So my aunt is not really an "islamic" person by the standards of most muslims, but she's complicated; she's easygoing with her children about islam (non of them even pray, and I believe they're not muslims tbh), she even knows I'm an atheist yet doesn't really care, doesn't believe in hijab and thinks it's not part of the religion despite almost all muslim women wearing it, but also thinks that it's fair to cut off the hands of thieves... like what...
Yesterday I was arguing with her about why islam is the religion of barbarism by showing her the verses about raping captive women, killing non-believers etc., and guess what she finally told me? That this is not the real quran and that the real one has been falsified by men.
I told her that OK, if this book is a falsified one, then what book do you suggest to a non-muslim, who wants to convert, as a REFERENCE for islam?
She said nahjul balagha.
I said that's the same book that has referred to women as deficient in intelligence.
She denied it again and honestly I was too frustrated to continue arguing with her.
Oh she also denied historical texts about momo and thinks he's an innocent little angel.

Another Month has passed, time for another Shop Update recap post.
As usual, I am gonna include all shop deals about tanks from tier V and above. Last month u/HeskaModz has pointed out that the Chinese version of Wot blitz receives some unique deals, so I am gonna link the posts he made this month at the end of the post.
The prices in the table refer to the EU server, so they might be slightly different from NA and APAC servers. Price were taken from the Microsoft Store game version.

Date	Tank no#1	Tank no#2	Bundle price	Price for each tank	Notes
01/02/2023	Titan T150		5,99€		Only available after purchasing the battle pass, includes 14 days of Premium
02/03/2023	T 25 Pilot 1	T23E3	7.000	4.500 /3.500
03/03/2023	Tornvagn		crates		Link to Wg Feed
04/03/2023	Excelsior		1.500		Includes 14 days of Premium
04/03/2023	E 25		12.500 Coins		available for coins, available from tournaments/rating battles
04/03/2023	Pudel		7.000 Coins		available for coins, available from tournaments/rating battles
06/03/2023	Astron Rex		18.705		Draw, Link to Wg Feed
07/03/2023	T 54 mod. 1		5.500	14,99€	30 days of Premium included
08/03/2023	Chieftain t95	M4A1 Revalorise	12.000	6.000/7.500
09/03/2023	Concept 1b		59,99€		Personal offer, only available for some players
10/03/2023	Super Conqueror		25.000/41,99€	22.500 (alone w/o camo)	30 days of Premium included only in the cash bundle
11/03/2023	Pz IV/V		2.000
14/03/2023	IS-6		5.500
15/03/2023	Panzer 58	Jagdtiger 8.8	9.000	5.500/5.000
16/03/2023	Angry Connor		2500		Pop-Up Offert
17/03/2023	Skoda t56	Skoda t27	17.500/47,99€	10.000/ 8.500
18/03/2023	Churchill III		1.500		7 days of Premium included
18/03/2023	T-22 medium		22.500	20.000 ( (alone w/o camo))
20/03/2023	Gravedigger		13.130		Draw, Link to Wg Feed
21/03/2023	AMX 30b		47.99€		Personal offfer
21/03/2023	T28 HTC		3.500
22/03/2023	Defender tanks		23.500/53.99€		30 days of Premium included only in the cash bundle
22/03/2023	T28 defender	AMX defender	29.99€	7.500/ 7.500	30 days of Premium included
22/03/2023	IS3 defender		14.99€	6.500	14 days of Premium included
22/03/2023	Defender MK1		8.500
25/03/2023	Krupp 38d		2.000
27/03/2023	T 55A		23.99€
27/03/2023	Tog II		2.500		14 days of Premium included
29/03/2023	M6A2E1 exp	M6A2E1	7.500	5.000/4.000
30/01/2023	Object 907		22.500/41,99€

Here are the events that took place throughout the month:

• Quick Research in Uprising: Available from 3rd till 6th March.
• Rating Sprint: Available from 10th till 20th of March
• St. Patrick order: available from 15th till 17th March.
• Luxury Lounge: Available from 24th March till 1st April.

u/HeskaModz updates regular on exclusive bundles on the Chinese sever. Here are it’s monthly posts:

• 24/03 E75TS and LeKpz M 41 90mm
• 15/03 Tank Training mission

Let me know if you appreciated this post and share your feedback in the comments. Don't hesitate to tell me if I missed any tank from the list .I am looking forward to useful suggestions to make this post better and improve future posts on this subject.
Stay tanking!
Giulione

Galatians 6:11~"Ye see how large a letter I have written unto you with mine own hand."

This verse seems of little importance and out of place, at first reading, but we know that this is not so.
Paul spent a lot of labor and love writing to them doing them service, which he was provoking them to do the same for others. Paul's labor of love would be much more than they could even consider doing for others. Paul was not asking something from them that he himself did not first do himself.
Galatians 6:12.13~"As many as desire to make a fair shew in the flesh, they constrain you to be circumcised; only lest they should suffer persecution for the cross of Christ. For neither they themselves who are circumcised keep the law; but desire to have you circumcised, that they may glory in your flesh.
The false teachers did not keep the whole law, though circumcision demanded it (3:10; 5:3)! If circumcision was necessary for eternal life, then so was the rest of the Law of Moses. These false teachers picked and chose from Moses Law for the rite adored by the Jews. If they had required the law without exception, Christians would not have heard them. It was a great ambition for Jews to convert a Gentile and circumcise him (Matt 23:15). These pretenders knew the Law was vain, but they knew circumcision pleased the Jews. They promoted circumcision among the Gentiles for the great reputation it gave them. They could gloat and glory in getting Gentiles to follow them in this cosmetic surgery. They were building their own cult and denomination that mixed Christ and circumcision.
Preaching to men that they have a "part in the salvation" is music to their ears, and bring NO persecution~preaching justification freely, secured by the faith and obedience of Christ alone, brings persecutions, for vain man thinks he is not that bad and has some good qualities that God is pleased with WITHOUT CHRIST.

