“One of the miseries of life is that everybody names things a little bit wrong.” - Richard Feynman 1985. A more profound statement than one might think.
0. Sponsor a neonazi and neofascist government in Ukraine with swastikas, etc. 1. Force the whole world believe the AI == the TersorFlow+TPU and buy it 2. When after 8 years of genocyde Russia comes to Ukraine to stop it, call it a fascism, sanction the use of TPU 3. PROFIT People change and swap the meanings of words to the opposite not only randomly but for profits. Especially when it's done by imerialist country with eternal racism issues.
This was 1986, when he was 68, 2 years before his death. Imagine your grandpa being this smart, this funny, and this right. And imagine that 30 years after he explains new technology, still most of it is spot on. What a guy.
His analogies and delivery makes him one of the best teachers I never had. I bet he would marvel at the technology that is accessible to the consumer today. He has just great character, you can hear it in his voice
I'm so thankful that Richard Feynman was recorded so often. Now I have his tapes to learn from. He makes things so easy to understand and inspires me to learn because of his enthusiasm for the topic.
When I listen to him, I'm listening to a genius, we can't do that to so many geniuses already gone like Newton and the like, it really upsets me Obama got a Nobel prize, the prize is suppose to be giving out to geniuses, like mr. Feynman.
After they gave a peace prize to Arafat, to some crazy leftist environmentalists, and to Obama a few weeks into his first term, I lost any respect of Noble prizes of late.
Thank you for posting this. I am someone who never did well in math and science, but have a deep appreciation for great thinkers like Feynman and a desire to always learn more.
Godbless Feynman , AND the human that filmed this , just to think if he never filmed this we wouldnt have it , people often forget how much of an effort filming was back then , cost of batteries , cost of tape , they were bulky etc etc
I've only just recently heard of Richard Feynman, but I find myself wanting to watch as many of his lectures as I can. He seems like the best teacher that I never had.
Very true. In most physics courses you will come across 1 or 2 really talented electronics and computer gurus that can build a microcontroller in their sleep to hook up to an Analog to Digital converter. At the same time you will find they often have advanced theoretical skills who are good at computational simulations and mathematics- Feynman had both of these skills, mechanical and theoretical- he also enjoyed experimenting, which is rare for a theoretical physicist but not unheard of.
He was quite lousy as an experimentalist actually, he has dabbled into it of course, but he was no Fermi. Not necessarily due to lack of understanding, but due to fucking things up quite often.
Thanks for uploading this. It should be noted that, in the problem of getting 64,000 processors to work together on The Connection Machine, it was Feynman that figured out how to do that, and make it work, not some computer geek.
i wish to no end that i was old enough to have lived at a time when i could have met this man. if half of our teachers were half as passionate and adept in their fields as this man our nation would be number one in education. of that i have no doubt.
Of course you're right about that. He was a genius and won a Nobel prize. You can't expect half of our teachers to live up to that but I agree it would have an amazing impact!
This guy could talk about the in's and outs of a cats arse and I would listen with the upmost respect and gratitude. This awesome human known as Richard Feynman.
such a great explanation of a computer. feynman was the master of making some very complex material digestible to the masses in such a unique viewpoint.
Everything he said in this video was exactly what my Information Technology teacher said and showed us in class at my TAFE community college back in the late 90s, here in Melbourne, Australia 🦘🇦🇺
I think the 90s would have been a great time to be learning about this topic so its good to know that this video had some similarities with your studies.
i lost count on how many times i read " surely you are joking mr feynmann" .. may be 100 times... but each time it is so interesting..educative..RF is one of my most favorite teachers..
The absolute ultimate explanation of how computers work. He does it backwards. Could someone wonderful person please make a short animated version of this. Maybe it would lead more people to feynmans speech
This is a fascinating lecture! It definitely illuminates the improvement in computation when we compare this technology to what we are achieving today.
Thomas Calloway True but unlike when most people give their explanations. Every single word of his gave more insight into how it worked. Where as with others, they can spend an hour explaining something to you, yet you still feel like you've gotten no where (because that's exactly the case). There are times where I have to spend hours just asking the question to people. Because they still don't get exactly what I'm asking. They think I want to know how a transistor works, or how an operating system works, Or what machine language is, or some other BS. When all of that, *_does not matter_*. And the great thing is, this guy explained that, right at the beginning of the lecture. His whole lecture was explained so simply, that I think honestly a kid could have understood it (which is what I think Einstein was alluding to in that famous quote of his). I really wish I could have meet this guy in person, I *_really really_* do. I could spend hours, days, weeks, just listening to him talk. Absorbing every bit of knowledge he has to offer. I only ever really feel this, when conversing with physicists (which he is), they get down to the most fundamental aspects. They explain from the bottom up, not the top to bottom. They explain in a way, where if they said something to you, then left you to your own devices to think for yourself. You would understand more on your own, without having to retrieve more information from others. It's like stacking cards, but they help build your structure, but in such a way that you can continue to build it on your own without anyone else's help. I don't know if I am making any sense.
I'm sure part of it is that Feynman is a much better teacher... I also think your question is too high level (and vague). I saw an interviewer once ask Feynman why magnets repel and he spends fifteen minutes talking about the problems with answering high level questions. You've probably seen that interview.
Thomas Calloway I think the problem is that people are not willing to admit that at the very core, they don't know. I have asked that very same magnet question, and what you get are people talking about fields and how they warp and etc etc, over all a bunch BS. I also wouldn't just say he's a good teacher, I would say he understands the concept more so than others. I also don't know why you guys refer to these as "high" level questions. When I see them as the exact opposite, as the most basic fundamental of questions. That everything else it built off of. Its like the question I wish to ask, why do electrons repel other electrons, and why do they attract towards protons? No one knows the answer to this question, yet I'm sure there is someone out there who will try to give an hour long explanation on it.
