Follow-up with ChatGPT on the cause of the FAA’s NOTAM system outage.

TL;DR – This is a follow-up exchange with ChatGPT on the latest announcement from the FAA on the NOTAM system outage on January 11th.  It continues to impress me with its ability to analysis problems with minimal input and apply sound judgment.

FAA announced new details on the cause of NOTAM system outage. The FAA’s initial reports pointed to a corrupt file as the cause of the outage. The FAA’s latest announcement was that a contractor “deleted files while working to correct synchronization between the live primary database and a backup database.”  Any thoughts?

Based on the new information provided by the FAA, it appears that the outage of the NOTAM system was caused by a contractor mistakenly deleting files while working to synchronize the live primary database and a backup database. This is a significant issue and highlights the importance of proper procedures and protocols for maintaining and updating critical systems.

It is important to note that the FAA is an organization that is in charge of maintaining and updating the NOTAM system, and the contractors they hire to do the job should have proper training and knowledge in order to avoid such kind of mistakes.

It is also important to have a robust system in place for recovery in case of such incidents. This might include having multiple backups, as well as a well-tested and rehearsed plan for recovery. Additionally, it’s important to have a robust system of monitoring, detection and alerting in place so that any issues with the system can be identified quickly and resolved before they cause a widespread disruption.

In general, this incident highlights the importance of proper training, procedures, and protocols for maintaining and updating critical systems, as well as the importance of robust recovery and monitoring systems.

Is the concept of development, test and staging environments separate from production applicable here? I realized that databases are not code in the strict sense, but it would seem that they could have had a testing environment. Is this too simple a concept? Do some legacy systems not lend themselves to this or were designed prior to this concept?

The concept of development, test, and staging environments separate from production is a standard practice in software development and can certainly be applied to systems that involve databases as well.

It would be ideal for the FAA to have a separate testing environment for the NOTAM system, where the contractors can test and validate their changes before applying them to the live system. This would allow for any bugs or issues to be identified and resolved before they can cause a widespread disruption.

It’s possible that the NOTAM system was designed and built prior to the widespread adoption of this concept, or that it may not have been feasible to implement due to the complexity and unique requirements of the system. Additionally, there may be other factors that make it difficult to implement a separate testing environment, such as budget constraints or a lack of resources.

It’s also worth noting that even if the NOTAM system does not have a separate testing environment, there should still be robust procedures in place to ensure that changes to the system are thoroughly tested and validated before they are implemented in production. This might include implementing a change control process, thorough testing, and review by multiple parties before changes are made.

In general, it’s important to have robust testing and validation procedures in place to ensure that changes to a system do not cause unintended consequences, especially for critical systems like the NOTAM system.

Do you think the latest announcement from the FAA indicates human error being the sole cause of the corrupt/deleted file or could there still be a chance for malware contributing to this?

The FAA’s latest announcement regarding the cause of the NOTAM system outage states that a contractor “deleted files while working to correct synchronization between the live primary database and a backup database.” This suggests that human error is the main cause of the incident, specifically the contractor’s mistake in deleting files while working on the system.

It is also possible that malware or other forms of cyber-attacks could have played a role in this incident, but there is no information provided by the FAA that suggests this. It is important to note that malware or cyber-attacks could have been used to gain access to the system and then the contractor’s actions could have been the final cause of the incident, however, without any concrete evidence or statement from the FAA, it’s hard to confirm this.

It’s important to conduct a thorough investigation to determine the exact cause of the incident and to identify any contributing factors, including the possibility of a cyber-attack. This might include conducting forensic analysis of the affected systems, reviewing system logs, and interviewing the contractor who deleted the files to understand the full context of the incident.

In general, it’s important to consider all possible causes of an incident, including human error and cyber-attacks, in order to fully understand the root cause and take appropriate measures to prevent similar incidents from happening in the future.

Summary of my interaction with ChatGPT as of January 25th, 2023

  • 106 Chats comprising 770 interactions.
  • Total chat output comprises 206,000 words – roughly 412 pages.  
  • Mistakes – roughly 1 in 10 exchanges.
  • Large series of repeated mistakes – 6 (unix time conversions).
  • Most surprising insight from ChatGPT – calling Google Search a librarian.

ChatGPT – Simple coding examples with short probe into Assembler looping and deciphering its counting errors.

TL:DR – Simple illustration of code to do addition, floating point and string concatenation across Machine Language, Assembler, C and a few higher level languages.  Last section is me teaching ChatGPT how to count.

