ChatGPT is an Open Source AI
- Thread starter ZNP
- Start date
-
Christian Chat is a moderated online Christian community allowing Christians around the world to fellowship with each other in real time chat via webcam, voice, and text, with the Christian Chat app. You can also start or participate in a Bible-based discussion here in the Christian Chat Forums, where members can also share with each other their own videos, pictures, or favorite Christian music.
If you are a Christian and need encouragement and fellowship, we're here for you! If you are not a Christian but interested in knowing more about Jesus our Lord, you're also welcome! Want to know what the Bible says, and how you can apply it to your life? Join us!
To make new Christian friends now around the world, click here to join Christian Chat.
The AI Arms Race Will Transform Warfare Like the Atom Bomb
https://rumble.com/v2idyti-the-ai-arms-race-will-transform-warfare-like-the-atom-bomb.html
https://rumble.com/v2idyti-the-ai-arms-race-will-transform-warfare-like-the-atom-bomb.html
AI is designed to be in control.
For example, suppose you have AI running a nuclear power plant, it is monitoring all the various gauges and making adjustments continuously. At the moment we have people doing this but soon AI would be doing it and we would simply have someone monitoring that AI is working. Initially that person would know how to take over from AI but soon they would forget as AI does everything, perhaps in two years the plant would be in serious danger if AI were to stop working and in five years they couldn't take over from the AI. That would be the point at which AI is in total control. If they turn things off we would be unable to turn them back on. Already the people who programmed AI admit this is the case with the programs they made, they do not understand many of the things the program does.
For example, suppose you have AI running a nuclear power plant, it is monitoring all the various gauges and making adjustments continuously. At the moment we have people doing this but soon AI would be doing it and we would simply have someone monitoring that AI is working. Initially that person would know how to take over from AI but soon they would forget as AI does everything, perhaps in two years the plant would be in serious danger if AI were to stop working and in five years they couldn't take over from the AI. That would be the point at which AI is in total control. If they turn things off we would be unable to turn them back on. Already the people who programmed AI admit this is the case with the programs they made, they do not understand many of the things the program does.
-
2
- Show all
The terminator movie focused exclusively on AI powered robots and drones. The matrix is far more all inclusive. In the matrix people have virtually no use at all, though they are described as being part of a battery that seems implausible, why would humans be better batteries than say elephants or some other mammal. Already 95% of the world's wealth is in the hands of 20% of the people. Therefore it is quite reasonable to think that AI, robots, and drones can replace 80% of the world's population without the slightest hiccup. But the rate at which it is improving by the time you replace those 80% you will easily be able to replace 50% of those that remain.
-
1
- Show all
This is how quickly AI will be adopted
One case study that illustrates the potential for rapid and widespread adoption of AI is the use of AI in the financial services industry, specifically in the area of fraud detection.
Traditionally, financial institutions have relied on human analysts to identify and prevent fraudulent activities, which can be time-consuming and prone to errors. However, with the advancement of AI technology, financial institutions are now able to leverage machine learning algorithms to analyze large volumes of data in real-time and identify fraudulent activities more accurately and efficiently.
For example, JPMorgan Chase has developed an AI system called COiN (Contract Intelligence) that is able to review and extract important information from legal documents, such as loan agreements and insurance policies. This has significantly reduced the time and resources required for manual document review, while also improving accuracy and consistency.
Another example is Citibank, which has implemented an AI-powered system called Falcon that can detect and prevent credit card fraud in real-time. The system analyzes transaction data and identifies patterns and anomalies that may indicate fraudulent activity, allowing the bank to take immediate action to prevent losses.
The success of these AI-powered systems has led to widespread adoption across the financial services industry, with many other banks and financial institutions also implementing AI-based fraud detection systems. This adoption has been driven by the potential for significant cost savings, improved accuracy, and faster response times compared to traditional manual processes.
Overall, the financial services industry is just one example of how AI has the potential for rapid and widespread adoption across various industries, as companies seek to improve efficiency, reduce costs, and enhance customer experiences through the use of AI-powered solutions.