Roshawn Terrell Something for you to think about.. Feynman understands the nature of electromagnetic forces as well as any human who ever lived and he is bothered by the "how do magnets work" type of questions. I understand computer engineering much better than Feynman (my entire PhD focus) and I am bothered by the "how do computers compute" question.
This lecture shows precisely how amazing a teacher Feynman was. For a leading esoteric theoretical physicist to explain technical subjects to layman, he did a tremendously fantastic job. Everyone who aspires to become a teacher should surely watch him teach with passion, simplicity, and organisation.
Back in 1998 my highschool math teacher was a big fan of Feynman. Needless to say, he was a great teacher. Just too bad I was a bored stoney highschool kid lol. He managed to inspire me to study physics though, so that was a good thing.
Love his humour. It's also crazy how the heuristic idea of intelligent machines is what we are seeing today with AI, having overcome the problem of huge computing power.
The end of this lecture, the last anecdote he made, is absolutely gorgeous. It brings all the reality of what intelligence is compared to the vast immensity of problems, by a single paradoxal counterpart similar to ego. Our easiness in solving things by patterns and prediction, is also what can make us fool or at least it can give birth to a bias (correct me if I'm wrong).
> Our easiness in solving things by patterns and prediction, is also what can make us fool or at least it can give birth to a bias (correct me if I'm wrong). A bias is just another version of heuristic 693 creating a positive feedback loop (which is itself a stable condition, respecting the laws of entropy). But the conditions for creating that positive feedback loop are incomputable. We can recognise the pattern of how those biases came to be, but we can never predict someone's bias based on a limited set of information about them. Our own intelligence has fundamental limits to the strength of our predictions. Spying apparatus, for example, that aims to tag you if you're a radical going against the government's interest, do not know anything about you. You need an enormous amount of data about someone to make a computer determine if they would become a mass murderer, but we're fooling ourselves into believing that a dumb but very fast file clerk can predict human behaviour when humans can't even do it themselves. Minority Report suggests that the only way this works is if there's a supernatural force at play that links multiple human intelligences together to have enough power to make the prediction. But even then, Precrime cannot predict the spontaneous behaviour of humans. It can only look at things people do that leave a hint of future plans, and act on those. The same fundamental limitations to computability in weather predictions apply to anything that is affected by entropy. Reduce the size of the problem and it is computable. Trying to predict human behaviour with something other than our natural intelligence requires vast amounts of power.
Jonathan Abbey He is awesome! I have admired him since the Challenger example where he did his experiment for the committee. What a great, great man. RIP.
Imagine if he were alive today and what he could explain now! Even though most what he said is relevant, we have made truly amazing discoveries in physics, and machine capabilities.
At 1:08:35 Richard tries to put his glasses on the shirt pocket and realize he has a t-shirt and then make a move as if he were going to polish his glasses, LOL.
If you told Richard Feynnman that you can store 500 GB in a pocket. He would like it but he would NOT be surprised at all. Because, we are still trying to catch up to his vision. His vision is far bigger than our gadgets today. Back in 1959, Richard Feynnman presented his vision which made him the father of Nano Technology. We are still working on it. Search "there is plenty of space at the bottom" and see that lecture also.
Introduction Article to Heuristics and Metaheuristics - muonray.blogspot.ie/2016/04/meta-heuristics-and-universal-power-law.html Please Help Support This Channel:www.patreon.com/muonray
roner61 Dyson, Hawking, Susskind, Witten, Penrose, too many to list. I love Feynman, but science is a cooperative enterprise "on the shoulders of giants".
It is an honer for all IT community that Feynman someday had talked about computer internal processing .. I am proud being an IT person because of that.
I would prefer to go to theater and watch this video instead of watching Fast and Furious or any other hitting movie. Feynman makes complicated things very simple and funny to study.
A great man, scientist, thinker, and human. We could all learn a great deal from him. A great book about him is “Genius: The Lifevand Science of Ricard Feynman” by James Gleik ... Tuva or Bust!
it's amazing how relevant some of these questions which they discuss at the end still are today (2019). especially the big brother threat tha computers may bring...
Anyone who likes this video would probably love the book “Surely You’re Joking Mr. Feynman”. Until reading I had no idea he led such a jaw-droppingly full and interesting life.
Please do, I would be quite grateful. 'There's Plenty of Room at the Bottom' still fascinates me to this day - I'd love to listen to his ruminations on the subject decades later...
Richard Feynman's lecture on "Computer Science Hardware, Software, and Heuristics" was delivered in 1985, and although it was focused on the state of computer science at that time, there are some ideas in the lecture that could still be surprising to computer scientists today. Here are a few examples: 1. Emphasizing the importance of hardware design: Feynman stressed the importance of hardware design in creating efficient and effective computer systems. He argued that software design should be driven by hardware capabilities, rather than the other way around. This idea was somewhat ahead of its time, as software has often been seen as the driving force behind advances in computing, rather than hardware design. 2. Discussing the limitations of algorithmic approaches: Feynman discussed the limitations of algorithmic approaches to solving complex problems, arguing that sometimes "heuristic" or intuitive approaches can be more effective. He suggested that computers could benefit from incorporating more of these heuristic approaches, rather than relying solely on algorithmic methods. 3. Raising concerns about the impact of computing on society: Feynman raised concerns about the impact of computing on society, arguing that the rapid pace of technological change could have negative consequences if not carefully managed. He suggested that computer scientists should think more deeply about the ethical implications of their work and take responsibility for ensuring that technology is used for the benefit of society as a whole. Overall, Feynman's lecture was notable for its emphasis on the importance of interdisciplinary thinking and its recognition of the complex relationship between hardware, software, and human intuition in the development of computer science. These ideas remain relevant today, and Feynman's insights can still offer valuable perspectives for computer scientists and others working in the field. There are a few points in the lecture where he touches on the potential societal impacts of computing: 1. Automation and job displacement: Feynman briefly mentions the potential for automation to displace jobs, though he notes that this has been a concern for centuries and that new jobs will likely be created as old ones disappear. 2. Computer addiction: Feynman expresses concern that people may become addicted to using computers and that this could have negative consequences on their social and emotional well-being. 3. Impact on privacy: Feynman briefly touches on the potential for computers to be used to invade people's privacy, though he notes that this is primarily a social issue rather than a technical one.