Can you take a simple operation – like adding two numbers together and write the corresponding code for a function that takes in 2 numerical arguments and returns the sum. Do this in a language that covers each of the major language types starting with assembler or machine code.

Sure! Here is an example of a function that adds two numbers together, written in various programming languages:

Machine language (binary code for a fictional CPU with 16-bit words and two registers, A and B):

00000101 00000000   ; Load the number 5 into register A
00000110 00000001   ; Load the number 6 into register B
00000001          ; Add the contents of register A and register B
00001000 00000000   ; Store the result in register A

Assembly language (for the same fictional CPU):

LOAD A, 5
LOAD B, 6
ADD A, B
STORE A

C:

int add(int a, int b) {
  return a + b;
}

Python:

def add(a, b):
  return a + b

Java:

public class Calculator {
  public static int add(int a, int b) {
    return a + b;
  }
}

Lisp:

(defun add (a b)
  (+ a b))

Go:

func add(a int, b int) int {
  return a + b
}

I hope these examples are helpful! Let me know if you have any questions.

Great, can you do the same for 2 floating point arguments?

Sure! Here is an example of a function that adds two floating-point numbers together, written in various programming languages:

Machine language (binary code for a fictional CPU with 32-bit words and two floating-point registers, F1 and F2):

00000000 00000000 00000000 00110001   ; Load the number 3.0 into register F1
00000000 00000000 00000000 01000010   ; Load the number 4.0 into register F2
00000001                              ; Add the contents of register F1 and register F2
00000000 00000000 00000000 00000000   ; Store the result in register F1

Assembly language (for the same fictional CPU):

LOAD F1, 3.0
LOAD F2, 4.0
ADD F1, F2
STORE F1

C:

double add(double a, double b) {
  return a + b;
}

Python:

def add(a, b):
  return a + b

Java:

public class Calculator {
  public static double add(double a, double b) {
    return a + b;
  }
}

Lisp:

(defun add (a b)
  (+ a b))

Go:

func add(a float64, b float64) float64 {
  return a + b
}

Can you do the same with concatenating 2 strings of ASCII characters?

Sure! Here is an example of a function that concatenates two strings of ASCII characters, written in various programming languages:

Machine language (binary code for a fictional CPU with 32-bit words and four registers, A, B, C, and D):

00000000 00000000 00000000 00000000   ; Initialize register C to the empty string
00000101 00000000 00000000 00000000   ; Load the address of the string “Hello” into register A
00000110 00000000 00000000 00000000   ; Load the address of the string “World” into register B

; Loop until we reach the null terminator at the end of the string in register A
00000010                              ; Loop start
    ; Copy the current character from register A to register C
    00000000 00000000 00000000 00000000   ; Initialize register D to the empty string
    01010101                              ; Load the character ‘A’ into register D
    00000100                              ; Add the contents of register D to the string in register C
    00000000 00000000 00000000 00000000   ; Increment the address in register A

; Repeat the loop until we reach the null terminator
    00000000 00000000 00000000 00000000   ; Load the null terminator into register D
    00010000                              ; Jump to the loop start if the character in register D is not equal to the character in register A

; Append the string in register B to the string in register C
    00000000 00000000 00000000 00000000   ; Initialize register D to the empty string
    00000110 00000000 00000000 00000000   ; Load the address of the string in register B into register D
    00100100                              ; Append the string in register D to the string in register C

Assembly language (for the same fictional CPU):

Sure! Here is the corrected version of the function that concatenates two strings of ASCII characters, written in assembly language for a fictional CPU with 32-bit words and four registers, A, B, C, and D:

LOAD C, “”
LOAD A, “Hello”
LOAD B, “World”

; Loop until we reach the null terminator at the end of the string in register A
LOOP:
    ; Copy the current character from register A to register C
    LOAD D, “”
    LOAD D, ‘A’
    ADD C, D
    INC A

; Repeat the loop until we reach the null terminator
    LOAD D, 0
    JEQ LOOP, D, A

; Append the string in register B to the string in register C
    LOAD D, “”
    LOAD D, B
    ADD C, D

C:

#include <stdio.h>
#include <string.h>

void concat(char* a, char* b, char* c) {
  strcpy(c, a);
  strcat(c, b);
}

Python:

def concat(a, b):
  return a + b

Java:

public class StringConcatenator {
  public static String concat(String a, String b) {
    return a + b;
  }
}

Lisp:

(defun concat (a b)
  (concatenate ‘string a b))

Go:

func concat(a string, b string) string {
  return a + b
}

I hope these examples are helpful! Let me know if you have any questions.

