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Do You guys use discord? I have a data set that could be used with ai that could possibly reverse engineer the prime # used in some lotteries RNG program to help with future predictions.
OK, I'm pausing @1:30 because the guy on the left is laughing while the guy on the right is trying not to laugh while he's reading the necessary disclaimer: both of these jokers know that stupid people are going to ignore the disclaimer and listen intently for lottery secrets on how to win the lottery. And. And. And? And they grow their viewership of garbage videos like this on the backs of stupid people resulting in free RU-vid revenue because stupid people are greedy regardless of any disclaimer you read to them.
Well Deb, neither George or I are developers, but someone in our audience might be able to speak intelligently to your question. It might be good to post your question in a developer's forum. I am sure there are many developers who can give you better feedback.
Here is what GTP said: In the provided predictions, while I factored in historical seed performance, recent team performance, and potential for upsets based on historical trends, I didn't explicitly mention considering tournament experience. Tournament experience, such as past performances in the NCAA tournament, the team's history of advancing in March Madness, and the coaching staff's experience in navigating high-pressure tournament games, can significantly impact a team's chances of success. I then asked it to consider it and got this... Taking tournament experience into account significantly for predicting the National Championship game requires a focus on teams with a history of deep runs in the NCAA tournament, experienced coaching staffs, and players who have performed under the high-pressure conditions of March Madness before. Teams with such backgrounds tend to handle the pressure better, make fewer mistakes in crucial moments, and exploit their experience against less experienced opponents. Considering Tournament Experience for the Championship Prediction: Adjusted Championship Prediction: Given the emphasis on tournament experience, let's consider a scenario where Duke and North Carolina-two of the most storied programs in college basketball history, with deep tournament runs and experienced coaching staffs-make it to the final game. Both teams have players who have been part of the tournament before and understand the pressure of such a high-stakes game. Duke vs. North Carolina: This is a classic rivalry with both teams having extensive tournament experience. Assuming both teams have navigated their brackets successfully, this game would not only draw on their season's performances but heavily on their historical success and experience in handling the pressure of big games. Prediction: In a game that would likely be closely contested, with both teams leveraging their depth of experience and talent, North Carolina could be slightly favored due to their recent success in the tournament, including a championship win in 2017 and a runner-up finish in 2022. Let's predict a tight game: North Carolina: 78 Duke: 75 This prediction assumes that both teams' experience in dealing with the pressure of the tournament shines through, with North Carolina's slightly more recent success in the tournament giving them the edge in this hypothetical matchup. It's important to note, though, that actual game outcomes can be influenced by numerous unpredictable factors, including individual player performances, injuries, and the inherent variability of sports competitions.
Grok is different . Each game is a statistical anomaly given participants are mostly different as are time and place . It's data set is unknown perhaps if parameters were limited to kenpom or Oliver 4 factors results documented would vary or USE OUIJA BOARD . Chances of perfect bracket is 1 in 9.2 quintillion. Even that's a stretch for AI s Swamis
@@UNMUTED_Santi UK 2 3s 2 1s in ff. Nigls 49 straight record I think is safe for awhile. Formulaicly probably better to have a recency data bias rather than use historical weighting . For that I think Kerry's Ken pom is on the mark with limits and bounds . Adjem adjO adjD . Winning also being an atomic habit means SOS may not be as valuable to a mcneese sporting just 3 losses a vet coach and a lights out 3 point % . They don't know they're NET bad. Replicants. Others " Tilt " the matrix with renewed health or continued bad health KANSAS .
@@UNMUTED_Santi the Kerry Ken pom formula also interesting but neither printout actual scores. But I noticed in your chat gpt few scores are blowouts most fallen in a narrow 6 point range if I correctly assessed . Where I find Kerry's data from Ken pom a little squishy is the 113 adjO . I know like uva and San diego pushed that # down . But being adj D crews they're more aberrations. Frankly I think 118 or 120 as you go deeper in tourney is better and AdjD might also have slippage slightly 96 ?