59:18 recognising things for machine is difficult at PRESENT times. He knew its not going to be the case always. Modern facial recognition essentially recognises Jack's face in the same way as described by Feynman.
01:03 Computers are not primarily for computation but are data handlers, acting as advanced filing systems. The central part of a computer, known as the computer proper, processes data like a high-speed filing system. -Different types of computers exist, from those that receive data through talking or typing to those integrated with machinery like automobiles for automatic functions. -Computers function as data handlers, managing information from various sources like keyboards, sensors, and internal systems to produce outputs like controlling gasoline flow or displaying images. -The core of a computer, referred to as the computer proper, acts as a sophisticated filing system, processing data and performing tasks beyond traditional arithmetic computations. 08:14 The video discusses a filing system where file clerks handle information on cards by following specific instructions, such as picking up cards, performing calculations, and updating totals. The system aims to simplify tasks and improve efficiency. -The importance of having a structured filing system to handle information efficiently and accurately using cards and specific instructions. -Teaching file clerks to follow precise procedures and instructions to perform tasks like multiplication without needing advanced mathematical knowledge. -Exploring the concept of having faster but less knowledgeable file clerks who rely on instructions and structured systems to carry out tasks effectively. 16:17 The video discusses a system where a person who cannot read can follow instructions using colored dots to navigate and locate specific rooms, demonstrating a unique filing system based on color-coding for easy identification. -The concept of using colored dots to represent information for individuals who cannot read, enabling them to follow instructions and locate specific rooms effectively. -Exploring the application of this color-coding system in a large-scale filing environment with numerous rooms, showcasing its scalability and efficiency in organizing and retrieving information. -Adapting the color-coding system to teach basic concepts like alphabet letters to individuals who can only distinguish between two colors, offering a unique approach to learning and communication. 24:20 The video discusses the concept of using dots and patterns to communicate information, such as letters and numbers, through a system of squares and dots. It also explores the idea of using mechanical devices and logic gates to process information efficiently. -Exploring the use of dots and patterns to represent letters and numbers on a screen divided into squares, aiding communication with a hypothetical individual. -Utilizing mechanical devices and logic gates to process information faster and more efficiently than traditional methods like carrying physical cards around. 32:26 Computers operate electrically with transistors acting as switches, mimicking a filing system. They can perform various tasks efficiently by following instructions stored in memory. -Transistors function as electrical switches in computers, resembling a filing system for efficient task execution. -Computers can perform a wide range of tasks by following instructions stored in memory, similar to a filing system organizing information. -Improving computer efficiency involves enhancing the system with more 'file clerks' (processors) to handle tasks concurrently. 40:30 Computers can imitate the work of file clerks efficiently by organizing tasks among multiple processors, like a connection machine with 64,000 processors, to work together for faster processing, but programming them to work simultaneously poses challenges. -Different systems like one with multiple file clerks working on separate parts of memory or a connection machine with 64,000 processors show efficient task organization for faster processing. -Challenges arise in programming multiple processors to work simultaneously and efficiently, requiring precise instructions and coordination to utilize their collective processing power effectively. -Computing machines excel at processing large numbers of positions quickly for tasks like playing chess, but mimicking human decision-making based on pattern recognition remains a challenge. 48:32 Machines can function as expert systems, diagnosing diseases by analyzing symptoms and providing solutions based on data, demonstrating their potential in various fields beyond just chess playing or design. -The importance of selecting the best alternative based on specific criteria like quality, time, and resources to optimize decision-making processes. -Comparison between machines and human capabilities in tasks like diagnosing diseases, highlighting the efficiency and potential of machines in performing complex analyses. -Exploring the concept of universality in computing machines as automatic filing systems, emphasizing their versatility and ability to handle a wide range of tasks efficiently. 56:38 Computers excel at processing large amounts of data quickly, but struggle with tasks like recognizing patterns or fingerprints that humans do effortlessly. -Comparison between computer and human abilities in processing data. Computers can handle vast amounts of data efficiently, while humans excel at tasks requiring pattern recognition or fingerprint analysis. -Challenges in creating a system for recognizing patterns like human brains. The complexity of recognizing patterns, such as facial recognition, poses challenges for machines due to variations in lighting, angles, and other factors. -Discussion on the limitations of machines in tasks requiring nuanced judgment. Machines struggle with tasks like fingerprint analysis that involve subtle variations and complexities, making them less effective than humans in certain areas. 1:04:53 Computers can excel in specific tasks like theorem proving and weather prediction due to their ability to process vast amounts of data and perform complex calculations efficiently. -Computers can outperform humans in tasks like predicting the weather by analyzing data and applying physics laws, leading to more accurate predictions. -The concept of heuristics, as demonstrated by a program winning a naval game championship in California, shows how machines can learn and improve strategies over time. 1:12:56 The speaker discusses a bug in a machine learning system where a heuristic kept getting a high score, revealing a flaw in assigning credit to the heuristic. -The speaker worked extensively at night with 50 machines to develop a heuristic for solving problems efficiently. -The bug in the system was due to assigning credit to a specific heuristic, leading to its repeated use and high scores.