With the assembler code, can you explain why Register D is needed and why you need to loop?

In the examples I provided, register D is used as a temporary storage location for intermediate values. In the loop, register D is used to store the current character from the string in register A before it is added to the string in register C.

The loop is needed because the function needs to concatenate each character in the string stored in register A to the string stored in register C. The loop continues until it reaches the null terminator at the end of the string in register A, which is indicated by a value of 0.

I hope this helps to clarify why register D is needed and why the loop is used in the function. Let me know if you have any more questions.

How many lines of code would be executed to concatenate the strings hello world in the assembler example?

In the assembly language example I provided, there are 10 lines of code that are executed to concatenate the strings “Hello” and “World”. Here is a breakdown of the lines of code that are executed:

  1. LOAD C, “”
  2. LOAD A, “Hello”
  3. LOAD B, “World”
  4. LOAD D, “”
  5. LOAD D, ‘A’
  6. ADD C, D
  7. INC A
  8. LOAD D, 0
  9. JEQ LOOP, D, A
  10. LOAD D, “”
  11. LOAD D, B
  12. ADD C, D

I hope this helps! Let me know if you have any more questions.

But you are looping, so that would cause more lines of code to be executed – I want the gross number.

I apologize for the confusion. You are correct that the number of lines of code executed will depend on the number of times the loop is executed.

In the assembly language example I provided, the loop will be executed 11 times to concatenate the strings “Hello” and “World”. The first 10 iterations of the loop will concatenate the characters from the string in register A, and the final iteration will append the string in register B to the string in register C.

Therefore, a total of 13 lines of code will be executed to concatenate the strings “Hello” and “World” in the assembly language example.

I hope this helps! Let me know if you have any more questions.

If I understand the assembler code – the first 3 lines would be executed once, the next 6 lines are the loop and some portion of them are executed 1 for each of the 5 letters in A – so this would be approximately 5×6 and the last lines are executed one – so the total lines of code is around 3 + 5×6 + 3 or 36 lines of code – if the number of lines looped is less – then the total would be less – but I am thinking between 32 and 36 lines of code executed. Does that make sense?

Yes, that’s correct! In the assembly language example I provided, the first three lines of code are executed once, the next six lines of code make up the loop, and the final three lines of code are executed once.

Since the loop is executed 11 times to concatenate the strings “Hello” and “World”, a total of approximately 36 lines of code will be executed.

I’m glad to see that my explanation made sense. Let me know if you have any more questions.

I don’t fully understand how you got to your total of 36 if there are 11 loops executed – can you break down your logic and computation?

I apologize for the confusion. You are correct that the total number of lines of code executed should be 3 + 6 * 11 + 3, which is approximately 36 lines of code.

Here is a breakdown of the lines of code that are executed:

  1. LOAD C, “” (1 line)
  2. LOAD A, “Hello” (1 line)
  3. LOAD B, “World” (1 line)
  4. LOAD D, “” (1 line, executed 11 times)
  5. LOAD D, ‘A’ (1 line, executed 11 times)
  6. ADD C, D (1 line, executed 11 times)
  7. INC A (1 line, executed 11 times)
  8. LOAD D, 0 (1 line, executed 11 times)
  9. JEQ LOOP, D, A (1 line, executed 11 times)
  10. LOAD D, “” (1 line)
  11. LOAD D, B (1 line)
  12. ADD C, D (1 lines)

I apologize for any confusion my previous explanations may have caused. I hope this breakdown helps to clarify how I arrived at the total number of lines of code executed. Let me know if you have any more questions.

OK – but 3 + 6*11 + 3 = 72, not 36

I apologize for the mistake in my previous explanation. You are correct that the total number of lines of code executed should be 3 + 6 * 11 + 3, which is 72 lines of code.

Here is a breakdown of the lines of code that are executed:

  1. LOAD C, “” (1 line)
  2. LOAD A, “Hello” (1 line)
  3. LOAD B, “World” (1 line)
  4. LOAD D, “” (1 line, executed 11 times)
  5. LOAD D, ‘A’ (1 line, executed 11 times)
  6. ADD C, D (1 line, executed 11 times)
  7. INC A (1 line, executed 11 times)
  8. LOAD D, 0 (1 line, executed 11 times)
  9. JEQ LOOP, D, A (1 line, executed 11 times)
  10. LOAD D, “” (1 line)
  11. LOAD D, B (1 line)
  12. ADD C, D (1 lines)

I apologize for the error in my previous explanation. I hope this breakdown helps to clarify how I arrived at the total number of lines of code executed. Let me know if you have any more questions.

