"If one gets through then all should get through" - No, and that does not imply there is loss of determinism. Just because we don't know (or understand something) does not imply it must be random!!!! They are identical, yes but the background is always in flux!!!!

*How can they talk about this topic without mentioning that the Federal Reserve Bank is just a "middle man" that steals Billions of dollars per week from the American people. The US government can print interest free money all by its self. The FED has to go!*

Sincerely appreciate OpenCourseWare. But, wow, can't understand why the camera person (assuming MIT student) doesn't zoom out so the viewer can see the slides. Are you kidding? C'mon.

This guy sounds like borat

Cool that the tape actually winds onto the other reel over the course of the episode in the graphic.

DIE hiring means I don't listen. Imagine hiring people for their race and gender then thinking you'll be listened to. Dolts.

My college sucks! Thanks a million MIT for these free open courses. I'm studying Economics so hoping more Econ related videos

💙

You make a CHOICE what direction the photon(s) are polarized when you shine them into a polarizing filter. Or perhaps they are not polarized. And there are different results. But YOU make that decision, not the Universe. Free will exists. And you can make statistical predictions based upon your choices. But YOU make those choices. Sanjosemike (no longer in CA)

Regarding part d) of finding the expected number of fish to be caught, we can use the total probability theorem as Prof Tsitsiklis suggested. Define X as the rv representing the number of fish caught in the first 2 hours. Then E[# of fish]=E[X|X>0] P(X>0) + E[1|X=0] P(X=0) where E[X|X>0] P(X>0)=[1P(X=1|X>0)+2P(X=1|X>0)+...]P(X>0)=1P(X=1)+2P(X=2)+...=E[X]=1.2

I bought a translation of his book 23 years ago when I was studying linear algebra for my physics degree. Good book.

_Reminded me of _*_how entertaining physics really is!_*

Omg this made so much sense! I loved this.

personal rewatch reference - 12:00 (rewatch why selection sort for unsorted dynamic array and insertion sort for sorted dynamic array)

2024 a.d. Just come across this information.

Bitcoin 🎉

Is there a newer version or is this still relevant I’m assuming?

Why are wide-gap semiconductors not transparent? (You know because they also have a large band gap just like the transp)

🥺 i wish I can join MIT

6:36 In Python, lists are implemented as dynamic arrays that store references (or pointers) to the actual objects, rather than the objects themselves. Each reference points to the memory location where the actual object data is stored. These references are arranged in contiguous memory blocks, enabling efficient data access. Here’s how element access works using an index i: Address(i) = base_address + (i * element_size) - base_address: This is the memory location of the first reference in the list. - i: This is the index of the element you want to access. - element_size: This is the uniform size of each reference in the list. This formula calculates the memory address where the reference to the actual object is stored. By maintaining a constant size for each reference, Python lists can directly compute the memory location of any element’s reference using its index. This avoids the need to traverse other elements, ensuring efficient and direct access. This “offset strategy” is crucial. It ensures that the processor can instantly calculate where each element’s reference is located in memory, regardless of the size of the actual data pointed to by the reference. This method effectively decouples the size of the actual object data from the efficiency of accessing an element by its index, allowing Python lists to manage data of varying sizes efficiently. In terms of actual data structures related to computer science, it is NOT a “linked list” in the literal sense as this is what the slide is eluding to, particularly where it illustrates the tail of a preceding ‘cell’ is point to the head of a subsequent ‘cell’. I get this just to illustrate python lists conceptually but at best it’s either a misunderstanding about the actual underlying data structure used to implement a python list (dynamic array) and at worst dumbing this down to be an imprecise and complicated analogy. The car analogy was perfect. But let’s not do the same for native types that do fundamentally require an understanding that is grounded in the data structures used to implement them (It’s a computer science class after all)

I'm listening to it while driving bike.it seems very useful and would be very helpful for me. Thanks to MIT.

Thank you so much.. Please do more such R, python and Google Earth Engine tutorial for GIS.. ❤

Please do more math courses

버핏이 현대포트폴리오이론은 필요없다 하자마자 이런 영상이..

Computer science was my first major but life took a turn and I became a nurse. After 15 years, I still want to get my degree in CS. These videos are cool, the teacher is great!

❤

I'm searching for memories of a long finished trig class.

Isn't the PH3 is a drago's compound so its bond angle should be 90°

Extraordinary professor.

should

Luckily the audio issue happens right after the simplified solution is shown. This definitely helped me wrap my brain around the solution, thank you!