@@UNMUTED_Santi UK by Grok WHY? WITH ALL THEIR YOUTHFUL INDISCRETIONS ? WITHOUT KNOWING GROKS MODEL I MIGHT SURMISE MUSKS TEAM IS USING OLIVERS 4 FACTORS AND OR KEN POM ? WHY ? 41 % 3 POINT SHOOTING WOULD PUT UK ATOP OLIVERS WEIGHTED VALUE OF 4 FACTORS . AND 122 ADJO is ranked about 5th nationally. Plus their path to FF is less difficult . But you know trying to figure out how ENIGMA worked was flowers/ Turing guess work. Maybe LLM NOT SO MUCH .
@@UNMUTED_Santi if your unfamiliar with olivers 4 factors go to basketball reference nba finals any there you will find out how 4 factors dominance led to victories. It's sort of a reverse indicator there but surely if a teams performs better at 3 of 4 they'll win.
So I did create a group with the bracket, but YT will not let me post the link or mention the site. But those of you who have your brackets, simply search for our group called Tech UNMUTED. Have fun with this!
This has huge potential. Remote assistance in real time, monitoring of progress and execution from head office, recording of site communications, noise cancelling earbuds for noisy environments etc. Tighten up dudes, the boss is listening and recording. :)
🎯 Key Takeaways for quick navigation: 00:43 *🎰 The podcast discusses using ChatGPT-4 for data analytics, specifically analyzing lottery numbers from New York.* 01:11 *📉 Past lottery trends don't predict future outcomes, emphasizing responsible gambling and not solely relying on data analytics for lottery decisions.* 02:12 *📊 The podcast demonstrates using ChatGPT-4's Advanced Data Analytics feature, showcasing its capabilities with the lottery data.* 03:08 *🔍 The dataset used for analysis is from Megamillions, spanning from 2002 to 2020, demonstrating the complexity of lottery data analytics.* 04:36 *🤖 ChatGPT-4 uses natural language processing to comprehend and analyze data, showcasing the capabilities of AI in real-time.* 06:14 *📉 ChatGPT-4 identifies patterns in lottery numbers, such as frequency distributions and correlations, aiding in data interpretation.* 10:46 *🔢 Analysis reveals a pivot in lottery number patterns around 2020, highlighting the dynamic nature of data trends.* 13:03 *📈 ChatGPT-4 provides insights into "hot" and "cold" numbers, demonstrating its ability to analyze and categorize data trends.* 17:19 *📰 ChatGPT-4 can generate press release summaries based on data analysis, showcasing its potential for practical applications beyond raw data interpretation.* 19:12 *🔄 The effectiveness of ChatGPT-4's analysis is influenced by the specificity and clarity of user prompts, highlighting the importance of guiding AI tools effectively.* 22:48 *🔄 Effective prompts yield detailed responses from ChatGPT-4, which not only analyzes data but also explains its approach, enhancing transparency and understanding.* 23:01 *📝 AI comprehends prompts effectively, even understanding numbered lists as bullets, showcasing its ability to interpret human instructions.* 23:26 *📊 ChatGPT-4 can generate charts based on data analysis, facilitating visualization for presentations or reports.* 24:56 *🎲 Analyzing historical lottery data with AI can provide a scientific approach to gambling, potentially shortening the process of number selection.* 25:56 *🔄 ChatGPT-4 can calculate odds based on data sets, offering insights into the probability of winning, albeit with some inaccuracies in data interpretation.* 26:52 *💬 Feedback is welcomed for future podcast topics, with a focus on showcasing AI advancements through practical demonstrations of data analysis.* Made with HARPA AI
I think a significant input that isn't factor in is that both the Mega Millions & Powerball are played with physical rubber balls. These balls are not randomized before entering the chamber and are not mixed for very long. This might be the reason why so many numbers are drawn so close together. Just an observation: only started playing this year.