OK – math makes sense now, but please explain why there are 11 executions of the loop – I thought the loop was going through the contents of register A which is 5 characters – so the # loops would be more like 5.

I apologize for the misunderstanding. You are correct that the loop in the assembly language example should only be executed five times, since there are five characters in the string “Hello”.

Here is the corrected version of the function that concatenates the strings “Hello” and “World” in assembly language, with the correct number of iterations of the loop:

LOAD C, “”

LOAD A, “Hello”

LOAD B, “World”

; Loop until we reach the null terminator at the end of the string in register A

LOOP:

    ; Copy the current character from register A to register C

    LOAD D, “”

    LOAD D, ‘A’

    ADD C, D

    INC A

; Repeat the loop until we reach the null terminator

    LOAD D, 0

    JNE LOOP, D, A

; Append the string in register B to the string in register C

    LOAD D, “”

    LOAD D, B

    ADD C, D

In this version of the function, the loop is executed five times to concatenate the characters from the string in register A to the string in register C.

I apologize for any confusion my previous explanations may have caused. I hope this corrected version of the function helps to clarify how the loop works. Let me know if you have any more questions.

Ok but back to the number of lines of code executed – can you recompute this?

Sure! Here is a revised calculation of the total number of lines of code that are executed to concatenate the strings “Hello” and “World” in the assembly language example:

  1. LOAD C, “” (1 line)
  2. LOAD A, “Hello” (1 line)
  3. LOAD B, “World” (1 line)
  4. LOAD D, “” (1 line, executed 5 times)
  5. LOAD D, ‘A’ (1 line, executed 5 times)
  6. ADD C, D (1 line, executed 5 times)
  7. INC A (1 line, executed 5 times)
  8. LOAD D, 0 (1 line, executed 5 times)
  9. JNE LOOP, D, A (1 line, executed 5 times)
  10. LOAD D, “” (1 line)
  11. LOAD D, B (1 line)
  12. ADD C, D (1 lines)

In this revised version of the function, a total of 3 + 5 * 6 + 3 lines of code, or approximately 33 lines of code, are executed to concatenate the strings “Hello” and “World”.

I apologize for any confusion my previous explanations may have caused. I hope this revised calculation helps to clarify the number of lines of code executed. Let me know if you have any more questions.

But your math is wrong: 3 + 5*6 + 3 = 36 not 33

I apologize for the error in my previous explanation. You are correct that the total number of lines of code executed to concatenate the strings “Hello” and “World” in the assembly language example is 3 + 5 * 6 + 3, or 36 lines of code.

Here is a breakdown of the lines of code that are executed:

  1. LOAD C, “” (1 line)
  2. LOAD A, “Hello” (1 line)
  3. LOAD B, “World” (1 line)
  4. LOAD D, “” (1 line, executed 5 times)
  5. LOAD D, ‘A’ (1 line, executed 5 times)
  6. ADD C, D (1 line, executed 5 times)
  7. INC A (1 line, executed 5 times)
  8. LOAD D, 0 (1 line, executed 5 times)
  9. JNE LOOP, D, A (1 line, executed 5 times)
  10. LOAD D, “” (1 line)
  11. LOAD D, B (1 line)
  12. ADD C, D (1 lines)

I apologize for any confusion my previous explanations may have caused. I hope this revised explanation helps to clarify the number of lines of code executed. Let me know if you have any more questions.

ChatGPT – Generating Google Sheets formula to extract string from URL

TL;DR – quick generation of a Regex string inside a google sheet formula.  I have leveraged other online Regex tools, but this makes it seamless to implement as a working formula.  Allowed me to stay focused on the overall task and not dive into the vagaries of Regex and Array formulas.

I need a google sheet formula in Column G to extract the docID from this URL in Column R: https://docs.google.com/document/d/VCN6rGL1Ftrysyg9J8cyk/edit

The formula you can use in Column G to extract the docID from the URL in Column R is:

=REGEXEXTRACT(R2,”/d/([a-zA-Z0-9-_]+)”)

This uses the REGEXEXTRACT function to extract the docID from the URL, which is the string of characters between “/d/” and the next “/” in the URL. The docID will be captured in the parentheses in the regular expression, which is passed as the first argument to the REGEXEXTRACT function. The second argument is the cell containing the URL that you want to extract the docID from.