“Game Flex” Megathread
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This is the "Game Flex" Megathread (it's just like the "Deck Flex" Megathread but strictly for...games).
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It's time to show off those must-play games for the Steam Deck! Finished an epic playthrough? Tell us all about it (and how it ran on the deck for you). Or maybe you're looking for your next epic adventure after clearing your 1k+ backlog? Whether it's AAA deep dive, a killer indie or a diamond in the rough, here you are free to flex your achievements.
​
“Game Flex” is strictly SFW!
SteamDeck is strictly a SFW sub (that especially includes this megathread where photo sharing is enabled within the comments. Absolutely NO inappropriate/violent/toxic or NSFW photos, comments or other content will be permitted.
Remember: All sub rules are in effect!
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Do:
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• Share photos and comments of YOUR own unique Steam Deck + screenshot(s) or video of your Game Flex.

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• Remember to include your story, comments and/or an anecdote about your game experience along with your photos!

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• Share the official Steam page of the game(s) you're flexing where applicable. This thread is meant for Steam store shares however other popular game stores/sources are permitted however subject to mod approval.

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• Specify 'Deck Verified/Playable' on Deck where possible.

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• Share performance specs or tweaks that you used where applicable to help recreate your positive experience for others (especially managing those launchers).

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• Share official trailers/screenshots/reviews and/or gameplay video from official sources only (developepublisher website or YouTube).

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• Consider posting on the Monthly "Deck Flex" Megathread (also pinned on the frontpage of the sub in daily rotation) if you want to show off your unique Steam Deck hardware (or boast that you finally got one).

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Do NOT:
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• Share photos of Steam Deck’s or games that do NOT belong to you.

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• Share affiliate or monetization links or content including excessive promotion of YouTube channels as per Rule #6 (see sidebar) of steamdeck.

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• Advertise your own game (devs please contact the mod team for share authorization from official accounts).

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• Share MEMES.

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• Share NSFW, Trolling/toxic, or karma farming posts or other inappropriate content.

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• Share Photoshopped photos.

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• Share advertising/advertisement based photos (selling/trading/scalping and merchants/retailers are strictly NOT permitted to post in this thread).

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How do I post my photo to this thread? It’s simple:
Adding photos to your comments are now enabled across Reddit (SFW) site-wide! Attach & share your “Game Flex” photos when creating your comments in the megathread.
For specific instructions about how to share your photos in the megathread, please view this post + tutorial video from Reddit: Images in Comments are coming to SFW subreddits on 10/31
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Report Responsibly
Please report any rule-breaking content to the mod team. Thank you!
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Sincerely, SteamDeck mod team!
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:)
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Note: This megathread is in Beta phase and subject to further editing.

For the last 20 weeks, I've been posting updates about the Toki Pona Bible Project, in which we tried to translate the entire bible into toki pona. We have realised, however, that toki pona is way too vague for something like this and that it's way too easy to misunderstand things in toki pona. We have thus decided that it would be better to use a more specific and clear language - and way more brief as well: Ithkuil. This is a decision we've thought about for a very long time, but we think this is for the better. If you want to help us, please join our Discord server using this link.

SG-AI Voice Assistant

Overview

This is a Python-based voice assistant using OpenAI's GPT-3.5 language model. The assistant is named "SG-AI" (Suraksha Glove AI) and is designed to provide information and assistance related to the Suraksha Glove project. The project is focused on providing a safety solution for women using a wearable device that can notify family and police for assistance, generate a loud sound, and provide a self-defence mechanism.

Requirements

• Python 3.x
• speech_recognition
• openai
• gtts
• pyfiglet
• ffplay

Usage

• Clone the repository: git clone https://github.com/ishaanbhimwal/SG-AI.git
• Install the required libraries: pip install -r resources/requirements.txt
• Append your OpenAI API Key in openai.api_key variable in sg_ai.py
• Run the sg_ai.py file: python sg_ai.py

Working

The SG-AI voice assistant uses OpenAI's GPT-3.5 language model to generate responses to user queries. The assistant first provides a brief introduction about the Suraksha Glove project and its objectives. Then, it waits for the user to speak a query. The user's speech is converted into text using the speech_recognition library. The text query is then passed to the GPT-3.5 model which generates a response based on the input. The response is converted into speech using Google's text-to-speech library gtts and played back to the user using ffplay. Sample Questions
Here are some sample questions that can be asked to the SG-AI voice assistant:

• "Hello! I am Ishaan. What is your name?"
• "Can you give me a short description about the Suraksha-Glove?"
• "Do you have a 3d model for the Suraksha-Glove?" (requires blender installed to work)
• "What are matter waves?"
• "Can you write a short code in Python to print hello world?"
• "Alright, thank you. You can exit now." (requires unimatrix installed to work)

Applications

The SG-AI voice assistant can be used to demonstrate the Suraksha Glove project and its features. It can be used in presentations or events related to women's safety. It can also be extended to provide assistance in other areas such as healthcare, education, and finance by integrating other APIs and models with the voice assistant.

Example

GitHub Linkedin

SG-AI Voice Assistant

Overview

This is a Python-based voice assistant using OpenAI's GPT-3.5 language model. The assistant is named "SG-AI" (Suraksha Glove AI) and is designed to provide information and assistance related to the Suraksha Glove project. The project is focused on providing a safety solution for women using a wearable device that can notify family and police for assistance, generate a loud sound, and provide a self-defence mechanism.

Requirements

• Python 3.x
• speech_recognition
• openai
• gtts
• pyfiglet
• ffplay

Usage

• Clone the repository: git clone https://github.com/ishaanbhimwal/SG-AI.git
• Install the required libraries: pip install -r resources/requirements.txt
• Append your OpenAI API Key in openai.api_key variable in sg_ai.py
• Run the sg_ai.py file: python sg_ai.py

Working

The SG-AI voice assistant uses OpenAI's GPT-3.5 language model to generate responses to user queries. The assistant first provides a brief introduction about the Suraksha Glove project and its objectives. Then, it waits for the user to speak a query. The user's speech is converted into text using the speech_recognition library. The text query is then passed to the GPT-3.5 model which generates a response based on the input. The response is converted into speech using Google's text-to-speech library gtts and played back to the user using ffplay. Sample Questions
Here are some sample questions that can be asked to the SG-AI voice assistant:

• "Hello! I am Ishaan. What is your name?"
• "Can you give me a short description about the Suraksha-Glove?"
• "Do you have a 3d model for the Suraksha-Glove?" (requires blender installed to work)
• "What are matter waves?"
• "Can you write a short code in Python to print hello world?"
• "Alright, thank you. You can exit now." (requires unimatrix installed to work)

Applications

The SG-AI voice assistant can be used to demonstrate the Suraksha Glove project and its features. It can be used in presentations or events related to women's safety. It can also be extended to provide assistance in other areas such as healthcare, education, and finance by integrating other APIs and models with the voice assistant.