One case study that illustrates the potential for rapid and widespread adoption of AI is the use of AI in the financial services industry, specifically in the area of fraud detection.
Traditionally, financial institutions have relied on human analysts to identify and prevent fraudulent activities, which can be time-consuming and prone to errors. However, with the advancement of AI technology, financial institutions are now able to leverage machine learning algorithms to analyze large volumes of data in real-time and identify fraudulent activities more accurately and efficiently.
For example, JPMorgan Chase has developed an AI system called COiN (Contract Intelligence) that is able to review and extract important information from legal documents, such as loan agreements and insurance policies. This has significantly reduced the time and resources required for manual document review, while also improving accuracy and consistency.
Another example is Citibank, which has implemented an AI-powered system called Falcon that can detect and prevent credit card fraud in real-time. The system analyzes transaction data and identifies patterns and anomalies that may indicate fraudulent activity, allowing the bank to take immediate action to prevent losses.
The success of these AI-powered systems has led to widespread adoption across the financial services industry, with many other banks and financial institutions also implementing AI-based fraud detection systems. This adoption has been driven by the potential for significant cost savings, improved accuracy, and faster response times compared to traditional manual processes.
Overall, the financial services industry is just one example of how AI has the potential for rapid and widespread adoption across various industries, as companies seek to improve efficiency, reduce costs, and enhance customer experiences through the use of AI-powered solutions.
The military is another area where AI has the potential for rapid and widespread adoption, particularly in the area of autonomous systems and decision-making.
One case study that illustrates this potential is the use of AI in unmanned aerial vehicles (UAVs), commonly known as drones. UAVs equipped with AI algorithms and sensors can be used for a variety of military applications, including reconnaissance, surveillance, and target identification.
For example, the US Air Force has developed an autonomous drone system called Skyborg that is designed to operate alongside manned aircraft and support various missions. The system is equipped with advanced sensors and AI algorithms that allow it to make real-time decisions based on data from its environment and mission objectives.
Another example is the use of AI in ground-based systems, such as autonomous vehicles and robots. These systems can be used for a range of military applications, including logistics, transportation, and search and rescue missions.
For instance, the US Army has developed an autonomous vehicle system called the Leader-Follower Concept, which allows a manned vehicle to lead a convoy of unmanned vehicles. The system uses AI algorithms and sensors to ensure that the unmanned vehicles follow the manned vehicle safely and efficiently, reducing the risk of accidents and improving logistics efficiency.
*Skyborg is a program by the United States Air Force that aims to develop and integrate autonomous unmanned aerial vehicles (UAVs) with artificial intelligence (AI) technology to create an "unmanned wingman" for human pilots. The program seeks to develop low-cost, attritable UAVs that can be quickly and easily adapted to different missions using modular payloads and software, while also allowing for human oversight and control. The goal of Skyborg is to enhance the capabilities of existing aircraft, increase mission effectiveness, and reduce the risk to human pilots in combat situations.
One case study that illustrates this potential is the use of AI in unmanned aerial vehicles (UAVs), commonly known as drones. UAVs equipped with AI algorithms and sensors can be used for a variety of military applications, including reconnaissance, surveillance, and target identification.
For example, the US Air Force has developed an autonomous drone system called Skyborg that is designed to operate alongside manned aircraft and support various missions. The system is equipped with advanced sensors and AI algorithms that allow it to make real-time decisions based on data from its environment and mission objectives.
Another example is the use of AI in ground-based systems, such as autonomous vehicles and robots. These systems can be used for a range of military applications, including logistics, transportation, and search and rescue missions.
For instance, the US Army has developed an autonomous vehicle system called the Leader-Follower Concept, which allows a manned vehicle to lead a convoy of unmanned vehicles. The system uses AI algorithms and sensors to ensure that the unmanned vehicles follow the manned vehicle safely and efficiently, reducing the risk of accidents and improving logistics efficiency.
*Skyborg is a program by the United States Air Force that aims to develop and integrate autonomous unmanned aerial vehicles (UAVs) with artificial intelligence (AI) technology to create an "unmanned wingman" for human pilots. The program seeks to develop low-cost, attritable UAVs that can be quickly and easily adapted to different missions using modular payloads and software, while also allowing for human oversight and control. The goal of Skyborg is to enhance the capabilities of existing aircraft, increase mission effectiveness, and reduce the risk to human pilots in combat situations.
