WEBVTT 00:00:00.000 --> 00:00:03.819 Usually, programming a computer is kind of a 00:00:03.819 --> 00:00:06.360 master and servant dynamic. You write a line 00:00:06.360 --> 00:00:09.500 of code, and the machine just executes that line. 00:00:09.839 --> 00:00:12.400 You give it this really rigid sequence of steps, 00:00:12.740 --> 00:00:15.400 and it follows them blindly to the letter. Yeah, 00:00:15.400 --> 00:00:17.480 that's the standard paradigm. But there is a 00:00:17.480 --> 00:00:20.179 programming language that flips this relationship 00:00:20.179 --> 00:00:22.719 entirely. You don't tell the machine what to 00:00:22.719 --> 00:00:25.679 do step by step. You just tell it what is true. 00:00:26.709 --> 00:00:29.390 you let it figure out the rest. Which is a huge 00:00:29.390 --> 00:00:32.770 mental shift. Oh, absolutely. So today, for you, 00:00:32.909 --> 00:00:34.789 the learner listening right now, we are diving 00:00:34.789 --> 00:00:37.649 into a stack of sources detailing a language 00:00:37.649 --> 00:00:41.049 that has been quietly powering artificial intelligence 00:00:41.049 --> 00:00:44.939 and complex databases for, well... Over 50 years, 00:00:45.079 --> 00:00:47.060 we're unpacking Prolog. It's quite a legacy. 00:00:47.219 --> 00:00:49.679 It really is. And whether you are a seasoned 00:00:49.679 --> 00:00:51.600 software engineer or just someone fascinated 00:00:51.600 --> 00:00:54.299 by how machines think, this deep dive into our 00:00:54.299 --> 00:00:56.219 sources is going to challenge your most basic 00:00:56.219 --> 00:00:58.799 assumptions about problem solving. OK, let's 00:00:58.799 --> 00:01:01.359 unpack this. To truly grasp what Prolog represents, 00:01:01.539 --> 00:01:03.259 you really have to look at it as a bridge. A 00:01:03.259 --> 00:01:06.590 bridge. Yeah. On one side, there is formal human 00:01:06.590 --> 00:01:09.390 logic, like the way philosophers and mathematicians 00:01:09.390 --> 00:01:12.069 describe the world using relations, variables, 00:01:12.730 --> 00:01:15.349 absolute truths. Right, like formal proofs. Exactly. 00:01:15.569 --> 00:01:18.230 And then on the other side, you have cold, hard 00:01:18.230 --> 00:01:21.370 machine execution. Prologue was designed to be 00:01:21.370 --> 00:01:23.409 the infrastructure connecting those two worlds. 00:01:24.189 --> 00:01:26.890 It allows a user to compute complex answers by 00:01:26.890 --> 00:01:30.290 simply querying a set of logical relations. The 00:01:30.290 --> 00:01:32.069 sources show this language didn't just emerge 00:01:32.069 --> 00:01:35.140 in a vacuum, though. It was essentially born 00:01:35.140 --> 00:01:38.060 into a philosophical battleground in the 1970s. 00:01:38.079 --> 00:01:40.519 Oh yeah, it was highly contested. The story starts 00:01:40.519 --> 00:01:43.599 around 1972 at the University of Aix -Marseille 00:01:43.599 --> 00:01:46.859 in France. Two researchers, Alain Colmerauer 00:01:46.859 --> 00:01:49.120 and Philippe Roussel, developed this new system. 00:01:49.709 --> 00:01:52.209 And the name itself is basically a dead giveaway 00:01:52.209 --> 00:01:54.390 to its purpose. Right, it's an abbreviation for 00:01:54.390 --> 00:01:57.250 the French programmation en logique. Programming 00:01:57.250 --> 00:01:59.629 in logic. Exactly. And the academic foundations 00:01:59.629 --> 00:02:01.849 beneath it were pretty dense. The language was 00:02:01.849 --> 00:02:04.290 built on Robert Kowalski's procedural interpretation 00:02:04.290 --> 00:02:07.010 of what are known as horn clauses. Okay, horn 00:02:07.010 --> 00:02:10.090 clauses. That sounds intense. It's jargon. But 00:02:10.090 --> 00:02:13.050 to strip that away, a horn clause is essentially 00:02:13.050 --> 00:02:16.110 a specific, highly restricted type of logical 00:02:16.110 --> 00:02:19.229 formula. Think of it as a strict if -then structure. 00:02:19.430 --> 00:02:21.710 Like, if this happens, then that happens. Sort 00:02:21.710 --> 00:02:24.669 of. It allows you to say, if condition A and 00:02:24.669 --> 00:02:28.189 condition B are met, then conclusion C is definitively 00:02:28.189 --> 00:02:31.770 true. And the motivation here was deeply practical. 00:02:32.050 --> 00:02:34.990 How so? Well, these researchers wanted to reconcile 00:02:34.990 --> 00:02:38.090 two competing ideas in computer science. On one 00:02:38.090 --> 00:02:40.849 hand, using pure logic as a declarative way to 00:02:40.849 --> 00:02:44.270 represent knowledge, and on the other, the procedural 00:02:44.270 --> 00:02:46.629 step -by -step representation of knowledge that 00:02:46.629 --> 00:02:49.389 was, you know, dominating North America at the 00:02:49.389 --> 00:02:51.689 time. And that tension brings us to what the 00:02:51.689 --> 00:02:54.509 sources describe as the transatlantic rivalry. 