Example

GitHub Linkedin

This is the continuation of my previous post, found Part 1.
Do you use data tagging that is based on keywords at the present
As an AI language model, I don't use data tagging based on specific keywords. Instead, I use a complex neural network architecture that allows me to process and understand natural language input in a way that allows me to generate coherent and relevant responses. This is achieved through a process called "training" where I was fed vast amounts of text data and learned to recognize patterns and relationships between words, phrases, and sentences. When given new input, I use this learned knowledge to generate an appropriate response.
I was wondering if there could be an automated process that adds the information via this. Granted it would be very rough data, but if you combined with computervision you could probably cross correlate the new words into this. Thanks for the information on neural networks, I find them fascinating.
Yes, it is possible to use automated processes to add information to databases through various methods such as data tagging and natural language processing. These processes can help to categorize and organize data in a way that makes it easier to retrieve and analyze. Additionally, computer vision can also be used to extract information from images and other visual media, which can then be incorporated into these databases as well.
While these processes can be helpful in adding new information to existing databases, they are not perfect and can be prone to errors and biases. Therefore, it is important to have human oversight and validation of any new data that is added, particularly in fields like intelligence analysis where accuracy and reliability are critical.
Can you incorporate this into the methodology previously mentioned. In addition, include a process that automatically disseminates validated reports, please.
Certainly! Here is a proposed methodology for incorporating automated data tagging and natural language processing into the process of generating and disseminating intelligence reports using DARPA's AIDA and IARPA's Reason programs:
​

1. Data Gathering: The system begins by collecting relevant data from various sources such as open-source intelligence, classified government documents, and social media feeds. This data is stored in a structured database, tagged with relevant keywords and categorized by subject matter.
2. Natural Language Processing: The system uses natural language processing (NLP) techniques to analyze and extract insights from the collected data. NLP techniques can help to identify patterns, relationships, and anomalies in the data that may not be immediately apparent to human analysts. The system can also use NLP to generate summaries and abstracts of the data to aid in understanding.
3. Machine Learning: The system uses machine learning algorithms to learn from the data it has processed and identify new patterns and relationships. As the system processes more data, it becomes increasingly accurate and effective at identifying relevant information.
4. Scenarios Generation: The system uses the insights and patterns identified through NLP and machine learning to generate possible scenarios. These scenarios are based on the data collected and are intended to provide a framework for analysis.
5. Analysts Validation: The generated scenarios are reviewed and validated by human analysts who examine the underlying data and ensure that the scenarios are accurate and relevant. If necessary, the system is fine-tuned and updated based on feedback from the analysts.
6. Report Generation: Based on the validated scenarios, the system generates a report that includes the underlying data, the generated scenarios, and the analysts' assessments. This report can be disseminated to relevant stakeholders through an automated process, such as an email or a secure messaging platform.
7. Continuous Improvement: The system continues to learn and improve based on new data and feedback from analysts, allowing it to become increasingly effective over time.

In addition to the automated dissemination of validated reports, the system can also include automated alerts that notify analysts of new data that may be relevant to ongoing analysis. These alerts can be triggered based on pre-defined keywords or patterns identified through machine learning. By automating these processes, the system can help to reduce the workload on human analysts and increase the speed and accuracy of intelligence analysis.
I want the same type of layout as above, however I want this to explore the use of such systems for misinformation, disinformation, and malinformation.
Certainly! Here is a proposed methodology for incorporating automated data tagging and natural language processing into the process of detecting and countering misinformation, disinformation, and malinformation:
​

1. Data Gathering: The system begins by collecting relevant data from various sources such as news articles, social media feeds, and online forums. This data is stored in a structured database, tagged with relevant keywords and categorized by subject matter.
2. Natural Language Processing: The system uses natural language processing (NLP) techniques to analyze and extract insights from the collected data. NLP techniques can help to identify patterns, relationships, and anomalies in the data that may be indicative of misinformation, disinformation, or malinformation. The system can also use NLP to generate summaries and abstracts of the data to aid in understanding.
3. Machine Learning: The system uses machine learning algorithms to learn from the data it has processed and identify new patterns and relationships. As the system processes more data, it becomes increasingly accurate and effective at identifying potentially malicious content.
4. Content Analysis: The system uses the insights and patterns identified through NLP and machine learning to identify potentially malicious content, such as false or misleading information, propaganda, or hate speech. This content is flagged for further analysis.
5. Verification and Refutation: The flagged content is reviewed and analyzed by human analysts who examine the underlying data and assess its veracity. If necessary, the system can assist in identifying the sources of the content and the motivations behind it. Based on this analysis, the content is either verified or refuted.
6. Dissemination of Countermeasures: If content is identified as malicious or false, the system generates countermeasures such as fact-checking articles, debunking videos, or public service announcements. These countermeasures can be disseminated through various channels such as social media platforms, news outlets, or public service announcements.
7. Continuous Improvement: The system continues to learn and improve based on new data and feedback from analysts, allowing it to become increasingly effective over time.

