Author Archives: EzraSidran

General Staff: Black Powder Battle Designer Bundle on Steam

The General Staff: Black Powder Designer Bundle store on Steam. Click on image to go directly to the Steam store.

I am very pleased to announce that the Steam store for General Staff: Black Powder Battle Designer Bundle is now up and active. More importantly, if you are an early backer, you should have received your Steam key to download it by now. If you are an early backer and have not received an email with your Steam key, please contact me directly.

Some important things to know:

The Battle Designer Bundle does not include the actual game! The game is a different install package and, hopefully, will be in beta in the next month or two. If you are an early backer and received a Steam key for the Battle Designer Bundle you will also receive a second Steam key, when available, for the actual game and you will be welcome to participate in beta testing, too.

The Battle Designer Bundle includes everything you need to create your own armies, maps and scenarios for use in the actual game. The Battle Designer Bundle includes the Army Editor, the Map Editor and the Scenario Editor. The Map Editor supports a digitizing tablet (if you’re lucky enough to have one and the talent to use one, I don’t).

I need your suggestions for a battle that I can use to create video tutorials for the Army, Map and Scenario Editors. If you have suggestions, please contact me directly. However, it’s important to remember that I need a good Order of Battle (OOB) table that includes unit strengths. I also need a good quality map that is at least 1155 x 805 pixels (resolution). If it’s an old battle map, I need somebody to take the time to remove the units from the map. For example, here’s the original map of Antietam from the Library of Congress:

Map of the battle of Antietam from the Library of Congress. Willcox, William H. Map of the battlefield of Antietam. [Philada., Lith. of P. S. Duval & Son, 1862] Map. Click to enlarge.

And here it is after I cleaned it up, removed the units and rotated it 90 degrees:

The Antietam map after I removed all the units, cleaned it up, lightened it and rotated it 90 degrees. Click to enlarge.

I’m looking forward to receiving your scenario suggestions and creating the video tutorials. The tutorials will be posted here and on our YouTube channel.

 

Testing the MATE 2.0 Artificial Intelligence on the new Antietam Scenario

We’ve just added a video showing the MATE 2.0 tactical artificial intelligence playing Blue (Union Army of the Potomac) against Red (Confederate Army of Northern Virginia) at Antietam. This video also includes an announcement that we’ll be working on getting the Army Editor, Map Editor and Scenario Editor installation packages and keys ready on Steam.

Why the Pundits are Completely Wrong About AI

I have a lot of respect for Steve Wozniak – quite a bit less for Elon Musk 1)Though I have to admit losing $20 billion in a few months is impressive. – who both recently signed a letter calling for, “all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4.” Woz is a true computer hardware pioneer; but he’s certainly not an AI expert and Elon, well, I’m not sure where his expertise lies, but it’s not AI.

When it comes to creating AI capable of commanding troops on a battlefield, I am probably one of the world’s top experts on the subject (it’s not a crowded field). I’ve been writing and studying ‘computational military reasoning’ for my entire professional career, it was the subject of my doctoral thesis, I’ve written AI for numerous computer wargames and I’ve been a Principal Investigator for DARPA (Defense Advanced Research Project Agency) on this very subject.

I am confident in stating that no humans have been injured or died as a result of my work in computational military reasoning. However, the most recent NHTSA data reports that there have been at least, “419 crashes [and]… 18 definite fatalities of autonomous self-driving vehicles (like Mr. Musk’s Teslas). So, clearly, in some circumstances AI can be dangerous. In all fairness, I should state that the reason the self-driving autonomous vehicles keep having fatal crashes isn’t technically the AI; it’s that the AI has imperfect information about the world in which it operates. The AI for self-driving vehicles gets that information from cameras and radar (LIDAR would be good, too). However, Telsa just removed the radar from it’s vehicles (“Elon Musk Overruled Tesla Engineers Who Said Removing Radar Would Be Problematic: Report,”) leaving the AI even more in the dark about the world in which it operates. So, is the AI at fault or corporate management? Maybe the problem isn’t AI.

Furthermore, most of what’s being sold to the public as AI are just some string manipulation parlor tricks tacked on to an internet search. ChatGPT-4, which is making all the headlines these days, was recently accurately described:

“Put simply, ChatGPT takes an initial prompt and determines – on an individual, word by word basis – what most often comes next based on the existing texts that it has scanned throughout the internet. In Wolfram’s words, “it’s just adding one word at a time” – but doing it so quickly that it seems as though a robot is writing an original, whole block of text.

Essentially, ChatGPT is a gigantic version of Google autocomplete.” – ​AI or BS? How to tell if a marketing tool really uses artificial intelligence

I recently asked ChatGPT for a quote from U. S. Grant about war and it responded:

Actually, it was W. T. Sherman who said, “War is hell.” But, ChatGPT has no real intelligence. How it erroneously linked Grant to the quote I have no idea. The greatest fear we should have of ChatGPT is incorrect citations in reference papers. The creators of ChatGPT have clearly traded accuracy for glitz and hype; it’s not even a good internet search engine, but it sure seems impressive!

There’s one more thing you should know. There are two kinds of machine learning: supervised and unsupervised. Probably >95% of machine learning programs are ‘supervised’; which means they are ‘trained’ on a data set. Whenever you see the words ‘training’ in reference to machine learning you know it’s supervised. Here’s an example of supervised machine learning: Netflix movie recommendations. Every time you select a movie on Netflix you are training their system on your likes and dislikes. It does a great job, doesn’t it? No, it does a terrible job. It once recommended Sound of Music to me because I watched Das Boot. Makes perfect sense. They both take place during WWII.

What I’m saying is that there is no ‘there’ there. There is no intelligence there. Somebody at Netflix (at one time I read they employed out of work screenwriters) tagged both Das Boot and Sound of Music with the same descriptor; presumably ‘WWII’ or ‘war movie’ and that was all that was necessary for Netflix to make a terrible suggestion.

I work in unsupervised machine learning. It doesn’t search the internet, or look for similar words in a big data base. It tries to make sense of the world in which it operates (a historic battlefield) and attempts to make optimal decisions for moving units based on math, geometry, trigonometry and boolean logic.

That’s AI. And it’s not dangerous. Autonomous self-driving cars? They’re dangerous.

References

References
1 Though I have to admit losing $20 billion in a few months is impressive.

Video Walk-through of the Army, Map & Scenario Editors

I‘ve just uploaded a video of a walk-through of the General Staff: Black Powder Army Editor, Map Editor and Scenario Editor. These applications are completed. We will be using Steam for distribution. While we are registered with Steam, and they have given us ‘our space’, we still have to build it out and make arrangements for download keys for early backers. We (why do I keep using ‘we’, it’s just me here) truly appreciate your patience.

I will be posting a gameplay video of General Staff: Black Powder next. As always, please feel free to contact me directly.