00:02:54.889 --> 00:02:57.389 Reading through the historical context, the computer 00:02:57.389 --> 00:02:59.770 science world was practically split in two. It 00:02:59.770 --> 00:03:02.490 really was. European AI researchers fiercely 00:03:02.490 --> 00:03:05.110 championed Prologue, while American AI researchers 00:03:05.110 --> 00:03:07.210 were firmly entrenched in a different language 00:03:07.210 --> 00:03:09.909 called Lisp. Yeah, the Lisp versus Prologue debate. 00:03:10.129 --> 00:03:11.930 And these weren't polite academic disagreements 00:03:11.930 --> 00:03:15.030 either. There were fierce, almost nationalistic 00:03:15.030 --> 00:03:17.469 debates over which language was superior. Because 00:03:17.469 --> 00:03:19.629 it was a debate about the very nature of intelligence, 00:03:19.629 --> 00:03:23.210 really, and how to digitally model it. The American 00:03:23.210 --> 00:03:25.509 approach with Lisp was highly functional and 00:03:25.509 --> 00:03:28.430 flexible, focusing on list processing. But the 00:03:28.430 --> 00:03:30.729 European approach with Prologue was basically 00:03:30.729 --> 00:03:34.069 betting the entire house on formal logic as the 00:03:34.069 --> 00:03:36.930 singular foundation of artificial intelligence. 00:03:37.270 --> 00:03:39.610 To make this tangible for you listening, think 00:03:39.610 --> 00:03:42.680 about it like cooking. Traditional procedural 00:03:42.680 --> 00:03:44.840 programming, which is what most of the software 00:03:44.840 --> 00:03:47.680 world still uses today with languages like C, 00:03:47.900 --> 00:03:51.199 Python, or Java, is like giving a chef a hyper 00:03:51.199 --> 00:03:54.219 -specific step -by -step recipe. Down to the 00:03:54.219 --> 00:03:57.080 exact measurements. Right. Take two eggs, crack 00:03:57.080 --> 00:03:59.199 them into a bowl, whisk for 10 seconds, turn 00:03:59.199 --> 00:04:02.219 the stove to medium. You are micromanaging the 00:04:02.219 --> 00:04:04.939 entire process. Trolog, being a declarative language, 00:04:05.360 --> 00:04:06.780 operates on a completely different paradigm. 00:04:06.840 --> 00:04:08.419 It's a totally different mindset. It is like 00:04:08.419 --> 00:04:10.180 walking into the kitchen and just describing 00:04:10.180 --> 00:04:12.539 the perfect omelet to the chef. An omelet is 00:04:12.539 --> 00:04:15.300 made of eggs. It is fluffy. It is cooked. Yep. 00:04:15.620 --> 00:04:17.600 You define the parameters of the truth, and then 00:04:17.600 --> 00:04:19.360 you leave the kitchen. The chef figures out how 00:04:19.360 --> 00:04:22.079 to make it happen. That analogy perfectly captures 00:04:22.079 --> 00:04:24.720 the shifting control flow. You are defining the 00:04:24.720 --> 00:04:26.839 relationships and the end goal, not the mechanics 00:04:26.839 --> 00:04:29.560 of the execution. And if we connect this to the 00:04:29.560 --> 00:04:32.139 bigger picture, this idea was so revolutionary 00:04:32.139 --> 00:04:35.759 at the time that it sparked some massive, incredibly 00:04:35.759 --> 00:04:38.259 ambitious technological gambles. Oh, like the 00:04:38.259 --> 00:04:41.339 Japanese project. Exactly. The most famous one, 00:04:41.459 --> 00:04:43.620 heavily detailed on our sources, was the Japanese 00:04:43.620 --> 00:04:46.579 fifth -generation computer systems project. the 00:04:46.579 --> 00:04:50.259 FGCS. This launched in the early 1980s. And they 00:04:50.259 --> 00:04:52.699 went all in. They essentially bet the future 00:04:52.699 --> 00:04:55.519 of their entire computing industry on logic programming. 00:04:55.980 --> 00:04:58.279 They didn't just write software, they built their 00:04:58.279 --> 00:05:01.660 entire operating system on a variant of Prolog 00:05:01.660 --> 00:05:04.300 called kernel language. And their goal for this 00:05:04.300 --> 00:05:06.930 hardware was just I mean, they were aiming for 00:05:06.930 --> 00:05:09.310 up to 1 billion logical inferences per second, 00:05:09.850 --> 00:05:12.810 a GLPS. Right, a GLPS. And keep in mind the technological 00:05:12.810 --> 00:05:16.170 baseline of that era. In 1982, standard computers 00:05:16.170 --> 00:05:19.170 were operating at around like 10 ,000 to 100 00:05:19.170 --> 00:05:21.310 ,000 logical inferences per second. So they were 00:05:21.310 --> 00:05:23.360 trying to jump light years ahead. The Japanese 00:05:23.360 --> 00:05:25.699 project was attempting to scale that metric up 00:05:25.699 --> 00:05:28.500 by orders of magnitude. And they weren't just 00:05:28.500 --> 00:05:31.019 writing better code to achieve this. They were 00:05:31.019 --> 00:05:34.220 literally hardwiring Prolog's unique execution 