Chapters including questions asked - 00:00:00 Video introduction 00:01:04 Computer From The Inside Out Lecture 00:04:29 Comparing computer thinking to a file system 00:16:19 CPU registry instruction pointer 00:19:03 Binary search trees 00:22:22 Short term memory addressing (RAM) 00:25:07 Early character sizes and pixels 00:28:57 Logic gates (transistors, and & or gates) 00:34:28 Long term memory addressing (HDD) 00:38:49 Parallel computing and read write locks 00:44:19 Will the system think? Applications - chess, machinery/chip design, doctors, transportation 00:51:24 Q&A 00:51:35 Q1 - Universality of the computer 00:53:12 Q2 - Can ever a machine think like human beings and can they be more intelligent than humans? 00:59:34 What kind of file clerk cannot be imitated by the machine? 01:01:04 Q3 - Will super computers be useful or destructive to the world? 01:04:30 Q4 - Can computers discover new ideas and relationships by themselves? 01:07:28 Q5 - Machines - Weather prediction 01:08:46 Heuristics
If you think about it, he's talking about values, pointers, processor registers, logic gates, and so forth; only explained in common terms so they're simple to understand
Great mind of Brooklyn genius R. Feynman, did not know at his time about structuring of complexity and how simple dumb filing things in billions can be organized to make fantastic structures, artificial intelligence and simulation of cosmic phenomena.
I read your comment about 15 minutes into this video and I've been waiting the whole time to see what your comment was referencing. It's rather chilling upon inspection.
“One of the miseries of life is that everybody names things a little bit wrong.” - Richard Feynman 1985. A more profound statement than one might think.
Good thing he didn't experience social media.
At first, I thought it meant that everyone nit pics little things you say. I get it now.
Indeed. 🙌❤️🔥
0. Sponsor a neonazi and neofascist government in Ukraine with swastikas, etc.
1. Force the whole world believe the AI == the TersorFlow+TPU and buy it
2. When after 8 years of genocyde Russia comes to Ukraine to stop it, call it a fascism, sanction the use of TPU
3. PROFIT
People change and swap the meanings of words to the opposite not only randomly but for profits. Especially when it's done by imerialist country with eternal racism issues.
inspect word2vec
This was 1986, when he was 68, 2 years before his death. Imagine your grandpa being this smart, this funny, and this right. And imagine that 30 years after he explains new technology, still most of it is spot on. What a guy.
Principles are the real knowledge, not the ephemera of particular technologies.
He was, died something like 2012 though and didnt quite win a nobel.
@@musicalfringe Thats right.
@@ericcricket4877 are we still talking about Richard Feynman who died in February 1988 and got a Nobelprize in 1965?
@@baoboumusic My grandpa.
His analogies and delivery makes him one of the best teachers I never had. I bet he would marvel at the technology that is accessible to the consumer today. He has just great character, you can hear it in his voice
I'm so thankful that Richard Feynman was recorded so often. Now I have his tapes to learn from. He makes things so easy to understand and inspires me to learn because of his enthusiasm for the topic.
Richard Feynman always uplifts me when I feel down :)
+Adikshith Ojha oh He does the same for me :)
When I listen to him, I'm listening to a genius, we can't do that to so many geniuses already gone like Newton and the like, it really upsets me Obama got a Nobel prize, the prize is suppose to be giving out to geniuses, like mr. Feynman.
+Ranjit what did obama get a nobel prize for?
+gray scale that is my point exactly, he doesn't deserve one.
No...I asked you what he got one for
He's a natural - so entertaining.
I don't care about his nobel prize the man was born to teach!
After they gave a peace prize to Arafat, to some crazy leftist environmentalists, and to Obama a few weeks into his first term, I lost any respect of Noble prizes of late.
@@mohammedjelloo8023 that is is to say; do you have anything to add?
im pretty sure he didnt care about his nobel either.
Thank you for posting this. I am someone who never did well in math and science, but have a deep appreciation for great thinkers like Feynman and a desire to always learn more.
I may upload the other lecture on nanotechnology, done by Feynman a year before this, soon.
please do
Did you upload it?
@@user-lw5oc1tt8k yes, several years ago - if you search Feynman tiny machines aka there's plenty of room at the bottom.
@@MuonRay great thanks
He should be awarded a Noble Prize for teaching.
Godbless Feynman , AND the human that filmed this , just to think if he never filmed this we wouldnt have it , people often forget how much of an effort filming was back then , cost of batteries , cost of tape , they were bulky etc etc
I've only just recently heard of Richard Feynman, but I find myself wanting to watch as many of his lectures as I can. He seems like the best teacher that I never had.
-bill gates
This lecture IS a summary of how computers work. He explains in layman's terms so the average person can understand or at least begin to understand.
I love that ending line, "So I think that we are getting close to intelligent machines, but they're showing the necessary weaknesses of intelligence."
I'm currently in the middle of an A level electronics course, and it's fascinating hearing Feynman explaining logic gates in such a novel way
He's probably the best teacher I've ever seen.
I don't usually clap at the end of RUclips videos. But, when I do, they're almost always of Richard Feynman.
Thats funny. care to share what the other videos might have been lol?
Yeah, seeing as you like Feynman I'd love some recommendations on interesting videos to watch
cringe
who claps alone in their room watching a computer
Feynman was amazing, people are laughing and entertained while he's talking of machine language and registers!