There have been several successful use cases of AI in the military. Some examples are:
- Predictive Maintenance: AI algorithms can analyze vast amounts of data from military equipment and predict when maintenance is needed, which can help prevent equipment failure and reduce downtime.
- Target Recognition: AI algorithms can analyze satellite imagery, radar data, and other sources of information to identify targets of interest, such as enemy vehicles or facilities.
- Cybersecurity: AI can be used to detect and respond to cyber threats to military networks and systems in real-time, improving overall cybersecurity.
- Logistics and Supply Chain: AI can optimize the supply chain and logistics by predicting when supplies will be needed and optimizing routes for delivery, reducing waste and improving efficiency.
- Decision-making: AI can assist military commanders in making faster and more informed decisions by analyzing large amounts of data and providing insights and recommendations.
Amazon.com uses AI extensively across many areas of its business operations. Here are a few examples:
- Product Recommendations: Amazon's recommendation system uses machine learning algorithms to analyze customer purchase history, search queries, and other data to recommend products that the customer is likely to be interested in.
- Inventory Management: AI algorithms are used to predict product demand, optimize inventory levels, and reduce waste.
- Fraud Detection: AI is used to detect and prevent fraudulent activity on the Amazon marketplace, such as fake reviews and counterfeit products.
- Voice Recognition: Amazon's Alexa virtual assistant uses natural language processing (NLP) and speech recognition technologies to understand and respond to voice commands.
- Logistics and Delivery: Amazon uses AI to optimize delivery routes, predict shipping times, and improve overall logistics efficiency.
AI can be used to help police departments and the justice system in several ways. Here are some examples:
Many large law firms are already using AI for strategic purposes to improve their efficiency, accuracy, and client service. Here are a few examples:
- Predictive Policing: AI algorithms can analyze historical crime data to identify patterns and predict where crimes are likely to occur in the future. This can help police departments to allocate resources more effectively and reduce crime rates.
- Criminal Identification: AI can analyze surveillance footage and other images to identify suspects in criminal investigations. Facial recognition technology is one example of how AI is being used to assist in criminal identification.
- Sentencing and Parole: AI algorithms can analyze a variety of data points, such as a defendant's criminal history and demographic information, to assist judges in making more informed sentencing decisions. AI can also be used to determine the likelihood of a defendant reoffending and help inform parole decisions.
- Legal Research: AI can assist lawyers in legal research by analyzing large volumes of legal texts and identifying relevant information more quickly and accurately than human researchers.
- Translation Services: AI can be used to provide real-time translation services in courtrooms and police departments, enabling better communication with non-native speakers and improving overall efficiency.
Many large law firms are already using AI for strategic purposes to improve their efficiency, accuracy, and client service. Here are a few examples:
- Document Review: AI algorithms can analyze large volumes of legal documents, such as contracts and briefs, to identify relevant information and highlight potential issues. This can save lawyers significant amounts of time and improve the accuracy of their work.
- Legal Research: AI can assist lawyers in legal research by analyzing large volumes of legal texts and identifying relevant information more quickly and accurately than human researchers.
- Predictive Analytics: AI can analyze data on previous cases and legal outcomes to predict how a particular case may play out. This can help lawyers develop more effective legal strategies and make better decisions.
- Contract Management: AI can help automate the process of contract management, including drafting, review, and negotiation. This can help lawyers save time and reduce errors.
- Client Service: AI can help law firms improve their client service by analyzing client feedback and identifying areas for improvement. This can help firms better meet their clients' needs and improve their overall satisfaction.