00:05:34.220 --> 00:05:37.639 model into the physical silicon architecture 00:05:37.639 --> 00:05:40.439 of the machines. Designing physical hardware 00:05:40.439 --> 00:05:43.420 specifically to process logical deductions is 00:05:43.420 --> 00:05:46.160 such a wild leap. It makes me wonder how this 00:05:46.160 --> 00:05:48.360 logic engine actually works under the hood. It's 00:05:48.360 --> 00:05:50.569 actually surprisingly elegant. Yeah. The sources 00:05:50.569 --> 00:05:52.329 break down the mechanics, and it starts with 00:05:52.329 --> 00:05:55.129 a really simple foundation. In Prolog, everything 00:05:55.129 --> 00:05:57.470 is based on a single data type called the term. 00:05:58.129 --> 00:06:00.259 A term can be an atom. which is just a simple 00:06:00.259 --> 00:06:03.120 lowercase name like red or apple. It can be a 00:06:03.120 --> 00:06:05.920 number. It can be a variable which acts as a 00:06:05.920 --> 00:06:09.000 capitalized placeholder like x or person. Or 00:06:09.000 --> 00:06:11.600 it can be a compound term which nests these things 00:06:11.600 --> 00:06:14.180 together to show relationships. Those terms are 00:06:14.180 --> 00:06:16.639 the building blocks. And a Prolog program itself 00:06:16.639 --> 00:06:19.060 doesn't look like normal code. There are no loops, 00:06:19.319 --> 00:06:21.879 no print statements, no step -by -step functions. 00:06:22.120 --> 00:06:24.360 None of the usual stuff. Right. It is really 00:06:24.360 --> 00:06:27.819 just a database of facts and rules. A fact is 00:06:27.819 --> 00:06:30.620 a simple, unconditional assertion of truth. So 00:06:30.620 --> 00:06:32.500 you could write a fact into the system that simply 00:06:32.500 --> 00:06:35.319 says Socrates is human. Just a bold, undeniable 00:06:35.319 --> 00:06:37.759 statement loaded right into the database. Exactly. 00:06:38.379 --> 00:06:41.160 Then you introduce rules. A rule dictates that 00:06:41.160 --> 00:06:43.800 a certain conclusion is true only if a specific 00:06:43.800 --> 00:06:46.399 set of other facts are true. Okay. Using our 00:06:46.399 --> 00:06:48.120 previous example, you could write a rule, all 00:06:48.120 --> 00:06:51.269 humans are mortal. Translated into Prolog syntax, 00:06:51.389 --> 00:06:53.529 you are essentially telling the machine X is 00:06:53.529 --> 00:06:56.730 mortal, I, F, X is human. So the machine now 00:06:56.730 --> 00:06:59.050 has a database of universal truths and conditional 00:06:59.050 --> 00:07:02.089 rules. And the user interacts with this by submitting 00:07:02.089 --> 00:07:04.069 a query. Right, you ask it a question. Yeah, 00:07:04.110 --> 00:07:06.050 after the computer. Like, is Socrates mortal? 00:07:06.389 --> 00:07:08.490 The sources mention the engine attempts to prove 00:07:08.490 --> 00:07:12.930 this by finding a refutation of the negated query 00:07:12.930 --> 00:07:16.170 using a method called SLD resolution. Which is 00:07:16.170 --> 00:07:18.209 a mouthful. Yeah, let me try to translate that 00:07:18.209 --> 00:07:19.959 jargon. because it sounds like a legal defense 00:07:19.959 --> 00:07:22.620 strategy or something. From what I gather, the 00:07:22.620 --> 00:07:24.759 computer basically assumes your query is false 00:07:24.759 --> 00:07:27.240 and then searches through its database of facts 00:07:27.240 --> 00:07:29.920 to find a contradiction. That's spot on. It is 00:07:29.920 --> 00:07:32.500 like a detective proving a suspect is guilty 00:07:32.500 --> 00:07:35.120 by proving their alibi is physically impossible. 00:07:35.339 --> 00:07:37.899 That is an excellent way to conceptualize SLD 00:07:37.899 --> 00:07:41.300 resolution. Prologue assumes Socrates is not 00:07:41.300 --> 00:07:44.500 mortal. It then looks at the rule X is mortal 00:07:44.500 --> 00:07:48.240 if X is human. OK. It looks at the fact Socrates 00:07:48.240 --> 00:07:52.540 is human. It realizes the assumption that Socrates 00:07:52.540 --> 00:07:54.899 is not mortal creates a logical contradiction. 00:07:55.519 --> 00:07:58.600 Therefore, the original query must be true. So 00:07:58.600 --> 00:08:01.360 it proves it by exhausting the alternative. But 00:08:01.360 --> 00:08:03.779 wait, if I just give the computer a massive sprawling 00:08:03.779 --> 00:08:06.480 pile of thousands of facts and rules and it just 00:08:06.480 --> 00:08:08.579 blindly searches for contradictions to answer 00:08:08.579 --> 00:08:10.939 my query, what happens when it goes down the 00:08:10.939 --> 00:08:13.379 wrong path? Now we're getting to the catch. Right. 