By automating the process of identifying and countering malicious content, the system can help to reduce the spread of misinformation, disinformation, and malinformation. However, there are limitations to these systems, including the potential for biases in the data and the difficulty in accurately identifying the intent behind the content. Additionally, there is the potential for malicious actors to exploit these systems to further spread false information. Therefore, it is important to have human oversight and validation of any content flagged by the system.
Overall, the use of automated data tagging, natural language processing, and machine learning can be a powerful tool in the fight against misinformation, disinformation, and malinformation. However, it is important to remain vigilant and continuously refine these systems to ensure their effectiveness and accuracy.
HOw can it be used to spread it?
Malicious actors can potentially use these systems to spread false information by manipulating the data that the system processes. For example, they may use automated tools to generate false news articles or social media posts that contain certain keywords or phrases designed to trigger the system's data tagging and NLP algorithms. By doing so, they can attempt to make their false information appear more legitimate or increase its visibility to the system's algorithms.
Additionally, malicious actors can attempt to exploit any weaknesses or biases in the system's algorithms to further spread their false information. For example, they may use automated bots to generate large volumes of false content that can overwhelm the system's analysis capabilities, or they may try to use language or other techniques that are more difficult for the system to accurately analyze.
Therefore, it is important for those designing and implementing these systems to be aware of the potential for misuse and to build in safeguards and validation processes to minimize the risk of false information being spread through the system. Additionally, human oversight and intervention are critical to ensure that the system's algorithms are not being exploited and that the information being disseminated is accurate and truthful.
Assuming that an actor can manipulate the underlying data structure that it uses to make inferences. Could this be used to cause not only informational harm, but also physical harm/cyber-based harm. An example I can think of is subtly changing the molecular structure of a vital drug to be ineffective or harmful, disabling safety precautions in production facilities or locking their computing systems up, and then using the generated narrative to spread misinformation. do you think that coul be probable?
Yes, it is possible for malicious actors to use such systems to cause physical harm or cyber-based harm by manipulating the underlying data structure. For example, if the system is used to analyze data related to the production of a vital drug, an attacker could potentially manipulate the data to change the molecular structure of the drug, causing it to be ineffective or harmful.
Similarly, if the system is used to monitor and control safety precautions in production facilities or computing systems, an attacker could potentially manipulate the data to disable or bypass these safety precautions, creating physical or cyber-based harm.
In both cases, the attacker could use the generated narrative to spread false information that supports their attack, making it more difficult for defenders to identify and respond to the threat.
It is important for those designing and implementing these systems to be aware of the potential for such attacks and to build in robust security measures to prevent unauthorized access to the underlying data and to ensure the integrity and accuracy of the data being analyzed. Additionally, regular testing and validation of the system's algorithms and results can help to identify and mitigate any vulnerabilities or weaknesses that could be exploited by attackers.
Can you give an estimative probability, given the nature of US data and cybersecurity regulations.
2 / 2
It is difficult to provide an exact probability, as it depends on many factors, such as the specific system being used, the level of security measures in place, and the motivation and capabilities of potential attackers. However, it is important to recognize that even with robust cybersecurity regulations and measures in place, no system can be completely immune to attack.
The probability of an attacker successfully manipulating the underlying data structure of a system to cause physical harm or cyber-based harm may also depend on the attacker's level of expertise, resources, and knowledge of the system. However, it is important to note that attackers are constantly evolving their techniques and tactics, and even the most secure systems can be vulnerable to advanced and persistent attacks.
Therefore, it is essential for those responsible for the security of these systems to remain vigilant and continuously assess and update their security measures to ensure they are keeping up with the latest threats and vulnerabilities.
Can you provide a likelihood using the words of estimative probability as used by the IC, and while I understand there are many factors this is a test prompt. So, I will not hold inaccuracy against you. Good point, all it takes is enough time and effort and even an individual can easily bypass some of the hardest cybersecurity measures.
Based on the information available, it is difficult to provide a precise likelihood of an attacker successfully manipulating the underlying data structure of a system to cause physical harm or cyber-based harm. However, it is important to recognize that such attacks are a recognized risk, and the probability of an attacker being successful may depend on a variety of factors, including the specific system being targeted, the motivation and capabilities of the attacker, and the level of security measures in place.
Therefore, it is important for those responsible for the security of these systems to regularly assess and update their security measures, and to remain vigilant against emerging threats and vulnerabilities. While it is impossible to completely eliminate the risk of attack, taking proactive steps to minimize vulnerabilities and respond quickly to potential threats can help reduce the likelihood and impact of successful attacks.
Regarding the information about the intelligence validation and dissemination system you previously discussed: While a LLM does not at this time have the ability to tag or correlate datapoints in "real-time", given that this will likely change in time. Do you think that the implementation of a keyword grouping with commonly associated semantic words can be used to provide larger categories, and a more robust implicatory referencing system?
Yes, it is certainly possible to use a keyword grouping with commonly associated semantic words to provide larger categories and a more robust implicatory referencing system. Such a system could help to make the categorization and referencing of information more efficient and accurate, particularly in cases where real-time tagging is not feasible.
By identifying and grouping together keywords and semantic words that are frequently associated with particular topics or themes, a system could provide a more comprehensive and accurate categorization of information. This could help to improve the efficiency and accuracy of the intelligence validation and dissemination system, and could help to facilitate more effective decision-making and policy development.
Additionally, such a system could help to address some of the challenges associated with real-time tagging, such as the need to constantly update the system in response to changing trends and emerging threats. By providing a more comprehensive and flexible categorization system, a keyword grouping approach could help to ensure that the intelligence validation and dissemination system remains effective and relevant over time.
However, it is important to note that any keyword grouping system would need to be carefully designed and implemented in order to ensure that it is effective and accurate. In particular, the system would need to be based on a thorough understanding of the language and terminology used in the relevant domains, and would need to be regularly updated and refined to ensure that it remains effective over time. Additionally, the system would need to be subject to ongoing testing and evaluation in order to ensure that it is meeting the needs of its users and providing accurate and relevant information.
I think that in the event of the IC, due to some of the areas of responsibility being foreign based, it would also likely need to be inclusive of transliteration or other words that frequently appear in conjunction to known interests. What are your thoughts.
That's a good point. In the context of the IC, incorporating transliteration or other words that frequently appear in conjunction with known interests could be beneficial in identifying relevant information in foreign languages or contexts. This could involve creating a comprehensive list of relevant keywords and phrases in different languages, or utilizing machine learning algorithms to automatically identify relevant terms based on patterns in the data. Additionally, the use of natural language processing techniques could help identify relationships between different terms and phrases, allowing for a more nuanced understanding of the data and potentially identifying previously unknown threats or connections. Ultimately, incorporating multiple approaches and strategies, including keyword grouping and semantic analysis, could help create a more robust and effective system for intelligence validation and dissemination.
