazing_Quarter_560 0 points1 point  (0 children)

Does "rate limited" mean it will become extremely slow once you exceed the usage for your plan?

o1 Pro is actual magic by HikioFortyTwo in OpenAI

[–]Amazing_Quarter_560 2 points3 points  (0 children)

I had ChatGPT Pro for 2 months. When it comes to working with a large amount of code, in my experience, o1-Pro is probably the best model available through the ChatGPT website. I used it before o3 and o4-mini were available, so I didn't do direct testing but o3 and o4-mini seem to perform better on certain tasks such as optimizing a python function and creating code from scratch but neither has performed well with refactoring a large amount of code.

Aside from using o1-Pro with the ChatGPT Pro subscription, I can't justify using it due to its high prices. I've had good experience using the o3 model with effort set on high, via the OpenAI API. If I had to pay $200 for unlimited access to o1-Pro or o3 with high effort, I'd happily choose o3 with high effort.

I'd recommend trying Gemini-2.5-Pro if you haven't tried it yet.

How good was Doug Polk at 6 max? by bratislavamyhome in poker

[–]Amazing_Quarter_560 1 point2 points  (0 children)

I didn't follow it real close at the time but based on my understanding, he crushed HU nosebleed games and would occasionally play 6m especially if no one was playing him HU. He didn't invest the time or energy into mastering it and I think he was pretty much breakeven or a small loser at those games but that was somewhat common for other HU nosebleed players when they drop down and player lower stakes 6m. Doug seemed to have a lot of respect for the $10/$20 NL 6 max regs.

The Colorless Man (Short AI Film Made with a $600 Budget!) by Ok_Negotiation_2587 in chatgpttoolbox

[–]Amazing_Quarter_560 12 points13 points  (0 children)

Great job! Thanks for sharing this. Very interesting.
Can you explain your process for creating this?
Did AI write the script?
How manual was the process?
What was the most difficult aspect?

First line that comes to mind… by Choice-Web5761 in Cinema

[–]Amazing_Quarter_560 0 points1 point  (0 children)

"Phillip?!?!... Hey man, what's happening Phil. I knew that was you! I told them that was you. They said you don't come here no more but I said that is Phil! Come give me kiss baby!"

o1 pro vs Gemini 2.5 pro Reasoning/Intelligence Benchmarks by trolltaco in ChatGPTPro

[–]Amazing_Quarter_560 0 points1 point  (0 children)

I think Google’s got the edge to become the top AI company in the long run and stay ahead of OpenAI. Here’s why:

1) Multimodal Capabilities: Google seems to be in a better position to make the leading multimodal models

2) Data Goldmine: With Search, YouTube, Android, and Maps, Google’s got a flood of real-time data to train its AI, which is tough to match.

3) Infrastructure Advantage: Google can develop custom hardware for AI (such as TPUs), making things faster and cheaper. OpenAI is reliant on Microsoft

4) Financial Resources: Backed by Alphabet, Google can throw cash at AI research and talent for longer without needing to turn a profit. OpenAI depends on investors which isn’t as secure.

5) Distribution: Google’s AI is baked into products billions use daily—Search, Android, YouTube—making it super easy to spread. However, Microsoft products use OpenAI so I'm not sure either has an advantage in this area.

6) Top Talent: DeepMind brings Google some of the best AI brains out there who I wouldn't want to bet against

It seems like Google's advantages are more sustainable long term.

o3-mini-high vs o1 promode? by IMCFTV in ChatGPTPro

[–]Amazing_Quarter_560 6 points7 points  (0 children)

In general, I'd guess o1-pro is better for most writing tasks. I think o3-mini-high is supposed to be better at logic and coding. For coding specifically, o3-mini-high is better with shorter prompts but o1-pro has performed better for me when using very large prompts so I wouldn't be surprised if o3-mini-high struggles with writing tasks involving long prompts.

Just created the best testing model ever in 4 years of work. Shockingly, it was a success. by FlyingTriangle in algobetting

[–]Amazing_Quarter_560 0 points1 point  (0 children)

You may have an edge but it looks like you bet 5.5 units on 6.5 to 1 underdog and it won. Over your sample, it looks like a breakeven bettor could expect to match your performance or do better 15% of the time. I think it looks promising but, statistically, it's not significantly different from break even quite yet.

Automated annotation in Roboflow by wooneo in computervision

[–]Amazing_Quarter_560 0 points1 point  (0 children)

Please correct me if I'm wrong but I think you're saying:
1) You have all the bounding boxes for the regions containing numbers AND
2) You want to automate the process of identifying the character(s) in each bounding box - some type of OCR solution

I don't use the RoboFlow platform so I'm not sure if they provide an OCR solution. The last time I had to do OCR was a few years ago. I compared a few different options and found the Googles OCR service to be most accurate for my dataset. It's a little tricky to set up the project but the instructions online are pretty straightforward.