00:08:13.600 --> 00:08:16.579 If I ask a highly complex question with dozens 00:08:16.579 --> 00:08:18.839 of variables, mathematically that sounds like 00:08:18.839 --> 00:08:21.589 a nightmare for processing power. Surely, in 00:08:21.589 --> 00:08:24.050 the real world, that relentless searching would 00:08:24.050 --> 00:08:26.930 just bring a computer to its knees from the sheer 00:08:26.930 --> 00:08:29.730 volume of possibilities. You've identified the 00:08:29.730 --> 00:08:31.990 core mechanical challenge of the language. This 00:08:31.990 --> 00:08:35.210 leads directly to Prolog's defining execution 00:08:35.210 --> 00:08:38.129 strategy, which is called chronological backtracking. 00:08:38.350 --> 00:08:40.990 Chronological backtracking? Yes. The system doesn't 00:08:40.990 --> 00:08:44.210 guess randomly. It explores the options systematically, 00:08:44.750 --> 00:08:47.129 mapping out a massive decision tree. Imagine 00:08:47.129 --> 00:08:50.190 navigating a really complex maze. OK, so if I 00:08:50.190 --> 00:08:52.629 am the prolog engine in this maze, and I hit 00:08:52.629 --> 00:08:55.149 an intersection with three possible paths. I 00:08:55.149 --> 00:08:57.809 create a choice point. Exactly. I decide to take 00:08:57.809 --> 00:09:00.169 the left path, binding my variables to the facts 00:09:00.169 --> 00:09:02.409 down that corridor. But let's say I hit a dead 00:09:02.409 --> 00:09:04.690 end. The facts don't support the rule. Instead 00:09:04.690 --> 00:09:06.990 of crashing or throwing an error, the engine 00:09:06.990 --> 00:09:09.269 just stops. It stops and then it backtracks. 00:09:09.509 --> 00:09:12.389 It undoes every single variable binding it made 00:09:12.389 --> 00:09:15.090 since that last intersection. It literally walks 00:09:15.090 --> 00:09:17.529 backward through the maze to the previous choice 00:09:17.529 --> 00:09:19.789 point and then tries the middle path. If that 00:09:19.789 --> 00:09:22.629 fails, it backtracks again and tries the right 00:09:22.629 --> 00:09:25.549 path. That's relentless. It searches this massive 00:09:25.549 --> 00:09:28.389 tree of possibilities dynamically moving backwards 00:09:28.389 --> 00:09:31.370 and forwards until it either constructs a flawless 00:09:31.370 --> 00:09:35.330 logical proof or exhausts every single conceivable 00:09:35.330 --> 00:09:38.289 option and returns a definitive false. So it 00:09:38.289 --> 00:09:40.750 will stubbornly try every combination until it 00:09:40.750 --> 00:09:43.629 finds the truth. Conceptually that sounds beautiful. 00:09:43.950 --> 00:09:47.690 It is pure, relentless logic. It is. But computationally, 00:09:47.850 --> 00:09:50.370 backtracking sounds incredibly heavy. Which brings 00:09:50.370 --> 00:09:52.950 us to the biggest historical criticisms of Prologue 00:09:52.950 --> 00:09:56.070 outlined in our sources, and the somewhat controversial 00:09:56.070 --> 00:09:58.029 compromises programmers had to make to get it 00:09:58.029 --> 00:10:00.429 to function in the real world. Yeah, the purity 00:10:00.429 --> 00:10:02.850 of the logic engine came with a severe cost. 00:10:03.309 --> 00:10:05.490 Because it relied on this exhaustive search method, 00:10:05.889 --> 00:10:07.870 software development Prologue historically suffered 00:10:07.870 --> 00:10:11.169 a massive performance penalty compared to conventional, 00:10:11.389 --> 00:10:14.809 procedural languages like C. just runs straight 00:10:14.809 --> 00:10:17.350 down the compiled instructions, while Prolog 00:10:17.350 --> 00:10:20.149 is busy wandering through a maze, checking every 00:10:20.149 --> 00:10:23.009 single branch in dead -end. Precisely. If you 00:10:23.009 --> 00:10:26.090 are executing a deterministic computation, meaning 00:10:26.090 --> 00:10:28.389 there is only one correct path to the answer, 00:10:28.750 --> 00:10:30.909 and you don't need the machine to explore multiple 00:10:30.909 --> 00:10:34.080 alternatives, Prolog's built -in backtracking 00:10:34.080 --> 00:10:37.299 mechanism is a colossal waste of computing resources. 00:10:37.460 --> 00:10:40.139 It's doing too much work. Way too much. It spends 00:10:40.139 --> 00:10:42.600 time setting up choice points and preparing to 00:10:42.600 --> 00:10:44.480 backtrack for scenarios that will never actually 00:10:44.480 --> 00:10:47.100 happen. So if the backtracking is the bottleneck, 00:10:47.240 --> 00:10:49.019 I imagine programmers had to find a way to put 00:10:49.019 --> 00:10:51.539 blinders on the engine. They needed a mechanism 00:10:51.539 --> 00:10:53.840 to tell the system, hey, you found a good enough 00:10:53.840 --> 00:10:56.559 path, stop looking at the other doors. They did, 00:10:56.659 --> 00:10:58.840 and they called it the cut. The cut? The cut 00:10:58.840 --> 00:11:01.700 is a specific operator, an exclamation point 00:11:01.700 --> 00:11:04.039 in the syntax, that a programmer manually inserts 00:11:04.039 --> 00:11:06.879 into the code. It explicitly commands the prolog 00:11:06.879 --> 00:11:09.620 engine, once you make this choice, commit to 00:11:09.620 --> 00:11:12.399 this path. Do not backtrack past this point. 