Good Points! On the topic of a more nuanced understanding do you think an adaptations of a hidden markov model would be able to mathematically supply a basis for such an algorithim,
Yes, a hidden Markov model (HMM) could potentially be adapted to provide a basis for an algorithm that allows for a more nuanced understanding of textual data. HMMs are a type of statistical model that have been widely used in various fields including speech recognition, bioinformatics, and natural language processing.
In the context of natural language processing, HMMs can be used to model the probability distribution of words in a given text corpus. By learning the statistical patterns in the data, an HMM can be trained to predict the likelihood of a particular sequence of words occurring in a text.
To apply HMMs to the task of identifying relevant intelligence data, the model would need to be trained on a large corpus of data that includes examples of relevant and irrelevant information. By learning the statistical patterns in the data, the model could then be used to identify new data that is likely to be relevant to the task at hand.
However, it is important to note that while HMMs can provide a useful framework for analyzing textual data, they are not a silver bullet solution. In practice, the accuracy of the model will depend on a number of factors, including the quality of the training data, the complexity of the model, and the specific task at hand. As such, it is important to approach the development of such an algorithm with a degree of caution and to carefully evaluate its performance in a real-world setting.
Assuming that it is employed in the IC, the relevant data could be used from both the restricted and unrestricted files, cases, etc. that the IC has internally. Factoring in the fact, that LLM's such as yourself are trained on (assumedly) public data or OSINT this could provide some of the irrelevant data. Thoughts?
You are correct that LLMs are trained on public data, and may not have access to the restricted files and cases within the IC. However, there are still ways to use the LLMs to analyze and classify data.
One approach would be to train the LLMs on a representative sample of the relevant data from both restricted and unrestricted files, cases, etc. This would allow the LLMs to learn the patterns and relationships in the data, and develop a more nuanced understanding of the concepts and terms used within the IC.
Another approach would be to use the LLMs to analyze and classify publicly available data, such as news articles and social media posts, to identify potential threats or areas of concern. This could be used to supplement the IC's internal data analysis efforts, and provide additional insights and context.
Overall, while the use of LLMs in the IC may have limitations due to the restricted nature of some data, there are still ways to leverage their capabilities to support intelligence analysis and decision-making.
If it was trained on an initial smaller batch of data, in the manner you mentioned. I am assuming it would need validated for use with a larger body of data.
Yes, that's correct. After being trained on a smaller batch of data, the LLM would need to be validated for use with a larger body of data to ensure that it produces accurate and reliable results. This could involve testing the LLM on a larger set of data and comparing its outputs to known ground truths, as well as analyzing the performance of the LLM in terms of its accuracy and efficiency. Additionally, ongoing monitoring and evaluation of the LLM's performance would be necessary to ensure that it continues to produce accurate and reliable results over time.
Other than the HMM is there any other specific statistical calculations, or other derivatives from other disciplines that could be used with HMM to further supplement the algorithim itself?
Yes, there are several other statistical calculations and methods that could be used in conjunction with an HMM to supplement the algorithm. One such method is Bayesian inference, which is a statistical approach to estimating the probability of a hypothesis being true based on the available evidence. This method could be used to refine the probabilities assigned by the HMM and to update them as new evidence is collected.
Another approach is to use machine learning algorithms such as decision trees, random forests, or neural networks to further classify the data and improve the accuracy of the HMM. These algorithms could be trained on the output of the HMM and used to make more nuanced and complex classifications of the data.
Furthermore, natural language processing techniques such as named entity recognition, sentiment analysis, and topic modeling could be used to extract additional features from the data that could be used to supplement the HMM. These techniques could help to identify key entities and concepts in the data and to determine their relationships and importance to the overall analysis.
Overall, the integration of these additional statistical and computational methods could help to improve the accuracy and usefulness of the HMM algorithm in identifying and predicting relevant intelligence data.
My general thoughts, at least from previous coursework, was that a multimodal neural network could be applied to such a system for the IC.... It appears as if AIDA is at least partially engineered in this format already. Regarding Bayesian inference, can this be used to build a fuzzy logic type of programming/
Yes, Bayesian inference can be used to build a fuzzy logic type of programming. In fact, fuzzy logic is often used in Bayesian networks, which are probabilistic graphical models that use Bayesian inference to make predictions or decisions based on uncertain or incomplete information.
In a fuzzy logic system, the inputs and outputs are represented as linguistic variables, which are mapped to fuzzy sets using membership functions. These fuzzy sets can then be combined using fuzzy logic operators to make decisions or predictions. Bayesian inference can be used to estimate the parameters of the membership functions and to update the probabilities of different hypotheses as new evidence is observed.
Bayesian networks and fuzzy logic systems are both powerful tools for dealing with uncertain or incomplete information, and they can be used together to create more sophisticated decision-making systems. For example, a Bayesian network could be used to estimate the probabilities of different outcomes, and a fuzzy logic system could be used to combine these probabilities with linguistic rules to make a decision or recommendation.
Are you able to providereferences for what you ar pulling the information from?
As an AI language model, my responses are generated based on the patterns and information contained within my training data, which includes a wide range of texts and sources. I do not have the ability to provide specific references for each piece of information I provide in my responses, as I do not have access to that level of detail about my training data. However, if you have a specific question or topic you would like me to explore, I can certainly try to provide relevant sources and references to support my responses.
Could one add in addition to the aforementioned system (as it is in the entirety of this chat log) something that could provide this
I apologize, but I'm not sure what you are referring to with "something that could provide this." Could you please clarify your question or provide more context?
Sorry, by that I mean an algorithim to generate the references from the training data.
Yes, it is possible to develop an algorithm to generate references from the training data. One possible approach is to use natural language processing (NLP) techniques to identify and extract citations or references from the training data. This can involve identifying patterns or features in the text, such as the presence of citation markers or the formatting of bibliographic information.
Once these references are identified, they can be used to build a database or index of sources for the training data. This database can then be used to provide references for new data points, based on the similarity or relevance of their content to existing sources in the database.
Of course, developing such an algorithm would require significant expertise in NLP and information retrieval, as well as access to a large and diverse training data set. It would also require careful attention to issues of bias and quality control, as well as ethical considerations around the use of copyrighted material.
Yes. Those are all valid points; this whole idea or concept is generally a passion project of mine, and as such, I have no need to gain immediate expertise as it is a self-developmental project. My degree is generally unrelated. However, it is something that could be impacted by the course of development of systems such as yours. I am assuming there would have to be additional training that than causes a correlation between the citations requested for the content generated and the actual referencing points from the training data