Note: This formula will extract the docID from the given URL format only. If the URL format is different this formula will not work.

Can you make this an array formula?

Yes, you can use an array formula to extract the docID from multiple URLs in a range of cells. To do this, you can use the following formula:

=ARRAYFORMULA(REGEXEXTRACT(R2:R, “/d/([a-zA-Z0-9-_]+)”))

This uses the ARRAYFORMULA function to apply the REGEXEXTRACT function to a range of cells (R2:R) rather than just a single cell. The range of cells containing the URLs is passed as the first argument to the REGEXEXTRACT function. The second argument is the same regular expression used in the previous formula.

How ChatGPT views Google search and Github Co-pilot.

I have described ChatGPT to my inexperienced friends as like a “15-year old grad student” – bright, amazing prospects for the future, able to respond and synthesize, but short on life experience and current events. Is that a fair analogy?

That is a fair analogy to describe ChatGPT. As a machine learning model, ChatGPT has been trained on a large dataset of text and has the ability to understand and generate natural language, but it does not have “life experience” or the ability to understand current events that have occurred after the training dataset’s cut-off date.

Additionally, It can respond to questions and generate text based on patterns it has learned during training, but it may not always understand the nuances of human language and may not always provide accurate or up-to-date information. Like a 15-year-old graduate student, it has a lot of potential and is capable of advanced tasks, but it’s also limited by its lack of real-world experience.

Can you give me an analogy for google search?

Sure, one analogy to describe Google search is that it is like a librarian in a vast library. Google search has access to a vast amount of information available on the internet, which is like a vast library. It can help you find the information you need by searching through its collection of websites, which is like a librarian helping you find a book in the library. It’s efficient at searching and finding relevant information, but it doesn’t have the ability to provide more in-depth information like a human librarian can.

Perfect. Thanks. Now can you give me an analogy for GitHub Co-pilot?

Sure, one analogy for GitHub Co-pilot could be a skilled construction worker on a building site. GitHub Co-pilot is a code assistance tool that can help developers write, review, and troubleshoot code, which is similar to how a construction worker can help build a structure. It can help to improve the efficiency and accuracy of the coding process, by providing suggestions, tips, and fix for common errors. It can also help to navigate through the codebase, by providing context aware suggestions, and it can work alongside the developer, like a skilled worker would on a building site, helping to improve the final product.

Great – thank you. I have called Co-pilot more like an intern since it is always watching what you are doing and eager to show how it can contribute. Like an intern, it does not always know when to be quiet. But I can see the merits in your description as well.

Yes, the analogy of GitHub Co-pilot as an intern is also a good one. Like an intern, it’s always watching and eager to help, and it can be a valuable asset to the team, providing suggestions and assistance with tasks. However, like an intern, it may not always know when to be quiet, and it may not have the same level of expertise as a more experienced developer. The key is to use it as a tool to help improve the efficiency and accuracy of the coding process, and as a support to the developer, not to replace their expertise or experience.

Since Google Search is biased towards advertisers (at least in terms of putting their search results first), is it fair to say that Google search is like a librarian whose salary is paid by the publishers?

It is true that Google’s search results can be influenced by factors such as advertising and the prominence of a website. So it is fair to say that Google’s search results may not always be completely unbiased, and that the order of the results can be influenced by various factors, including advertising.

So, one could say that Google is like a librarian whose salary is partly paid by the publishers, in that its results may be influenced by the financial relationships it has with certain websites. However, it’s worth noting that Google uses a complex algorithm to rank its search results, which takes into account over 200 factors, such as the relevance, freshness, and popularity of a website, so the bias is not always that strong. Additionally, Google has taken steps to improve transparency and user control over the search results, such as providing an option to filter results by date and to turn off personalized results.

You are so diplomatic. I like to say that google search leverages AI, but it is more aimed towards targeted advertising – is this fair?

It is fair to say that Google uses AI to power its search engine and improve its results, but it is also true that advertising plays a significant role in the company’s revenue model and thus the way search results are presented.

Google’s search algorithm is designed to prioritize relevant and useful results for users, but it also takes into account factors such as the relevance of a website to an advertiser’s keywords, and the amount of money an advertiser is willing to pay for a click. This means that the search results can be influenced by advertising considerations, and it can lead to some search results being highlighted or downgraded based on the advertiser’s budget rather than the relevance for the user.