00:11:12.559 --> 00:11:15.580 Wow. Yeah, it forcibly introduces a deterministic 00:11:15.580 --> 00:11:18.649 path into a non -deterministic engine. The irony 00:11:18.649 --> 00:11:21.009 there is thick. I mean, you come to a language 00:11:21.009 --> 00:11:24.289 like prologue for the absolute purity of declarative 00:11:24.289 --> 00:11:26.509 logic. You just want to describe the problem 00:11:26.509 --> 00:11:29.210 to the chef and let them work. Right. But to 00:11:29.210 --> 00:11:31.110 make the program run fast enough so the computer 00:11:31.110 --> 00:11:33.070 doesn't freeze, you have to dirty your hands 00:11:33.070 --> 00:11:35.330 with procedural hacks. You have to step back 00:11:35.330 --> 00:11:37.169 into the kitchen and start micromanaging the 00:11:37.169 --> 00:11:39.710 search tree, manually locking doors in the maze. 00:11:40.710 --> 00:11:43.710 It is a profound philosophical compromise. The 00:11:43.710 --> 00:11:46.629 sources explicitly note that relying on cuts 00:11:46.629 --> 00:11:49.129 destroys one of Prologue's main attractions. 00:11:49.529 --> 00:11:52.509 It's purely declarative nature. Because now you're 00:11:52.509 --> 00:11:55.110 giving it steps again. Exactly. Once you start 00:11:55.110 --> 00:11:57.250 aggressively inserting cuts, you have to read 00:11:57.250 --> 00:11:59.470 the program procedurally to understand what it 00:11:59.470 --> 00:12:02.309 is doing. You have to trace the execution steps 00:12:02.309 --> 00:12:04.649 in your head rather than simply reading the logical 00:12:04.649 --> 00:12:06.990 truths. That's a shame. Furthermore, you lose 00:12:06.990 --> 00:12:09.269 the ability to run programs backwards and forwards, 00:12:09.350 --> 00:12:12.029 which is arguably one of the most magical properties 00:12:12.029 --> 00:12:14.580 of pure logic. programming. Let's expand on that 00:12:14.580 --> 00:12:17.620 magic because the concept of running code backwards 00:12:17.620 --> 00:12:20.460 is entirely foreign to someone used to standard 00:12:20.460 --> 00:12:23.559 programming. Oh, it's fascinating. In Pure Prolog, 00:12:23.940 --> 00:12:26.299 a single logical relationship can be queried 00:12:26.299 --> 00:12:29.279 in multiple directions. Imagine you write a standard 00:12:29.279 --> 00:12:31.820 rule for concatenating or joining two lists together. 00:12:32.059 --> 00:12:34.740 In a procedural language, you give the function 00:12:34.740 --> 00:12:37.279 two lists, and it spits out the combined list. 00:12:37.679 --> 00:12:39.820 In pure Prolog, you can do that, but you can 00:12:39.820 --> 00:12:42.879 also do the reverse. Wait, really? Yeah. You 00:12:42.879 --> 00:12:45.200 can give the engine the combined list, leave 00:12:45.200 --> 00:12:48.240 the two input lists as blank variables, and ask 00:12:48.240 --> 00:12:50.779 the engine to find all the possible ways to split 00:12:50.779 --> 00:12:53.379 that large list back into two smaller ones. That 00:12:53.379 --> 00:12:56.539 is amazing. The exact same block of code computes 00:12:56.539 --> 00:12:59.340 both forwards and backwards. It just evaluates 00:12:59.340 --> 00:13:01.200 the logical relationship from different starting 00:13:01.200 --> 00:13:04.149 points. But the moment you add a procedural cut 00:13:04.149 --> 00:13:07.090 to optimize the performance, that bi -directional 00:13:07.090 --> 00:13:09.809 flexibility is permanently broken. So you trade 00:13:09.809 --> 00:13:12.669 mathematical beauty for execution speed. And 00:13:12.669 --> 00:13:14.830 the sources point out this wasn't the only hurdle 00:13:14.830 --> 00:13:17.809 for the language. Building massive enterprise 00:13:17.809 --> 00:13:20.190 -level applications, what they call programming 00:13:20.190 --> 00:13:23.730 in the large, was incredibly difficult due to 00:13:23.730 --> 00:13:25.909 the severe module fragmentation. Right. Yes. 00:13:26.120 --> 00:13:29.440 For a very long time, the creators of major Prolog 00:13:29.440 --> 00:13:31.799 compilers couldn't agree on a standardized module 00:13:31.799 --> 00:13:34.000 system. And a module system is basically how 00:13:34.000 --> 00:13:38.179 you break a massive software program into smaller, 00:13:38.919 --> 00:13:41.460 manageable, isolated pieces that can talk to 00:13:41.460 --> 00:13:44.179 each other safely, right? Correct. Without a 00:13:44.179 --> 00:13:46.580 standard, code written for one Prolog system 00:13:46.580 --> 00:13:48.740 often just wouldn't work on another. Reading 00:13:48.740 --> 00:13:50.740 the timeline in our sources is almost comical. 