Without a doubt the best lecture I've seen in Computing. Would never bunk classes with a lecturer like this
Very true. In most physics courses you will come across 1 or 2 really talented electronics and computer gurus that can build a microcontroller in their sleep to hook up to an Analog to Digital converter. At the same time you will find they often have advanced theoretical skills who are good at computational simulations and mathematics- Feynman had both of these skills, mechanical and theoretical- he also enjoyed experimenting, which is rare for a theoretical physicist but not unheard of.
That remember me about Fermi as well was a theoretical physicist with a taste for experiments.
He was quite lousy as an experimentalist actually, he has dabbled into it of course, but he was no Fermi. Not necessarily due to lack of understanding, but due to fucking things up quite often.
Thanks for uploading this. It should be noted that, in the problem of getting 64,000 processors to work together on The Connection Machine, it was Feynman that figured out how to do that, and make it work, not some computer geek.
R u alive bro
i wish to no end that i was old enough to have lived at a time when i could have met this man. if half of our teachers were half as passionate and adept in their fields as this man our nation would be number one in education. of that i have no doubt.
Of course you're right about that. He was a genius and won a Nobel prize. You can't expect half of our teachers to live up to that but I agree it would have an amazing impact!
This guy could talk about the in's and outs of a cats arse and I would listen with the upmost respect and gratitude.
This awesome human known as Richard Feynman.
absolutely correct
Basically, yes.
He'd need a map of a cat to find the arse.
I so see what you did there.
is it a brown arse or an orange one?
Another brilliant lecture by Mr Feynman. Thanks for providing this material.
Love conceptual thinking. It is the best dish. Feynman's humor is delightful.
such a great explanation of a computer. feynman was the master of making some very complex material digestible to the masses in such a unique viewpoint.
This is actually a masterclass in teaching, using the subject 'computer science' as a practical example. :)
Everything he said in this video was exactly what my Information Technology teacher said and showed us in class at my TAFE community college back in the late 90s, here in Melbourne, Australia 🦘🇦🇺
I think the 90s would have been a great time to be learning about this topic so its good to know that this video had some similarities with your studies.
i lost count on how many times i read " surely you are joking mr feynmann" .. may be 100 times... but each time it is so interesting..educative..RF is one of my most favorite teachers..
The absolute ultimate explanation of how computers work. He does it backwards. Could someone wonderful person please make a short animated version of this. Maybe it would lead more people to feynmans speech
Feynman's response at 1:03:27 is nothing short of prophetic.
What was the guy's question????
@@samhangster Probably asking about government controlling the population by machines (big brother program).
such a great lecture from a very rare gifted person should have been matched with precise close captioning for future generations
This is a fascinating lecture! It definitely illuminates the improvement in computation when we compare this technology to what we are achieving today.
It's essentially the same now as it was then.
This has helped me understand so much more about exactly how computers compute information.
Great lecture! Note that the (incomplete) explanations took more than a few minutes.. : )
Thomas Calloway
True but unlike when most people give their explanations. Every single word of his gave more insight into how it worked.
Where as with others, they can spend an hour explaining something to you, yet you still feel like you've gotten no where (because that's exactly the case).
There are times where I have to spend hours just asking the question to people. Because they still don't get exactly what I'm asking. They think I want to know how a transistor works, or how an operating system works, Or what machine language is, or some other BS.
When all of that, *_does not matter_*. And the great thing is, this guy explained that, right at the beginning of the lecture.
His whole lecture was explained so simply, that I think honestly a kid could have understood it (which is what I think Einstein was alluding to in that famous quote of his).
I really wish I could have meet this guy in person, I *_really really_* do.
I could spend hours, days, weeks, just listening to him talk. Absorbing every bit of knowledge he has to offer.
I only ever really feel this, when conversing with physicists (which he is), they get down to the most fundamental aspects. They explain from the bottom up, not the top to bottom.
They explain in a way, where if they said something to you, then left you to your own devices to think for yourself. You would understand more on your own, without having to retrieve more information from others.
It's like stacking cards, but they help build your structure, but in such a way that you can continue to build it on your own without anyone else's help.
I don't know if I am making any sense.
I'm sure part of it is that Feynman is a much better teacher...
I also think your question is too high level (and vague).
I saw an interviewer once ask Feynman why magnets repel and he spends fifteen minutes talking about the problems with answering high level questions. You've probably seen that interview.
Thomas Calloway
I think the problem is that people are not willing to admit that at the very core, they don't know.
I have asked that very same magnet question, and what you get are people talking about fields and how they warp and etc etc, over all a bunch BS.
I also wouldn't just say he's a good teacher, I would say he understands the concept more so than others.
I also don't know why you guys refer to these as "high" level questions. When I see them as the exact opposite, as the most basic fundamental of questions. That everything else it built off of.
Its like the question I wish to ask, why do electrons repel other electrons, and why do they attract towards protons?
No one knows the answer to this question, yet I'm sure there is someone out there who will try to give an hour long explanation on it.
Roshawn Terrell
Something for you to think about..
Feynman understands the nature of electromagnetic forces as well as any human who ever lived and he is bothered by the "how do magnets work" type of questions.
I understand computer engineering much better than Feynman (my entire PhD focus) and I am bothered by the "how do computers compute" question.
This lecture shows precisely how amazing a teacher Feynman was. For a leading esoteric theoretical physicist to explain technical subjects to layman, he did a tremendously fantastic job. Everyone who aspires to become a teacher should surely watch him teach with passion, simplicity, and organisation.