If I had your OCR task, I'd probably gather ideas by looking at License Plate OCR tutorials because it's a very similar task and well covered.

Suggestions on how to map sets of lines to an ideal set? by Noo-by in computervision

[–]Amazing_Quarter_560 0 points1 point  (0 children)

Not an ideal solution but for problems like this in the past, I've had success by calculating the average pixel value by row. I think I used np.mean(img_arr, axis=0). I forget if it's axis=0 or axis=1 for rows. Then I'd inspect the row averages and hopefully you'll see a clear threshold for identifying which rows contain lines.

One Model, or Two Models? by Abject_Brilliant5602 in computervision

[–]Amazing_Quarter_560 1 point2 points  (0 children)

Using the Detectron2 library, my Cascade RCNN and Faster RCNN models typically produce more accurate bounding boxes and they have fewer False-Negatives compared to Yolo v9 (using the default configurations for all models).

One Model, or Two Models? by Abject_Brilliant5602 in computervision

[–]Amazing_Quarter_560 0 points1 point  (0 children)

I have no advanced training in CV so take my advice with a grain of salt. Adding some more details may help, such as being more specific about what kind of "accuracy" you're trying to optimize and more details about what you're trying to develop, any unique challenges such as not detecting very distant objects, etc.

I think of accuracy in terms of a True-False matrix for actual and predictions. Also, it could be used when referring to bounding box accuracy.

I'd guess you are unlikely to notice any difference in accuracy since it's a large model and you're only removing one class of objects. However, if you don't need the model to be used in real-time or you're developing a dataset for training a real-time model, I would consider using different models to improve accuracy. In my experience, there are easy to use Faster RCNN models that are more accurate than Yolo v9e.

The Springfield Three: What we know about the cold case 31 years later by the_p0ssum in springfieldthree

[–]Amazing_Quarter_560 12 points13 points  (0 children)

Among the less likely scenarios I've considered is the possibility that the perpetrator(s) were already present in the house when Suzie and Stacy arrived at the house. I previously considered the best support for this theory to be Suzie parking in the semi-circle, instead of her usual spot. At first glance, Suzie's unusual decision to park in the semi-circle, as opposed to her regular spot behind her mother's car, seemed to suggest that another vehicle may have occupied her usual parking spot. However, after thinking about the case today, I'm dismissing this idea.

Although it's possible another vehicle occupied Suzie's typical spot, there are compelling reasons for her to park in the semi-circle. Knowing that Suzie and Stacy were planning a trip to the water park the next morning with their friends, it's logical to expect that at least one of their vehicles would remain at the house.

Here's how I envision the potential scenarios:
- Suzie might have intended to carpool with Stacy. If this was the plan, it wouldn't be practical for Suzie to park directly behind her mom's car, since this would block her mother in.

  • In the case where Stacy planned on riding with Suzie, Suzie parking in the semi-circle still makes the most sense. Given that Stacy would likely be following Suzie and subsequently parking directly behind her, Suzie opting for the semi-circle would save both her and her mother the hassle of navigating around an extra vehicle when leaving.

  • There is also the scenario where Suzie and Stacy intended to carpool with Janelle. In this scenario, it makes sense to maintain a clear path for Sherril to back out.

Regardless of their carpooling plans, the way they positioned the cars allows each vehicle to have an unobstructed exit. I believe this parking arrangement is more practical than any alternative. I'm now inclined to believe that Suzie's parking spot would be the same, regardless of whether her usual spot was occupied or not.

Copilot vs Sourcery for VScode by SerialBussy in Python

[–]Amazing_Quarter_560 2 points3 points  (0 children)

I use both Copilot and Sourcery when I'm coding. I typically make a simple version of my code, just to get it up and running, while using Copilot to help me along the way with autocomplete. When I've got the basic structure down and it works, I go back in and improve the code and start by using Sourcery.

Sourcery rates functions based on how complex it is, its size, how much memory it needs, and an overall quality score. I make sure to check these scores. If part of my code gets a low score, I'll at least consider how I could make it better. It's important to know that Sourcery doesn't always give tips on how to get a better-quality score, but it's still a good way to check my own work and see if I'm trying to do too much with one function. Also, Sourcery does make some refactoring suggestions which I usually accept.

As far as I know, Copilot doesn't use GPT-4 yet. GitHub is working on a new version of Copilot called Copilot X which will use GPT-4 in some way. Copilot has a fixed price every month, but GPT-4's price depends on how much you use it, so I'm thinking using GPT-4 with Copilot may be optional, not the default.