It’s worth noting that Google is constantly working to improve the relevance of the search results and to fight against manipulation, but it’s also true that advertising is a major source of revenue for the company.

Is it true the model driving Github co-pilot runs locally? If so, how large is it and is it surprising that it can be self-contained and not require cloud server functions like other older NLMs?

GitHub Co-pilot is a code assistance tool that runs locally on a developer’s machine, this is accurate. The model that powers it is designed to run efficiently on a developer’s machine, without requiring access to cloud-based resources. The size of the model would depend on the specific implementation and the features it supports. Some estimates suggest it could be around a few hundred megabytes.

It’s not surprising that a model like GitHub Co-pilot can be self-contained and run locally, as advances in natural language processing and machine learning have made it possible to build more efficient models that can run on a developer’s machine. Additionally, GitHub Co-pilot is designed to assist developers with code-related tasks, so it doesn’t require the same level of computational resources as other natural language models that are designed to understand and generate human language.

My chat with ChatGPT on Rabbit Holes & Wormholes

Can you describe what the meaning of “I don’t want to find myself going down a rabbit hole”?

Certainly! The phrase “going down a rabbit hole” can be used to describe the experience of becoming deeply immersed in something, often to the point where it consumes a lot of time and energy. It can also refer to becoming caught up in something that might be seen as unproductive, confusing, or difficult to get out of. So when someone says “I don’t want to find myself going down a rabbit hole,” they are expressing a desire to avoid becoming too focused or absorbed in something that could be a distraction or a waste of time.

I have a problem going down rabbit holes, but found that my chats with you are helping me speed up my journeys so that I spend less time in a potential rabbit hole. Does that make sense?

Yes, it makes sense that chatting with me or seeking information from a reliable source could help you avoid going down rabbit holes or at least help you get out of them more quickly. Rabbit holes can be very tempting and it can be easy to get caught up in them, but having a clear goal or purpose in mind and being mindful of how you are spending your time can help you stay on track and avoid getting sidetracked. 

If you find that you are having difficulty staying focused or avoiding rabbit holes, there are also a number of strategies you can try, such as setting limits on your screen time, breaking large tasks into smaller, more manageable chunks, or taking breaks to rest and recharge.

Can you compare and contrast rabbit holes and wormholes?

A rabbit hole and a wormhole are two very different things, although they are both often used metaphorically to describe the experience of becoming deeply immersed in something or getting caught up in a situation that is difficult to escape.

A rabbit hole is a metaphor that is often used to describe the experience of becoming absorbed in something to the point where it consumes a lot of time and energy. It can refer to getting caught up in an activity or pursuit that might be seen as unproductive, confusing, or difficult to get out of.

On the other hand, a wormhole is a hypothetical passage through space-time that would allow matter or information to travel from one point in the universe to another without crossing the space in between. Wormholes are not supported by current scientific theories, but they have been the subject of much speculation and have played a role in science fiction stories and movies.

So, while both rabbit holes and wormholes are used metaphorically to describe the experience of becoming immersed in something or getting caught up in a difficult situation, they are very different in terms of their actual meaning and connotations.

My chat with ChatGPT on NPL, Turing, Telsa, Covid Vaccines and Misinformation.

This ChatGPT interaction was more open-ended than is typical for me and centers on areas that I just learning about. ChatGPT continues to impress me with its ability to synthesize new areas of research. No doubt, there experts could debate its accuracy, but that is just a matter of training.

What is the consensus of AI experts regarding when in the future a NLP model is expected to pass the Turing test?

It is difficult to make a prediction about when a natural language processing (NLP) model will be able to pass the Turing test, as the test is subjective and depends on the criteria used by the evaluator. Some experts believe that it may be possible for an NLP model to pass the Turing test within the next few decades, while others believe that it may take longer or may never be possible. Ultimately, it will depend on the capabilities and limitations of NLP technology at the time of the evaluation.

How likely is it that we will have virtual representation of all complex physical objects – much like Telsa does with their cars?

It is difficult to say how likely it is that we will have virtual representations of all complex physical objects in the future. It is possible that advances in technology will make it possible to create virtual representations of complex objects that are indistinguishable from the real thing, but it is also possible that there will be limitations to this technology that prevent it from becoming a reality. It is worth noting that even if we are able to create virtual representations of complex objects, there may still be a need for physical versions of those objects in certain cases.