00:13:51.080 --> 00:13:53.220 The ISO standard for the core Prolog language 00:13:53.220 --> 00:13:57.539 was published in 1995. But part two, which standardized 00:13:57.539 --> 00:13:59.980 the module system, didn't arrive until the year 00:13:59.980 --> 00:14:02.500 2000. It took forever. And part three of the 00:14:02.500 --> 00:14:04.919 ISO standard, which covers definite clause grammars, 00:14:05.279 --> 00:14:07.659 a crucial tool for parsing language, that was 00:14:07.659 --> 00:14:10.679 just published in June 2025. I know, it's unbelievable. 00:14:10.980 --> 00:14:13.120 It took the international community over 50 years 00:14:13.120 --> 00:14:15.360 to standardize that specific part of the language. 00:14:15.759 --> 00:14:18.000 Looking at the performance penalties, the procedural 00:14:18.000 --> 00:14:20.559 hacks, and a half century of standardization 00:14:20.559 --> 00:14:23.659 delays, it begs the question, Did Prolog just 00:14:23.659 --> 00:14:26.440 fail? Did the procedural languages like C and 00:14:26.440 --> 00:14:29.200 Java completely win the war? Prolog didn't fail. 00:14:29.360 --> 00:14:33.100 It evolved to survive. How so? The academic and 00:14:33.100 --> 00:14:35.840 developer community recognized the severe processing 00:14:35.840 --> 00:14:38.220 bottlenecks associated with backtracking, and 00:14:38.220 --> 00:14:40.879 they developed brilliant algorithmic solutions. 00:14:41.720 --> 00:14:43.580 One of the most significant breakthroughs was 00:14:43.580 --> 00:14:46.279 a technique called tabling, which is a form of 00:14:46.279 --> 00:14:48.720 memoization. Memo -ization, that's essentially 00:14:48.720 --> 00:14:50.720 the computer taking notes as it works, correct? 00:14:50.879 --> 00:14:53.820 Exactly. It is a space -time trade -off. Systems 00:14:53.820 --> 00:14:57.940 like XSB and modern SWI Prolog implemented tabling 00:14:57.940 --> 00:15:00.360 to save the logic engine from endlessly repeating 00:15:00.360 --> 00:15:03.480 its own work. OK. As Prolog evaluates a complex 00:15:03.480 --> 00:15:06.840 query and navigates the maze, it stores its intermediate 00:15:06.840 --> 00:15:10.440 findings in memory in a literal table. If it 00:15:10.440 --> 00:15:12.620 wanders down a path and encounters the exact 00:15:12.620 --> 00:15:15.139 same subgoal it has already solved, it doesn't 00:15:15.139 --> 00:15:17.240 recalculate it. It just looks up the answer in 00:15:17.240 --> 00:15:19.940 the table. So you sacrifice some memory space 00:15:19.940 --> 00:15:22.559 to drastically cut down the execution time. That 00:15:22.559 --> 00:15:24.820 sounds like a standard optimization, but how 00:15:24.820 --> 00:15:27.159 does it save the system from crashing? Because 00:15:27.159 --> 00:15:30.019 it solves the fatal flaw of infinite recursive 00:15:30.019 --> 00:15:32.759 loops. Imagine you are building a family tree 00:15:32.759 --> 00:15:34.940 application in Prolog, and you ask the engine 00:15:34.940 --> 00:15:37.700 to find all of someone's ancestors. In a pure 00:15:37.700 --> 00:15:40.799 depth -first search, if the data has a circular 00:15:40.799 --> 00:15:44.120 loop, say, two distant cousins married, creating 00:15:44.120 --> 00:15:47.000 a loop in the lineage, the Prolog engine will 00:15:47.000 --> 00:15:50.019 get trapped in that circle. It'll just keep backtracking 00:15:50.019 --> 00:15:52.220 and stepping forward infinitely until the computer 00:15:52.220 --> 00:15:55.259 runs out of memory and crashes. Oh, I see. Tabling 00:15:55.259 --> 00:15:58.039 breaks the loop. The engine checks the table, 00:15:58.419 --> 00:16:00.899 sees it has already evaluated that specific person, 00:16:01.440 --> 00:16:04.360 realizes it is in a cycle, and forces the search 00:16:04.360 --> 00:16:06.840 down a different path. It makes the language 00:16:06.840 --> 00:16:09.720 vastly more robust for complex, messy reasoning 00:16:09.720 --> 00:16:13.399 tasks. Tabling saves it from endless loops. And 00:16:13.399 --> 00:16:15.960 that ability to handle massive, complex webs 00:16:15.960 --> 00:16:19.220 of logic without crashing is exactly why Prologue 00:16:19.220 --> 00:16:21.679 didn't die out, but instead became a secret weapon 00:16:21.679 --> 00:16:23.740 for modern tech giants. It definitely found its 00:16:23.740 --> 00:16:26.679 specific uses. Despite the academic debates and 00:16:26.679 --> 00:16:29.360 the reliance on cuts, Prologue found incredibly 00:16:29.360 --> 00:16:31.980 specific high -stakes niches where traditional 00:16:31.980 --> 00:16:34.779 procedural languages completely stumbled. Let's 00:16:34.779 --> 00:16:37.159 look at where this 1970s logic engine is hiding 00:16:37.159 --> 00:16:40.000 in plain sight today. Prologue's unique architecture 00:16:40.000 --> 00:16:42.480 makes it perfectly suited for domains that require 00:16:42.480 --> 00:16:46.460 complex rule evaluation, namely, expert systems, 00:16:47.039 --> 00:16:49.440 theorem proving, and natural language processing. 