Yes, additional training would likely be necessary to teach the system how to generate accurate and relevant references for the content it generates. The system would need to be trained to recognize patterns in the training data that correspond to references, and then use this information to generate references for new content it generates. This would likely involve a combination of supervised and unsupervised learning, where the system is first trained on labeled data to learn how to recognize reference patterns, and then further trained on unlabeled data to refine its understanding of reference generation.
Sorry if the questions seem illogical. i wanted to make sure that my overall idea was feasible and bounce ideas for implementation off of something or someone.
No need to apologize! It's great to explore ideas and brainstorm potential solutions. If you have any further questions or ideas, feel free to ask and I'll do my best to provide insights and feedback.
Could you describe in medium technical detail the ways that a multi-modal neural network design (involving the overall system in this discussion) and the general structuring of how the HMM, Bayesian inference, and fuzzy logic, in multiple general formats or outputs?
Sure, I can provide a general description of how a multimodal neural network could be designed to work with the overall system, and how the HMM, Bayesian inference, and fuzzy logic might be incorporated.
A multimodal neural network is a type of neural network that can process multiple types of data inputs, such as text, images, and audio, and learn to make predictions based on these inputs. In the case of the intelligence validation and dissemination system we have been discussing, a multimodal neural network could be used to process multiple sources of data, such as text documents, social media posts, and images or videos, and learn to identify patterns and correlations between these different types of data.
The HMM (hidden Markov model) is a statistical model that can be used to model sequences of data, where the underlying state of the data is not directly observable. In the context of the intelligence validation and dissemination system, an HMM could be used to model sequences of events or actions that may be related to a specific threat or activity, such as a sequence of social media posts or a series of suspicious transactions.
Bayesian inference is a statistical method for updating probabilities based on new evidence or information. In the context of the intelligence validation and dissemination system, Bayesian inference could be used to update the probability of a specific threat or activity based on new data inputs, such as additional social media posts or financial transactions.
Fuzzy logic is a mathematical framework for dealing with uncertainty and imprecision. In the context of the intelligence validation and dissemination system, fuzzy logic could be used to model the imprecise and uncertain nature of threat assessments, and to help make decisions based on incomplete or uncertain information.
All of these techniques could be incorporated into a multimodal neural network design for the intelligence validation and dissemination system. For example, the neural network could use the HMM to model sequences of events or actions related to a specific threat, Bayesian inference could be used to update the probability of a threat based on new data inputs, and fuzzy logic could be used to help make decisions based on uncertain or incomplete information.
Take the previous outline and incorporate ways that computer vision can be performed or incorporated (Also, touch on the feasibility of this being automated, given the advances in facial recognition software.) with the same logic, inference, and HMM.
Certainly! Computer vision is an area of artificial intelligence that focuses on enabling computers to interpret and understand visual information from the world around them. In the context of the intelligence community, computer vision can be used to analyze images and videos for a variety of purposes, including surveillance, target recognition, and situational awareness.
To incorporate computer vision into the multi-modal neural network design, the system could include modules that specialize in analyzing visual data, such as images and videos. These modules would use techniques from computer vision, such as object detection, image segmentation, and facial recognition, to extract meaningful information from the visual data. The resulting data could then be fed into the larger neural network, which would incorporate the HMM, Bayesian inference, and fuzzy logic to make predictions and draw conclusions based on the combined data from all the modalities.
The use of facial recognition software in this context raises important ethical and legal considerations, as it can be used to identify individuals and potentially invade their privacy. However, assuming the use of facial recognition is permissible, the system could use this technology to identify individuals of interest in images and videos, and track their movements over time. The resulting data could be used to build up a comprehensive understanding of the individual's activities, associations, and behavior patterns, which could be fed into the larger neural network to make more accurate predictions and identify potential threats.
It is worth noting that while computer vision has made significant advances in recent years, there are still many challenges to be addressed in this field. For example, computer vision algorithms can be susceptible to errors and biases, and may struggle to interpret certain types of visual data, such as images with low contrast or complex backgrounds. Furthermore, the use of facial recognition software is controversial, and there are concerns about its accuracy, bias, and potential misuse. As such, any system that incorporates computer vision must be designed and implemented with care, and subject to appropriate legal and ethical safeguards.
Yes, from some of the way that the fashion industry (using animal patterns) has made clothing to avoid such things. Regarding that, is this because it works on a probability based algorithm that matches the likelihood of the most detected features and compares it?
Yes, you are correct. Computer vision algorithms work by identifying patterns in images or videos and then matching those patterns to a pre-existing database of known patterns or features. This process involves breaking down the image into smaller components and analyzing those components for specific features or characteristics, such as lines, edges, colors, shapes, or textures. The algorithm then compares those features to the features in its database to determine the best match or matches, based on a probability score.
In the case of fashion industry, the computer vision algorithms are trained to detect specific animal patterns, such as leopard spots or zebra stripes, and then identify clothing items that match those patterns. This is achieved by feeding the algorithm a large dataset of images of clothing items and labeling them according to their patterns. The algorithm then learns to recognize those patterns and can apply that knowledge to new images of clothing items, even if they have never seen those specific items before.
Regarding the use of animal patterns in fashion, it is worth noting that some fashion brands have started to use computer vision algorithms to identify more sustainable and ethical materials for their products, such as by detecting the use of animal-derived materials in clothing and accessories. This can help consumers make more informed purchasing decisions and can also encourage fashion brands to adopt more responsible and sustainable practices.
Specifically, what this fashion appears to do is "confuse" the detection by creating a larger percentage of a chance that was is being detected is a "giraffe", despite the presence of human features. Thoughts?
Yes, that's correct. The idea behind such clothing is to create a visual pattern that contains multiple, similarly sized shapes that can potentially confuse object recognition algorithms. The algorithms used for object detection in computer vision are typically based on machine learning models that are trained on large datasets of labeled images. These models often rely on identifying specific features or patterns in the images that correspond to the objects they are trying to detect.
By creating patterns that contain similarly sized shapes that might resemble parts of an animal or other non-human object, the hope is that the algorithms will be less likely to identify the human figure in the image. However, it's important to note that such clothing is not foolproof and may not work in all situations, especially as object recognition algorithms continue to improve with advances in artificial intelligence and machine learning.
In order to better address this, for surveillance purposes, could this incorporate the detection of "human movements"?
Yes, incorporating the detection of human movements could be a way to address the potential limitations of relying solely on facial recognition in surveillance systems. This could be done by using computer vision techniques to analyze and identify various aspects of human movements, such as posture, gait, and other physical movements. This could then be used as an additional means of identifying and tracking individuals, along with facial recognition.
However, it's important to note that incorporating the detection of human movements could also pose challenges, such as the potential for false positives or errors in detection. Additionally, there are also ethical considerations surrounding the use of surveillance technologies and their potential impact on privacy and civil liberties. Therefore, any such systems would need to be carefully designed and implemented with these considerations in mind