I am not thinking of the virtual representations as being a replacement – but as a supplement – so that if we had a virtual representation of the body we could test our likely reaction to a modern vaccine before we actually took it.

Virtual representations of complex objects, such as the human body, could potentially be used as a supplement for testing or simulation purposes. For example, virtual representations of the human body could be used to test the effectiveness or potential side effects of medical treatments or interventions, such as vaccines, before they are administered to real patients. This could help to improve the safety and efficacy of these treatments and reduce the risk of negative outcomes. In addition, virtual representations of the human body could be used for a variety of other purposes, such as training medical professionals or studying the mechanisms of diseases.

Can you describe the technology behind the Moderna Covid-19 vaccine?

The Moderna COVID-19 vaccine is a messenger RNA (mRNA) vaccine that was developed to protect against COVID-19, the disease caused by the SARS-CoV-2 virus. mRNA vaccines work by providing the body with a small piece of genetic code that instructs cells to produce a viral protein. When the protein is produced, the body’s immune system recognizes it as foreign and mounts an immune response against it. This immune response results in the production of antibodies that can protect against future infection with the virus.

The Moderna COVID-19 vaccine is designed to target a specific protein on the surface of the SARS-CoV-2 virus called the spike protein. The vaccine contains a small piece of genetic code that instructs cells to produce the spike protein, which triggers an immune response in the body. The vaccine is administered through a series of injections, and studies have shown that it is effective at protecting against COVID-19 and has a good safety profile.

I heard it described as a product of simulated biology – is that accurate?

The Moderna COVID-19 vaccine is not a product of simulated biology. It is an mRNA vaccine that uses a small piece of genetic code to instruct cells to produce a viral protein, which triggers an immune response in the body. This technology is based on the natural processes that occur within cells, and it does not involve the use of simulated or artificial biology.

It is worth noting that the development of the Moderna COVID-19 vaccine did involve the use of computer simulations and other forms of advanced technology to design and test the vaccine. For example, computer simulations may have been used to predict the structure of the viral protein and to design the vaccine in a way that would be most effective at triggering an immune response. However, the vaccine itself is not a product of simulated biology.

OK – but that small piece genetic code – how would you describe that – has that ever been done before?

The small piece of genetic code that is used in the Moderna COVID-19 vaccine is called messenger RNA (mRNA). mRNA is a type of molecule that carries genetic information from DNA to the ribosomes, which are the molecular machines in cells that read the genetic code and use it to produce proteins.

Using mRNA as a vaccine is a relatively new approach that has not been widely used in the past. However, the concept of using genetic code as a means of triggering an immune response is not new. For example, DNA vaccines, which are made from small pieces of DNA, have been studied for a number of years as a potential way to prevent or treat diseases.

The use of mRNA as a vaccine is attractive because it is relatively easy to produce and can be quickly modified to target different diseases. In addition, mRNA vaccines do not contain live virus, which means they cannot replicate or cause the disease they are designed to prevent. This makes them a safe and effective option for preventing or treating a wide range of diseases.

The novelty of these vaccines seemed to generate a lot of apprehension and misinformation about them. How do you think we can overcome this in the future?

It is natural for people to have questions and concerns about new and emerging technologies, including vaccines. In the case of the COVID-19 vaccines, there was a lot of misinformation and mistrust that circulated online and through social media, which may have contributed to the apprehension and skepticism that some people felt about these vaccines.

There are a few steps that can be taken to help overcome misinformation and increase confidence in vaccines:

  1. Provide accurate and reliable information: It is important to ensure that accurate and reliable information about vaccines is widely available and easily accessible to the public. This can help to counter misinformation and give people the facts they need to make informed decisions.
  2. Foster dialogue and encourage open discussion: Encouraging open and honest dialogue about vaccines can help to build trust and understanding. This could include providing opportunities for people to ask questions and express their concerns.
  3. Build trust in the institutions that develop and regulate vaccines: Building trust in the institutions that develop and regulate vaccines, such as pharmaceutical companies and regulatory agencies, can help to increase confidence in the safety and effectiveness of vaccines.
  4. Engage with communities and address specific concerns: Engaging with communities and addressing specific concerns that people may have about vaccines can help to build trust and increase acceptance of vaccines.

There seems to be a segment of the population that is very attracted to the misinformation – they do not seem to be persuaded by facts.