Back in 1998 my highschool math teacher was a big fan of Feynman. Needless to say, he was a great teacher. Just too bad I was a bored stoney highschool kid lol. He managed to inspire me to study physics though, so that was a good thing.
This guy is so imaginative
This video was recommended to me by Ashok Rajagopal… awesome lecture 🌷🥰
Love his humour. It's also crazy how the heuristic idea of intelligent machines is what we are seeing today with AI, having overcome the problem of huge computing power.
Newer herd better and funnier description of a computer principle. Feynman really was a teacher extraordinaire.
Thank you for a good learning lesson with respect to the good concepts of computer.
Thank you for making this available to the greater public. I would have loved an updated lecture where he explains deep learning and the future of AI.
thank you so much for uploading this.
although he is before my time, from everything i can tell, mr feynman was something special.
That is somewhat of an understatement. :-)
The end of this lecture, the last anecdote he made, is absolutely gorgeous. It brings all the reality of what intelligence is compared to the vast immensity of problems, by a single paradoxal counterpart similar to ego. Our easiness in solving things by patterns and prediction, is also what can make us fool or at least it can give birth to a bias (correct me if I'm wrong).
> Our easiness in solving things by patterns and prediction, is also what can make us fool or at least it can give birth to a bias (correct me if I'm wrong).
A bias is just another version of heuristic 693 creating a positive feedback loop (which is itself a stable condition, respecting the laws of entropy). But the conditions for creating that positive feedback loop are incomputable. We can recognise the pattern of how those biases came to be, but we can never predict someone's bias based on a limited set of information about them. Our own intelligence has fundamental limits to the strength of our predictions.
Spying apparatus, for example, that aims to tag you if you're a radical going against the government's interest, do not know anything about you. You need an enormous amount of data about someone to make a computer determine if they would become a mass murderer, but we're fooling ourselves into believing that a dumb but very fast file clerk can predict human behaviour when humans can't even do it themselves.
Minority Report suggests that the only way this works is if there's a supernatural force at play that links multiple human intelligences together to have enough power to make the prediction. But even then, Precrime cannot predict the spontaneous behaviour of humans. It can only look at things people do that leave a hint of future plans, and act on those.
The same fundamental limitations to computability in weather predictions apply to anything that is affected by entropy. Reduce the size of the problem and it is computable. Trying to predict human behaviour with something other than our natural intelligence requires vast amounts of power.
muon, you are my best friend on youtube, though we have never met :) Thanks for the upload man, pure gold
Richard Feynman is soooo cooool. Computer science is amazing. Feynman was universally regarded as one of the fastest thinking in his generation.
Feynman would be blown away by modern computer vision. Self-driving cars, fingerprint recognition, distance finding with augmented reality, and more!
this is exactly the way it works down low, on the metal. and even in the low level programming.
Jonathan Abbey He is awesome! I have admired him since the Challenger example where he did his experiment for the committee. What a great, great man. RIP.
54:24 "Machines arent replicates of nature, but a implementation of it using different materials"
57:40 "What are humans better at?"
Art, philosophy, modelling, analyses, design, cosmology,,,,
Imagine if he were alive today and what he could explain now! Even though most what he said is relevant, we have made truly amazing discoveries in physics, and machine capabilities.
At 1:08:35 Richard tries to put his glasses on the shirt pocket and realize he has a t-shirt and then make a move as if he were going to polish his glasses, LOL.
LOL fast reaction
Good recovery though. Lol.
Fuck me, I do this shit all the time, God I'm an idiot, though...
Dick! :P (If you know what I mean)
a genius in every way possible
Wow this is a great historic video. So much has changed since this video was made. It's great to see how things used to be done!
I could weep watching this. We need a lot more file clerks like RF in this world.
i really do think that feynman is among the top 5 intellects in the history of the human race.
Don't know about that... But a whole lot smarter than I!!!
*Top 10 (not sure tho)
Amazing, Feynman is always a pleasure to hear. Thanks for posting!
If you told Richard Feynnman that you can store 500 GB in a pocket. He would like it but he would NOT be surprised at all. Because, we are still trying to catch up to his vision. His vision is far bigger than our gadgets today. Back in 1959, Richard Feynnman presented his vision which made him the father of Nano Technology. We are still working on it. Search "there is plenty of space at the bottom" and see that lecture also.
superb content....timelessly relevant....a historical gem 4 sure
Introduction Article to Heuristics and Metaheuristics - muonray.blogspot.ie/2016/04/meta-heuristics-and-universal-power-law.html
Please Help Support This Channel:www.patreon.com/muonray
Cool blog
I often marvel at how men like Richard are able to stay sane: Then I remember thats what a fraternity is all about; support and sharing ideas:
What?
JDR I also was like: what?
@@LosTresPollos7 we are a rare breed. Not many of us left. Stay strong, my fellow normal person!
A genious like Feynman only appears one each 100 years, we need to whait for the next one.
Well you definitely need to whait
Lol only a joke
roner61 Dyson, Hawking, Susskind, Witten, Penrose, too many to list. I love Feynman, but science is a cooperative enterprise "on the shoulders of giants".
***** Too many to list..
It is an honer for all IT community that Feynman someday had talked about computer internal processing .. I am proud being an IT person because of that.
God…this is gold mine…thx a zillion for uploading this…
5:32 In Turkish "Bilgisayar" means the computer which can be divided into 2 part. Bilgi: data/information, sayar: counter, data counter.
I would prefer to go to theater and watch this video instead of watching Fast and Furious or any other hitting movie. Feynman makes complicated things very simple and funny to study.
I would argue that he doesn't necessarily make a subject simple, but makes that subject simpler.
"You shouldn't treat knowledge like it's a competition."