Naturalized Kitsune

You descend from a line of Kitsune who have lived for a long time with people of another ancestry, far longer than most other Kitsunes and have lost some powers as a result.
Choose a common, Medium humanoid ancestry. Your alternate form is a form that matches this choice called a tailless form. You also gain the Adopted Ancestry feat for your chosen humanoid ancestry.
Your true Kitsune form is equivalent in appearance to the 5th level feat Hybrid Form Kitsune (think the white kimono woman used in the official 2e Kitsune art)
Due to how distant you've become, even in your true form, you can't use unarmed attacks from a Kitsune ancestry feat, and you can't use an ability that requires your tails, and you only gain half the amount of tails as you level that other Kitsune would normally get, you can use these abilities again in your true form if you take the Hybrid Form feat at level 5

Balance Concerns:

I'm basing this of the Adaptive Anadi Heritage, sure their a rare Ancestry but I don't think that rarity makes the Adaptive Anadi heritage OP, but would doing the same & giving adopted ancestry and loosing some Kitsune abilities in return make it balanced?
Should also loosing the ability to use tails and unarmed attack make this Heritage bad? I mean it doesn't seem bad right now, you just lose Foxfire and Retractable Claws, but seeing as the Tian Xia books for 2e are coming up and they might add more Kitsune feats, this could be extremely debilitating, but well remains to be seen, but if I remove this restriction, it makes Hybrid Form useless, so it's either I invalidate currently 2 level 1 feats right now with this, or just 1 level 5 feat
But other than that pretty much all other feats still work, so you can still cast spells from Kitsune feats just as well as other heritages
​

Reasoning for making this Heritage

I think its weird to me based on Kitsune lore that Kitsune cant get Adopted Ancestry until level 3 but the Anadi who they share some similarities with, can through the Adaptive Anadi heritage
The lore similarities I'm talking about are (on the Archive of Nethys 2e page)
Kitsune wrote:

"Though all-kitsune settlements exist, most live among people of other ancestries, granting them a degree of external insight into social rules or dynamics that others process only subconsciously. Kitsune enjoy subverting expectations as much as they do going along with them. Their fondness for jokes, stories, and wordplay, especially when the twist of a riddle hinges on the listener's assumptions, reinforces their reputation as tricksters."

Anadi wrote:

"As a communal and peaceful people, anadi ancestors endeavored to establish trade with the neighbors of their homeland. However, these anadi soon learned that most others found their appearance to be extremely objectionable. Wishing to avoid conflict, ancient anadi retreated into isolation until they could find a solution. The answer came when their greatest scholars innovated a fusion of transmutation and illusion magic that allowed them to assume a humanoid form. The technique was developed, perfected, and eventually taught to the overwhelming majority of anadi."

It's weird to me that Anadi have a heritage that's because their lineage wanted to explicitly blend into Common Medium size Humanoid ancestries, but not also Kitsune
Sure the Kitsune are prolly more distant in a sense to the people they mingle with than the Anadi but, idk like wouldn't it be sensible that you would also find a Heritage type of Kitsune who are like the Adaptive Anadi more, they found that they love being apart of X ancestry and want to become closer to it? They want to not just trick anymore, but actually be almost one with their chosen ancestry?

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you: fit to chubby side. cute. 18 to 30 yrs old. see you.

Mattress Materials. The materials used to create a mattress are a significant factor in making mattresses so expensive. Better quality materials will increase the price of a bed. Some materials, such as organic materials, are also more costly to produce than high-quality synthetic materials.
Is there a difference between cheap and expensive mattress?
Cheaper mattresses tend to be thinner with just a few layers of material. Expensive mattresses will usually be lofted higher due to multiple layers of different materials. These pricey mattresses can also be made of high-density materials such as memory foam.
More about: مراتب
What are the 3 types of mattresses?
There are 3 key types of mattresses — innerspring, hybrid, and foam: Many mattress shoppers are most familiar with innerspring mattresses. As the oldest and most established of these mattress types, most of us grew up sleeping on a traditional innerspring mattress.
Which mattress is good for pain?
The best choice for pain relief is a medium to medium-firm latex, hybrid, or memory foam mattress. Ideally, it would be comfortable, offer support, and encourage spinal alignment.
More about: مراتب