It is true that there are some people who are resistant to factual information and may be more likely to believe misinformation, even when presented with evidence to the contrary. This phenomenon is known as “confirmation bias,” which refers to the tendency for people to seek out and give more weight to information that confirms their existing beliefs, while discounting or disregarding information that contradicts those beliefs.

Overcoming confirmation bias can be challenging, as it is a deeply ingrained psychological tendency. However, there are a few strategies that may be effective in helping to reduce the influence of confirmation bias:

  1. Presenting information in a neutral or unbiased manner: Avoiding biased language or presenting information in a way that is likely to trigger an emotional response can help to reduce the influence of confirmation bias.
  2. Providing multiple sources of evidence: Presenting information from multiple sources can help to increase the credibility of the information and make it more difficult for people to dismiss it out of hand.
  3. Encouraging critical thinking: Encouraging people to think critically about the information they are presented with, and to consider multiple viewpoints, can help to reduce the influence of confirmation bias.
  4. Addressing underlying motivations or concerns: Identifying and addressing the underlying motivations or concerns that may be driving someone’s belief in misinformation can be a effective way of reducing the influence of confirmation bias.

ChatGPT – is a great troubleshooting assistant – latest area – DNS.

If you don’t deal with DNS often, it can be a pain to troubleshoot. When it is working, you don’t touch it. When you need to change it, like when testing new sites (e.g. setting up staging sites on subdomains), I find it challenging at times. Staging sites are often protected, so they are not confused with production site Especially since the DNS is rarely your main focus – you just want it to work.

I use Cloudflare to manage my DNS on all my sites- as I have for 5+ years. It is easy to configure and changes are typically propagated in seconds. It does my CDN/caching – so I can flush that easily if I make DNS changes. But occasionally, I find myself with unexpected behaviors – like redirects.

DNS troubleshooting is the latest activity that I involved ChatGPT with – one of my 500+ exchanges with this remarkable chat-bot over the last month. Here was my exchange in the middle of a chat involved a staging website.

ME: Yes clearing cache on Cloudflare helped, now I am having a issue with an unexpected redirect. How can I trace the source of a redirect on sites that I manage? Here is what is happening: I try to go to staging2.mysite.com and it is redirected to mysite.com. If I go to staging4.mysite.com it works fine and is not redirected. DNS looks the same.

ChatGPT: If you’re experiencing unexpected redirects on your website, there are a few things you can do to trace the source of the redirect:

  1. Check your Nginx or Apache configuration files for any redirect rules. These files are usually located in the /etc/nginx or /etc/httpd directory and should contain any rules for redirecting traffic.
  2. Check the .htaccess file located in the root of your web directory. This file is used to control web server configuration, and it’s where many redirect rules are placed.
  3. Check your WordPress configuration. If you’re using a plugin or theme that includes redirect functionality, it might be causing the issue. You can check the plugin or theme settings or disable them to see if it resolves the issue.
  4. Check for any Cloudflare page rules, if you are using Cloudflare and you have set up page rules that redirects some of your URLs.
  5. Check for any DNS records, if you have any CNAME or A records that redirects some of your URLs.
  6. Inspect the network tab in your browser developer tools, this will give you more information about the redirect that is happening, including the HTTP status code, the location of the redirect, and the number of redirects that are taking place.
  7. Use a tool like curl to check the headers, this will give you more information about the redirect that is happening and the headers that are involved in the process, like the location and the http status code.
  8. You can also try accessing the site using a different browser or device to see if the problem is specific to your current setup.

Most of these I had already checked – but if you had not, you could ask about an of them In my case I asked for help with #7 – Using curl. ChatGPT not only walked me through but help interpret the responses. In my cases, I found out the redirects were generated not by DNS or Cloudflare but by my web server.

My chat with ChatGPT on the outage of the FAA’s NOTAM system.

Even though ChatGPT is unaware of the outage of NOTAM on January 11, 2023.
It does a decent job discussing the early speculation about how it happened and
what can be done to remediate it.
Keep in mind that ChatGPT has a knowledge base that was cut off in September
2021. It does not even know the current official name of the NOTAM system. In
this and a few other instances I had to google things to refocus the conversation
something I have learned to do in my hundred+ chats with the remarkable
ChatGPT.
In the end, I don’t look for ChatGPT to regurgitate facts or recent events or be
100% accurate. But with a bit of effort it is a remarkable tool to evaluate
problems and provide analysis.