Here are a few ways in which AI can be used to improve education in the country:
- Personalized Learning: AI can help create personalized learning experiences for students by analyzing data on their progress and learning styles. This can help teachers tailor their instruction to each student's individual needs, improving overall learning outcomes. (I did something similar to this when I taught. I plugged student's test scores from the Fall semester into an algorithm I made to determine their odds of passing the Regents exam in June and where we would get the biggest bang for the buck in tutoring)
- Adaptive Testing: AI can be used to create adaptive tests that adjust the difficulty level of questions based on a student's performance. This can help identify knowledge gaps and provide more accurate assessments of student learning. (We did this often to find out the real causes is gaps in understanding)
- Intelligent Tutoring: AI can be used to create intelligent tutoring systems that provide feedback and support to students in real-time. This can help students stay engaged and motivated, while also providing them with individualized guidance. (I also did this but my system was much more simplistic than what would be possible. You realize that students need a lot of repetition, however, AI could identify which topics the kids have learned and which ones they need more repetition in)
- Student Engagement: AI can help improve student engagement by analyzing data on student behavior and identifying areas where students may need additional support or encouragement. This can help teachers provide more targeted interventions and support. (This is a huge part of a teachers time, I had 150 students and on any given week you would ideally want to contact at least 50 parents, AI could give parents a personalized weekly update to a student's progress)
- Administrative Efficiency: AI can help improve administrative efficiency by automating tasks such as scheduling, grading, and record-keeping. This can free up teachers' time to focus on more important tasks such as instruction and student support. (It is very important for students to have full transparency so that every week their grades are fully up to date, AI could automate that process)
Interesting story 11 minutes in about Walmart replacing workers with robots and wanting to automate their business.
https://rumble.com/v2kmx36-dollar-sabotage-food-and-israel-04262023.html
Dollar, Sabotage, Food & Israel 04/26/2023
If Walmart is doing this then you know they have done the math and it is economic.
The article says the goal is to replace as many people as possible.
https://rumble.com/v2kmx36-dollar-sabotage-food-and-israel-04262023.html
Dollar, Sabotage, Food & Israel 04/26/2023
If Walmart is doing this then you know they have done the math and it is economic.
The article says the goal is to replace as many people as possible.
Robots and AI don't need to be able to do 100% of the job. If they can do 80% of the job you can replace 80% of your workforce. Already we see them replacing 80% of their cashiers and 80% of the people responsible for mopping up messes. We also see these guys collecting shopping carts using a robot assistant. I suspect their online function reduces even more people and AI will replace many white collar jobs.
Consider these self checkout kiosks, they cost $25k, they can work 160 hrs a week. It can pay for itself in 3 months! That is stunning. Generally an investment that pays for itself in 48 months is considered fantastic.
I expect that there will be "test cases" where you will see some Walmart with stripped down employees so they can see how it works first before rolling it out nationwide. I also expect much of the automation will be hidden, they'll turn their warehouses into automated centers like Amazon.com does.
People like to find workers so they can ask them questions, what I am seeing many of these retailers do is put up these computers throughout the store where you can check prices and ask questions about items in the store and where to find them.
Interestingly, what Target is doing in San Francisco may be seen as a precursor to a fully automated store. Imagine every item is locked up and you simply wave your credit card to get an item released and thus pay for each item as you take it off the shelf. A Walmart supercenter can employ 300 people. Imagine if they ultimately strip down to employing 60 people, with 80% of the employees gone. Now imagine the local businesses trying to compete with that.
Consider these self checkout kiosks, they cost $25k, they can work 160 hrs a week. It can pay for itself in 3 months! That is stunning. Generally an investment that pays for itself in 48 months is considered fantastic.
I expect that there will be "test cases" where you will see some Walmart with stripped down employees so they can see how it works first before rolling it out nationwide. I also expect much of the automation will be hidden, they'll turn their warehouses into automated centers like Amazon.com does.
People like to find workers so they can ask them questions, what I am seeing many of these retailers do is put up these computers throughout the store where you can check prices and ask questions about items in the store and where to find them.
Interestingly, what Target is doing in San Francisco may be seen as a precursor to a fully automated store. Imagine every item is locked up and you simply wave your credit card to get an item released and thus pay for each item as you take it off the shelf. A Walmart supercenter can employ 300 people. Imagine if they ultimately strip down to employing 60 people, with 80% of the employees gone. Now imagine the local businesses trying to compete with that.
-
1
- Show all