00:16:50.059 --> 00:16:52.039 The most prominent example in our sources is 00:16:52.039 --> 00:16:54.600 IBM Watson. When Watson went on the game show 00:16:54.600 --> 00:16:56.879 Jeopardy and systematically crushed the human 00:16:56.879 --> 00:16:59.779 champions, Prologue was functioning as a critical 00:16:59.779 --> 00:17:02.720 component of its cognitive architecture. The 00:17:02.720 --> 00:17:05.480 developers at IBM needed a language capable of 00:17:05.480 --> 00:17:07.920 expressing highly complex pattern matching rules 00:17:07.920 --> 00:17:10.880 over natural language parse trees. And to break 00:17:10.880 --> 00:17:13.680 down why a parse tree is basically a logic puzzle, 00:17:14.579 --> 00:17:16.720 think of a sentence like the quick brown fox. 00:17:17.710 --> 00:17:20.170 Procedural code struggles to understand the contextual 00:17:20.170 --> 00:17:22.349 relationship between those arbitrary words. Just 00:17:22.349 --> 00:17:25.410 too rigid for that. Exactly. But if you mathematically 00:17:25.410 --> 00:17:27.450 map that sentence into a tree of grammatical 00:17:27.450 --> 00:17:29.769 rules, where a noun definitively connects to 00:17:29.769 --> 00:17:32.529 an adjective which modifies a verb, suddenly 00:17:32.529 --> 00:17:35.890 messy human language becomes a strict logic equation. 00:17:36.269 --> 00:17:38.750 And Prologue was specifically designed to instantly 00:17:38.750 --> 00:17:40.849 hunt through massive trees of logical rules. 00:17:41.309 --> 00:17:43.819 Right. That meant it could parse jeopardy clues, 00:17:44.559 --> 00:17:47.279 identify the subject, and evaluate the grammatical 00:17:47.279 --> 00:17:49.839 relationships faster than any other language 00:17:49.839 --> 00:17:52.180 IBM experimented with. What's fascinating here 00:17:52.180 --> 00:17:55.279 is the IBM engineers explicitly stated that Prologue 00:17:55.279 --> 00:17:58.579 was the ideal choice due to its simplicity and 00:17:58.579 --> 00:18:01.319 expressiveness for that exact task. It allowed 00:18:01.319 --> 00:18:03.940 them to write clean, declarative rules for English 00:18:03.940 --> 00:18:06.599 grammar rather than thousands of lines of procedural 00:18:06.599 --> 00:18:09.779 code trying to anticipate every possible sentence 00:18:09.779 --> 00:18:11.900 structure. That's incredible. But it isn't solely 00:18:11.900 --> 00:18:14.759 utilized by supercomputers. We see it in modern 00:18:14.759 --> 00:18:17.119 open source infrastructure as well. Consider 00:18:17.119 --> 00:18:20.180 TerminusDB. Oh, right. It's an open source graph 00:18:20.180 --> 00:18:22.619 database designed for collaboratively building 00:18:22.619 --> 00:18:25.599 massive knowledge graphs. And the entire system 00:18:25.599 --> 00:18:28.700 is implemented in Prolog. A knowledge graph is... 00:18:28.619 --> 00:18:31.619 at its core, a massive web of connected facts. 00:18:31.779 --> 00:18:34.400 It links people, places, concepts. It makes perfect 00:18:34.400 --> 00:18:36.880 sense. I mean, what better tool to query and 00:18:36.880 --> 00:18:39.440 navigate a sprawling database of logical relations 00:18:39.440 --> 00:18:42.380 than a programming language built entirely around 00:18:42.380 --> 00:18:44.319 logical relations? Exactly. It's the perfect 00:18:44.319 --> 00:18:46.359 fit. Here's where it gets really interesting, 00:18:46.500 --> 00:18:48.900 though. Buried deep in the history section of 00:18:48.900 --> 00:18:51.700 our sources is my absolute favorite application. 00:18:52.140 --> 00:18:54.819 We've talked about IBM Watson parsing Jeopardy! 00:18:54.819 --> 00:18:57.559 clues, but we also have to talk about Sega. The 00:18:57.559 --> 00:19:01.259 video game company. Yes. In 1986, Sega released 00:19:01.259 --> 00:19:04.299 the Sega AI computer exclusively for the Japanese 00:19:04.299 --> 00:19:06.980 market, and the operating system utilized Prolog. 00:19:07.119 --> 00:19:09.759 They utilized it specifically for reading Japanese 00:19:09.759 --> 00:19:12.779 natural language inputs via a specialized touchpad. 00:19:13.000 --> 00:19:15.910 It is wild to trace that lineage. A theoretical 00:19:15.910 --> 00:19:17.809 language born in the university in France in 00:19:17.809 --> 00:19:20.769 1972, built entirely on the philosophy of formal 00:19:20.769 --> 00:19:23.390 logic, ends up parsing Japanese language inputs 00:19:23.390 --> 00:19:26.410 on a Sega console in the 1980s, and then helps 00:19:26.410 --> 00:19:29.049 an IBM supercomputer win Jeopardy! decades later. 