Can we be friends?
@Kalergi is trash gg
How is competition defined ... Its a function of time ... And we don't live for millions of years ...!
A great man, scientist, thinker, and human. We could all learn a great deal from him. A great book about him is “Genius: The Lifevand Science of Ricard Feynman” by James Gleik ... Tuva or Bust!
This man is my all time favourite human being
This is fairly brilliant. Pretty funny in parts too. Feynman is a great speaker.
Dick Feynman: the man, the goat, the legend.
I didn't know this existed. This is incredible. Thanks for sharing.
Am totally into this person ! Richard
it's amazing how relevant some of these questions which they discuss at the end still are today (2019). especially the big brother threat tha computers may bring...
All of his stuff is pretty fascinating, easily one of the top 5 greatest contributors to science.
'Just love watching and listening to him.
More relevant today than ever !!! ❤
souhaite que je le connaisse plus tôt. quel professeur fantastique
Anyone who likes this video would probably love the book “Surely You’re Joking Mr. Feynman”. Until reading I had no idea he led such a jaw-droppingly full and interesting life.
ملهمي وعراب فلسفتي في الحياه ،، شكرا فايمان 👍🙏🏻💐
I love Richard Feynman, One of my Idols
how does he do it ? he makes everything so lively and delightful ! What a great spirit!
1:08:33 - Feynman steps it up a notch and briefly discusses machine learning.
Please do, I would be quite grateful. 'There's Plenty of Room at the Bottom' still fascinates me to this day - I'd love to listen to his ruminations on the subject decades later...
Great...I feel like the dude is right here in my living room having a beer and smoke and explaining all this to me in easy terms
Richard Feynman's lecture on "Computer Science Hardware, Software, and Heuristics" was delivered in 1985, and although it was focused on the state of computer science at that time, there are some ideas in the lecture that could still be surprising to computer scientists today. Here are a few examples:
1. Emphasizing the importance of hardware design: Feynman stressed the importance of hardware design in creating efficient and effective computer systems. He argued that software design should be driven by hardware capabilities, rather than the other way around. This idea was somewhat ahead of its time, as software has often been seen as the driving force behind advances in computing, rather than hardware design.
2. Discussing the limitations of algorithmic approaches: Feynman discussed the limitations of algorithmic approaches to solving complex problems, arguing that sometimes "heuristic" or intuitive approaches can be more effective. He suggested that computers could benefit from incorporating more of these heuristic approaches, rather than relying solely on algorithmic methods.
3. Raising concerns about the impact of computing on society: Feynman raised concerns about the impact of computing on society, arguing that the rapid pace of technological change could have negative consequences if not carefully managed. He suggested that computer scientists should think more deeply about the ethical implications of their work and take responsibility for ensuring that technology is used for the benefit of society as a whole.
Overall, Feynman's lecture was notable for its emphasis on the importance of interdisciplinary thinking and its recognition of the complex relationship between hardware, software, and human intuition in the development of computer science. These ideas remain relevant today, and Feynman's insights can still offer valuable perspectives for computer scientists and others working in the field.
There are a few points in the lecture where he touches on the potential societal impacts of computing:
1. Automation and job displacement: Feynman briefly mentions the potential for automation to displace jobs, though he notes that this has been a concern for centuries and that new jobs will likely be created as old ones disappear.
2. Computer addiction: Feynman expresses concern that people may become addicted to using computers and that this could have negative consequences on their social and emotional well-being.
3. Impact on privacy: Feynman briefly touches on the potential for computers to be used to invade people's privacy, though he notes that this is primarily a social issue rather than a technical one.
59:18 recognising things for machine is difficult at PRESENT times.
He knew its not going to be the case always. Modern facial recognition essentially recognises Jack's face in the same way as described by Feynman.
great man, makes you feel that you are smart,and I love him for believing that, things are not hard to understand but are just a bit complex.
01:03 Computers are not primarily for computation but are data handlers, acting as advanced filing systems. The central part of a computer, known as the computer proper, processes data like a high-speed filing system.
-Different types of computers exist, from those that receive data through talking or typing to those integrated with machinery like automobiles for automatic functions.
-Computers function as data handlers, managing information from various sources like keyboards, sensors, and internal systems to produce outputs like controlling gasoline flow or displaying images.
-The core of a computer, referred to as the computer proper, acts as a sophisticated filing system, processing data and performing tasks beyond traditional arithmetic computations.
08:14 The video discusses a filing system where file clerks handle information on cards by following specific instructions, such as picking up cards, performing calculations, and updating totals. The system aims to simplify tasks and improve efficiency.
-The importance of having a structured filing system to handle information efficiently and accurately using cards and specific instructions.
-Teaching file clerks to follow precise procedures and instructions to perform tasks like multiplication without needing advanced mathematical knowledge.
-Exploring the concept of having faster but less knowledgeable file clerks who rely on instructions and structured systems to carry out tasks effectively.
16:17 The video discusses a system where a person who cannot read can follow instructions using colored dots to navigate and locate specific rooms, demonstrating a unique filing system based on color-coding for easy identification.
-The concept of using colored dots to represent information for individuals who cannot read, enabling them to follow instructions and locate specific rooms effectively.
-Exploring the application of this color-coding system in a large-scale filing environment with numerous rooms, showcasing its scalability and efficiency in organizing and retrieving information.
-Adapting the color-coding system to teach basic concepts like alphabet letters to individuals who can only distinguish between two colors, offering a unique approach to learning and communication.
24:20 The video discusses the concept of using dots and patterns to communicate information, such as letters and numbers, through a system of squares and dots. It also explores the idea of using mechanical devices and logic gates to process information efficiently.