Mattress Materials. The materials used to create a mattress are a significant factor in making mattresses so expensive. Better quality materials will increase the price of a bed. Some materials, such as organic materials, are also more costly to produce than high-quality synthetic materials.
Is there a difference between cheap and expensive mattress?
Cheaper mattresses tend to be thinner with just a few layers of material. Expensive mattresses will usually be lofted higher due to multiple layers of different materials. These pricey mattresses can also be made of high-density materials such as memory foam.
More about: مراتب
What are the 3 types of mattresses?
There are 3 key types of mattresses — innerspring, hybrid, and foam: Many mattress shoppers are most familiar with innerspring mattresses. As the oldest and most established of these mattress types, most of us grew up sleeping on a traditional innerspring mattress.
Which mattress is good for pain?
The best choice for pain relief is a medium to medium-firm latex, hybrid, or memory foam mattress. Ideally, it would be comfortable, offer support, and encourage spinal alignment.
More about: مراتب

Mattress Materials. The materials used to create a mattress are a significant factor in making mattresses so expensive. Better quality materials will increase the price of a bed. Some materials, such as organic materials, are also more costly to produce than high-quality synthetic materials.
Is there a difference between cheap and expensive mattress?
Cheaper mattresses tend to be thinner with just a few layers of material. Expensive mattresses will usually be lofted higher due to multiple layers of different materials. These pricey mattresses can also be made of high-density materials such as memory foam.
More about: مراتب
What are the 3 types of mattresses?
There are 3 key types of mattresses — innerspring, hybrid, and foam: Many mattress shoppers are most familiar with innerspring mattresses. As the oldest and most established of these mattress types, most of us grew up sleeping on a traditional innerspring mattress.
Which mattress is good for pain?
The best choice for pain relief is a medium to medium-firm latex, hybrid, or memory foam mattress. Ideally, it would be comfortable, offer support, and encourage spinal alignment.
More about: مراتب

Mattress Materials. The materials used to create a mattress are a significant factor in making mattresses so expensive. Better quality materials will increase the price of a bed. Some materials, such as organic materials, are also more costly to produce than high-quality synthetic materials.
Is there a difference between cheap and expensive mattress?
Cheaper mattresses tend to be thinner with just a few layers of material. Expensive mattresses will usually be lofted higher due to multiple layers of different materials. These pricey mattresses can also be made of high-density materials such as memory foam.
More about: مراتب
What are the 3 types of mattresses?
There are 3 key types of mattresses — innerspring, hybrid, and foam: Many mattress shoppers are most familiar with innerspring mattresses. As the oldest and most established of these mattress types, most of us grew up sleeping on a traditional innerspring mattress.
Which mattress is good for pain?
The best choice for pain relief is a medium to medium-firm latex, hybrid, or memory foam mattress. Ideally, it would be comfortable, offer support, and encourage spinal alignment.
More about: مراتب

Why mattresses are so expensive?
Mattress Materials. The materials used to create a mattress are a significant factor in making mattresses so expensive. Better quality materials will increase the price of a bed. Some materials, such as organic materials, are also more costly to produce than high-quality synthetic materials.
Is there a difference between cheap and expensive mattress?
Cheaper mattresses tend to be thinner with just a few layers of material. Expensive mattresses will usually be lofted higher due to multiple layers of different materials. These pricey mattresses can also be made of high-density materials such as memory foam.
More about: مراتب
What are the 3 types of mattresses?
There are 3 key types of mattresses — innerspring, hybrid, and foam: Many mattress shoppers are most familiar with innerspring mattresses. As the oldest and most established of these mattress types, most of us grew up sleeping on a traditional innerspring mattress.
Which mattress is good for pain?
The best choice for pain relief is a medium to medium-firm latex, hybrid, or memory foam mattress. Ideally, it would be comfortable, offer support, and encourage spinal alignment.
More about: مراتب

I heard so many good things about this game so I got it on switch. It’s technically my first farming game not counting rune factory 4 because it’s more of an rpg than a farming game. So most of the mechanics that make this farming game seem alien to me. Any tips and tricks for the game as a whole. Anything I should know early on. Don’t give me to much info, because I want to learn the game but at the same time I just need small to medium tips. Nothing big.

Nicolai Sinai on an ep of Exploring the Quran and the Bible makes the claim that Q 3:7,

It is He who has sent down to you, [O Muhammad], the Book; in it are verses [that are] precise - they are the foundation of the Book - and others unspecific. As for those in whose hearts is deviation [from truth], they will follow that of it which is unspecific, seeking discord and seeking an interpretation [suitable to them]. And no one knows its [true] interpretation except Allah. But those firm in knowledge say, "We believe in it. All [of it] is from our Lord." And no one will be reminded except those of understanding.

which cautions against ambiguous Quranic verses in favor of specific ones, is best understood as a "post-prophetic" addition - simply that they were more likely to have been produced later than traditional prophetic revelations of the quran - and potentially outside of it, though he seems cautious to go this far. Verses like this have implications for the chronology of the construction of the Quran that likely (?) differ from the traditional narrative.
I think his reasoning for this being post-prophetic was just that a verse like this only get produced after there is a community grappling with a text, especially in the context of viewing the Quran as a cohesive unit, doubly so because it goes against the Quran's general claim that it is mubeen/clear.
I wonder if there are other verses that meet this criteria. I was reminded that there is a verse that, unless I'm reading it wrong, either paves the way or justifies after-the-fact the need for abrogation in Q 2:106

If We ever abrogate a verse or cause it to be forgotten, We replace it with a better or similar one. Do you not know that Allah is Most Capable of everything? Any verse [from the previous Books] We cause to be abrogated or forgotten; We will replace it with one like it or better.

So I'm left with some questions.

1. Is there a reason Prof. Sinai doesn't cite pro-abrogation verses as post prophetic?
   
2. Are there other meta-textual verses that make at least some degree of sense in a post-prophetic context? By meta-textual I guess i just mean verses describing how to deal with the text.
   

looking forward to replies, thanks for reading <3