00:19:29.200 --> 00:19:31.420 It really underscores the deep versatility of 00:19:31.420 --> 00:19:33.440 the language. It highlights a fundamental truth 00:19:33.440 --> 00:19:36.720 about computer science, really. Prolog is Turing 00:19:36.720 --> 00:19:39.420 complete. Meaning what, exactly? That means anything 00:19:39.420 --> 00:19:42.700 you can compute with C, Java, or Python, you 00:19:42.700 --> 00:19:45.380 can technically compute with Prolog. It simply 00:19:45.380 --> 00:19:47.420 approaches the computation from a completely 00:19:47.420 --> 00:19:50.539 different paradigm. It views computation as a 00:19:50.539 --> 00:19:53.559 sequence of logical state transitions, navigating 00:19:53.559 --> 00:19:56.960 a landscape of truths, rather than a linear sequence 00:19:56.960 --> 00:19:59.599 of hardware instructions. fundamentally shifts 00:19:59.599 --> 00:20:02.700 how you approach a problem. And that brings us 00:20:02.700 --> 00:20:05.400 to the end of our sources today. Wrapping up 00:20:05.400 --> 00:20:07.720 this deep dive, it's clear that Prolog isn't 00:20:07.720 --> 00:20:11.019 just a relic of the AI Cold War, nor is it just 00:20:11.019 --> 00:20:14.160 an academic curiosity. Far from it. It is a living 00:20:14.160 --> 00:20:16.500 testament to the idea that sometimes the best 00:20:16.500 --> 00:20:19.640 way to solve an incredibly complex problem isn't 00:20:19.640 --> 00:20:21.980 to meticulously tell the computer how to do every 00:20:21.980 --> 00:20:24.740 little thing. Sometimes the most powerful approach 00:20:24.740 --> 00:20:27.240 is to just teach the machine what is true, step 00:20:27.240 --> 00:20:29.339 out of the way, and let it find the path through 00:20:29.339 --> 00:20:32.000 the maze itself. For you listening, engaging 00:20:32.000 --> 00:20:34.619 with the concepts behind a language like Prologue, 00:20:34.619 --> 00:20:36.660 even if you never write a single line of code, 00:20:36.819 --> 00:20:39.279 expands your critical thinking. It trains you 00:20:39.279 --> 00:20:41.460 to separate the definition of a problem from 00:20:41.460 --> 00:20:44.690 the execution of its solution. In our modern, 00:20:44.950 --> 00:20:47.029 highly procedural world where we are constantly 00:20:47.029 --> 00:20:49.950 focused on the steps to achieve something, focusing 00:20:49.950 --> 00:20:52.849 purely on the truth of the system is a rare and 00:20:52.849 --> 00:20:55.710 valuable perspective. It rewires your brain to 00:20:55.710 --> 00:20:58.089 look at the destination before plotting the steps. 00:20:58.430 --> 00:21:01.390 It does. And analyzing this history leaves us 00:21:01.390 --> 00:21:04.220 with a lingering question about the future. We 00:21:04.220 --> 00:21:06.099 discussed how the Japanese fifth -generation 00:21:06.099 --> 00:21:08.539 project failed in the 1980s because they tried 00:21:08.539 --> 00:21:10.960 to build physical hardware specifically optimized 00:21:10.960 --> 00:21:13.720 for prologue's logic and standard general -purpose 00:21:13.720 --> 00:21:15.839 chips eventually outpaced them. Right, the general 00:21:15.839 --> 00:21:18.500 -purpose chips went out. But today, the computing 00:21:18.500 --> 00:21:21.079 demands of modern AI are hitting physical limits. 00:21:21.700 --> 00:21:23.920 Researchers are now developing neuromorphic chips 00:21:23.920 --> 00:21:26.339 hardware that physically mimics the synapses 00:21:26.339 --> 00:21:28.900 of a biological brain rather than relying on 00:21:28.900 --> 00:21:32.059 binary math. This raises a fascinating possibility. 00:21:32.299 --> 00:21:34.619 As we hit the ceiling of general purpose chips, 00:21:34.880 --> 00:21:37.019 could the future of artificial intelligence be 00:21:37.019 --> 00:21:39.920 a return to that 1980s dream? Could the next 00:21:39.920 --> 00:21:43.579 major leap in AI involve taking prologue's philosophy 00:21:43.579 --> 00:21:46.960 of pure declarative logic and hardwiring it directly 00:21:46.960 --> 00:21:50.359 into these new artificial digital brains? Hardwiring 00:21:50.359 --> 00:21:52.859 a digital brain not to calculate math, but to 00:21:52.859 --> 00:21:55.779 instantly deduce truth. Taking the ultimate declarative 00:21:55.779 --> 00:21:58.339 language and fusing it with neuromorphic hardware. 00:21:58.759 --> 00:22:00.839 That is a completely new frontier to consider. 00:22:01.069 --> 00:22:02.910 Thank you so much for joining us on this deep 00:22:02.910 --> 00:22:05.009 dive into the source material. Keep asking questions, 00:22:05.170 --> 00:22:07.130 keep looking beyond the procedural steps, and 00:22:07.130 --> 00:22:07.910 we'll catch you next time.