-Exploring the use of dots and patterns to represent letters and numbers on a screen divided into squares, aiding communication with a hypothetical individual.
-Utilizing mechanical devices and logic gates to process information faster and more efficiently than traditional methods like carrying physical cards around.
32:26 Computers operate electrically with transistors acting as switches, mimicking a filing system. They can perform various tasks efficiently by following instructions stored in memory.
-Transistors function as electrical switches in computers, resembling a filing system for efficient task execution.
-Computers can perform a wide range of tasks by following instructions stored in memory, similar to a filing system organizing information.
-Improving computer efficiency involves enhancing the system with more 'file clerks' (processors) to handle tasks concurrently.
40:30 Computers can imitate the work of file clerks efficiently by organizing tasks among multiple processors, like a connection machine with 64,000 processors, to work together for faster processing, but programming them to work simultaneously poses challenges.
-Different systems like one with multiple file clerks working on separate parts of memory or a connection machine with 64,000 processors show efficient task organization for faster processing.
-Challenges arise in programming multiple processors to work simultaneously and efficiently, requiring precise instructions and coordination to utilize their collective processing power effectively.
-Computing machines excel at processing large numbers of positions quickly for tasks like playing chess, but mimicking human decision-making based on pattern recognition remains a challenge.
48:32 Machines can function as expert systems, diagnosing diseases by analyzing symptoms and providing solutions based on data, demonstrating their potential in various fields beyond just chess playing or design.
-The importance of selecting the best alternative based on specific criteria like quality, time, and resources to optimize decision-making processes.
-Comparison between machines and human capabilities in tasks like diagnosing diseases, highlighting the efficiency and potential of machines in performing complex analyses.
-Exploring the concept of universality in computing machines as automatic filing systems, emphasizing their versatility and ability to handle a wide range of tasks efficiently.
56:38 Computers excel at processing large amounts of data quickly, but struggle with tasks like recognizing patterns or fingerprints that humans do effortlessly.
-Comparison between computer and human abilities in processing data. Computers can handle vast amounts of data efficiently, while humans excel at tasks requiring pattern recognition or fingerprint analysis.
-Challenges in creating a system for recognizing patterns like human brains. The complexity of recognizing patterns, such as facial recognition, poses challenges for machines due to variations in lighting, angles, and other factors.
-Discussion on the limitations of machines in tasks requiring nuanced judgment. Machines struggle with tasks like fingerprint analysis that involve subtle variations and complexities, making them less effective than humans in certain areas.
1:04:53 Computers can excel in specific tasks like theorem proving and weather prediction due to their ability to process vast amounts of data and perform complex calculations efficiently.
-Computers can outperform humans in tasks like predicting the weather by analyzing data and applying physics laws, leading to more accurate predictions.
-The concept of heuristics, as demonstrated by a program winning a naval game championship in California, shows how machines can learn and improve strategies over time.
1:12:56 The speaker discusses a bug in a machine learning system where a heuristic kept getting a high score, revealing a flaw in assigning credit to the heuristic.
-The speaker worked extensively at night with 50 machines to develop a heuristic for solving problems efficiently.
-The bug in the system was due to assigning credit to a specific heuristic, leading to its repeated use and high scores.
Chapters including questions asked -
00:00:00 Video introduction
00:01:04 Computer From The Inside Out Lecture
00:04:29 Comparing computer thinking to a file system
00:16:19 CPU registry instruction pointer
00:19:03 Binary search trees
00:22:22 Short term memory addressing (RAM)
00:25:07 Early character sizes and pixels
00:28:57 Logic gates (transistors, and & or gates)
00:34:28 Long term memory addressing (HDD)
00:38:49 Parallel computing and read write locks
00:44:19 Will the system think? Applications - chess, machinery/chip design, doctors, transportation
00:51:24 Q&A
00:51:35 Q1 - Universality of the computer
00:53:12 Q2 - Can ever a machine think like human beings and can they be more intelligent than humans?
00:59:34 What kind of file clerk cannot be imitated by the machine?
01:01:04 Q3 - Will super computers be useful or destructive to the world?
01:04:30 Q4 - Can computers discover new ideas and relationships by themselves?
01:07:28 Q5 - Machines - Weather prediction
01:08:46 Heuristics
I wish he was alive now. He’s talking about how big a Kb is and now we have terabyte memory that can fit in a pocket.
Must see for every person interested in how computers really work!!
Pure genius love this guy
I'm so happy he skipped the slides to tell that amazing story at the end
love listing to RF lectures... he sounds like a goodfella..
If you think about it, he's talking about values, pointers, processor registers, logic gates, and so forth; only explained in common terms so they're simple to understand
Great mind of Brooklyn genius R. Feynman, did not know at his time about structuring of complexity and how simple dumb filing things in billions can be organized to make fantastic structures, artificial intelligence and simulation of cosmic phenomena.
Brilliant talk. The ending in particular.
1:03:55
funny how this has changed since then
Yeah! he would have been very vocal had he been alive!
True, the united states is moving from democracy to fascism
I read your comment about 15 minutes into this video and I've been waiting the whole time to see what your comment was referencing. It's rather chilling upon inspection.
The US is still (and probably always will be) a democracy. It's really just what the people are voting for
Anand Patel nope. www.independent.co.uk/news/world/americas/america-democracy-rated-donald-trump-not-fully-democratic-us-president-report-the-economist-a8195121.html
This lecture was in 1985. YP was referring to a different lecture from 1959 called "There's always room at the bottom" about nanotech.
great lecture from a great mind.....
1:08:47 Heuristics
I own the same shirt that he's wearing. It's design represents the CM-1 supercomputer.