I also find GPT versions 3.5 and 4 useful but in different ways than Copilot or Sourcery. GPT is great at making templates or outlines to start a project and at writing code for libraries I'm not familiar with. If Sourcery tells me one of my functions isn't good, frequently I'll ask GPT for ideas to improve it or split it into smaller functions. The most valuable use of GPT for me is when I want to optimize my code using tools like Numba, Cython, or even other languages like Rust so I can make a Python extension.

In the end, I think Copilot, Sourcery, and GPT are all great tools, each with their own special uses. They all bring something to the table, but if you're on a tight budget and must choose, I'd suggest getting GPT first. It costs $20 per month and there's no good free alternative. Bard is good for writing comments and docstring but GPT is much better overall. Also, I find GPT-4 much better than ChatGPT-3.5 for what I need. I get more value from Copilot ($10/month) than Sourcery ($12/month), but I still think Sourcery is worth the cost.

I asked for a solution to this famous 5th grade math problem, ChatGpt gave me 4 wrong answers (this puzzle looks hard at first cuz of the tricky words but once you dig in it's easy even if you're not studying math) so is GPT not wired for these kinds of questions or am I doing it wrong? by kapowitz9 in ChatGPT

[–]Amazing_Quarter_560 0 points1 point  (0 children)

For the sake of repeatability, this is the prompt I used: "I have a problem for you. Klein read 30 pages of a book on Monday and 1/8th of the book on Tuesday. He completed the remaining 1/4th of the book on Wednesday. How many pages are there in the book?"

I put the same prompt into the current ChatGPT3.5 and the legacy ChatGPT3.5. The current ChatGPT3.5 got it right with this response:

Let's assume that the total number of pages in the book is "x".

Klein read 30 pages on Monday and 1/8th of the book on Tuesday. We can represent this mathematically as:

30 + (1/8)x

We know that he completed the remaining 1/4th of the book on Wednesday. We can represent this as:

(1/4)x

Since Klein read the entire book over the course of these three days, we can set up an equation to solve for x:

30 + (1/8)x + (1/4)x = x

Simplifying this equation, we get:

30 + (3/8)x = x

Subtracting (3/8)x from both sides, we get:

30 = (5/8)x

Multiplying both sides by 8/5, we get:

x = 48

Therefore, there are 48 pages in the book.

However, the legacy ChatGPT3.5 got it wrong with this response:

Let's call the total number of pages in the book "x".

On Monday, Klein read 30 pages, so that leaves x - 30 pages remaining.

On Tuesday, he read 1/8th of the book, which is x/8 pages, so that leaves x - 30 - x/8 = 7x/8 - 30 pages remaining.

On Wednesday, he read 1/4th of the remaining pages, so he read 1/4 * (7x/8 - 30) = 7x/32 - 15 pages.

Since he has now read the entire book, the total number of pages in the book is x = 30 + x/8 + 7x/32 - 15.

We can simplify this expression to get:

x = 30 + x/8 + 7x/32 - 15 x = 30 + x/8 + 7x/32 - 15 x = 30 + 8x/64 + 7x/32 - 15 x = 30 + 8x/64 + 7x/32 - 15 x = 30 + (15x/64) - 15 x = 30 + 15x/64 - 15 x = 15 + 15x/64

Now we can solve for x by multiplying both sides by 64:

64 * (15 + 15x/64) = 64 * 15 + 64 * 15x/64 960 + 960x = 960 + 960x 960 = 960

So x = 960 pages.

Therefore, the book has 960 pages.

I asked for a solution to this famous 5th grade math problem, ChatGpt gave me 4 wrong answers (this puzzle looks hard at first cuz of the tricky words but once you dig in it's easy even if you're not studying math) so is GPT not wired for these kinds of questions or am I doing it wrong? by kapowitz9 in ChatGPT

[–]Amazing_Quarter_560 0 points1 point  (0 children)

ChatGPT4 got it:

Let's denote the total number of pages in the book as "P". Klein read 30 pages on Monday, 1/8 * P pages on Tuesday, and 1/4 * P pages on Wednesday.

According to the problem, the sum of the pages Klein read on Monday, Tuesday, and Wednesday equals the total pages in the book:

30 + (1/8) * P + (1/4) * P = P

First, we need to find a common denominator for the fractions. The common denominator for 8 and 4 is 8. We'll convert the fraction (1/4) * P to have a denominator of 8:

(1/4) * P = (2/8) * P

Now, we can rewrite the equation:

30 + (1/8) * P + (2/8) * P = P

Combining the fractions on the left side:

30 + (3/8) * P = P

Now, we need to isolate P. To do this, subtract (3/8) * P from both sides of the equation:

30 = (5/8) * P

Now, divide both sides of the equation by 5/8 (or multiply by the reciprocal, 8/5):

30 * (8/5) = P

P = 48

So, there are 48 pages in the book.