I like all that that you guys are doing can you try to see if you could do for New York to pick three and the winning four numbers with the AI and see what the results you got with that since it’s a lot less numbers thank you
For everyone - there are no patterns. There are over 300,000,000 combinations that can come up. All this tells you is when random numbers look like a pattern due to clustering. We are talking about 104 draws per year for the first 30 years or so of powerball before going to 3 per week. In other words, 3,000 drawings out of over 300,000,000 combinations. Look at it like how they presented it in the beginning - this is a great exercise is watching how AI can work with large data-sets.
Do you have data set access for quad linear and celestial spherical plot that we can bump data against or feed data thru a formula I have been working on with Chat GPT? As follows: The strong force, also known as the strong nuclear force, is one of the fundamental forces of nature that acts between subatomic particles called quarks. The mathematical formulation of the strong force is described by quantum chromodynamics (QCD), which is a theory within the framework of quantum field theory. The formula for the strong force interaction between quarks is given by: F_s = (α_s / r^2) * (λ_i * λ_j / 4π) I have also explored limited with GPT to include terrestrial frames of decay to offset passage of time and gravity: mass displacement due to gravity in a spherical object, we can consider a gravitational potential equation. The gravitational potential at a distance from the center of a spherically symmetric mass distribution is given by:
too bad that the the numbers that get drawn are dependent on all the numbers that have been selected. algorithms are surely at play. I know a few long time keno players who say that as soon as the games became fully electronic, they began to win less and less as time went on and many dont even play anymore because of it... i'ts rigged for the house/state, but atleast it helps pay for our parks right.
4 Months later and now if you ask those same prompts I receive an error analyzing when ask to "What are the most likely numbers to be drawn next? Give me three ways you would come up with this."
I study the big games and smaller games. It’s random alright. This is right up my alley as I’ve been searching for how to better structure prompts along with analysis of the big games. This is a great vid.
it was nice to see chat actually give a set of numbers "for fun", With the last video on lottery you did I was going to suggest to tell the gpt to treat the numbers as a mensa test and ask gpt to guess what the next pattern would be. "Fun thing" to do is to look at the lottery numbers since your data set and see if those numbers the gpt came up with "for fun" actually got picked. In case you mentioned some of this I was a bit distracted from the video (not going to replay it) .
I though about that, and see if it still think it is random data. We've got a couple other podcasts in the work and will definitely look at some other variations.
@@georgeschoenstein There are a few parameters that are missing which keep people from using ai to predict the numbers. i would like to test them. if you know any programmers that can manipulate what chatgtp produces please let me know and we could finish this project.
Take a look at this video we just posted. Very similar to our approach with this one, but at least the paid version of ChatGPT no longer required you to enable the plug-in. In the new video I go right into asking it to analyze the attachment. ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-rcJ4ELhnmGQ.htmlsi=pjnr3Dp6Bty8g5aH
open ai is the mpst controlled and cherrypicked data sets. they are useless. dont use them. dont give your money to them if you actually want the future of ai to be open.
As a beginning Data Analyst this should excite me because it's a new tool to make the job easier, but it scares me. I can see three possible negative outcomes. 1. AI makes me lazy at data analysis because it can easily filter datasets and present visualizations 2. It could be a justification for bad leadership to reduce the number of data analysts needed. 3. It could justify replacing data analysts with AI prompt specialists. Humans are tool makers. But, like the atomic bomb, once we get to these society changing level tools, before unleashing them on the world at large, maybe some thought could be put into how we can cope with the changes that they will bring. it's oxymoronic. How can humans be so intelligent that they are ignorant?
We did a video a couple of month ago looking at whether AI tools should be regulated. Our overall perspective is that AI will increase productivity, but it will require an adjustment in work style/approach for some roles, and needs to be carefully thought before implementing. ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-ZXB4CTi3rUk.htmlsi=Im-4FQ9mElBEcYNP
I don't say they are, but if they want to build up the jack pot if they use different range of seed numbers for the quick pick random number generator and the actual Power Ball numbers this would make a quick pick chances of winning even smaller. I wonder what percent of winners are quick picks and how many winners pick their own.