Non local hidden variables sir

Wawaweewah Jagshemash

Great Video! Below are the timestamped summaries from ChatWithPDF: 00:00🌡 Introduction to heat engines and their role in converting heat into work, focusing on power plants as real-world examples. 01:34🚂 Steam engines, jet engines, and internal combustion engines as different types of heat engines, with a brief mention of hurricanes as heat engines. 02:57🔄 Abstract representation of heat engines with cyclic machines and thermal reservoirs, emphasizing the concept of efficiency. 04:58🔥 Discussion on thermal reservoirs, total work, heat, and efficiency in heat engines, highlighting the importance of maintaining temperature differences. 07:14💡 Explanation of a typical heat engine representation with high and low-temperature reservoirs, work in, work out, and the concept of a cyclic engine. 09:38⚙ Analysis of the Carnot cycle, focusing on isothermal and adiabatic processes to calculate work and heat exchanges in an ideal gas. 11:20🌊 Explanation of high and low-temperature reservoirs in real-world engines like power plants, steam locomotives, and hurricanes. 12:31🌀 Discussion on the mathematical aspects of isothermal and adiabatic processes in ideal gas engines, including internal energy and state functions. 15:58🔄 Overview of the Carnot cycle's efficiency calculation and the significance of temperature differentials in maximizing engine efficiency. 17:56📈 Calculation of the Carnot efficiency for the ideal gas Carnot cycle and its implications for improving power plant efficiency. 20:59🔍 Analysis of isotherms and adiabats in ideal gas engines, focusing on work calculations and the relationship between pressure, volume, and temperature. 24:36 📊 Derivation of equations for isotherms and adiabats in ideal gas engines, emphasizing the role of internal energy and heat capacity ratio. 27:45🔥 Explanation of adiabats and their steeper curves compared to isotherms due to the heat capacity ratio in ideal gas engines. 30:02⏳ Calculation of work and heat exchanges in different segments of the Carnot cycle and their significance in determining engine efficiency. 32:12🔄 Calculation of the Carnot efficiency by analyzing work done, heat absorbed, and heat rejected in a heat engine running on a Carnot cycle. 35:18⚖ Comparison between an ideal Carnot cycle and a less efficient cycle in terms of heat absorbed, heat released, and implications for entropy generation. 37:06🔄 Engineering decisions to improve power plant efficiency by increasing high temperature and decreasing low temperature to approach Carnot efficiency limits. 38:42🔥 Discussion on heat transfers, the Carnot cycle's efficiency, and the relationship between heat rejected and entropy generation in less efficient cycles. 41:29💡 Introduction to dq over t as a key concept related to entropy generation by non-ideal cycles, setting the stage for understanding the second law of thermodynamics. 43:58🔄 Conclusion on the importance of understanding heat engines, their efficiency, and implications for entropy generation as a bridge to discussing the second law of thermodynamics.

Great Video! Below are the timestamped summaries from ChatWithPDF: 00:00🧠 Lecture introduction to basic principles in thermodynamics using interactive methods with a fun approach. 02:33🎨 Drawing a cartoon of noninteracting gas molecules in a box, showing how they spontaneously distribute in space. 06:10🔄 Discussing statistical likelihood in thermodynamics with examples of ball distributions and entropy. 08:44📚 Explaining the concept of entropy and how things move from low entropy to high entropy in the universe. 11:11🌡 Exploring solutions in thermodynamics, demonstrating endothermic and exothermic processes with hot and cold packs. 13:31❓ Clarifying the exchange of entropy in systems and discussing Maxwell's demon as a thought experiment. 16:07🌀 Describing the process of diffusion in noninteracting and interacting molecules, leading to changes in entropy. 18:57🧪 Performing experiments with hot and cold packs to illustrate endothermic and exothermic reactions. 21:17📊 Introducing phase diagrams as a tool to communicate material balance and equilibrium in different systems. 25:01🎯 Emphasizing the importance of phase diagrams for understanding material behavior under varying conditions. 27:16💻 Exploring the use of computerized tools like CALPHAD to calculate phase diagrams for practical applications. 30:52🌡 Discussing the balance between entropy and energy in different systems through phase diagrams. 33:01🌡 Conducting experiments with hot and cold packs to demonstrate the effects of endothermic and exothermic processes. 35:42🧊 Observing the outcomes of endothermic and exothermic reactions using hot and cold packs. 38:24🔬 Introducing phase diagrams as a visual tool to communicate material balance and equilibrium in different systems. 41:19📈 Explaining the significance of phase diagrams in material science and engineering decisions. 44:07🔍 Detailing examples of phase diagrams such as water, binary, ternary, and Richardson-Ellingham diagrams. 46:14🔄 Discussing the complexity and utility of phase diagrams in understanding material behavior under different conditions. 48:27🛠 Highlighting the application of CALPHAD software for calculating phase diagrams in practical engineering scenarios. 50:37📚 Outlining the structure of the thermodynamics course, focusing on equilibrium, phase diagrams, and foundational concepts. 52:38🤔 Sharing a quote by Arnold Sommerfeld about the complexity of thermodynamics and the learning process.

Can anyone explain what exactlt is alpha

What am i watching

This has to be the most entertaining lecture I've ever seen. Once you start watching, you cannot stop. He make concise statements. Easy to be understood by 7 year olds.

First, thanks for the lesson 👍🏻 Question: in the last example of adding the sum of odds, how would the While loop execute the code if the odd condition is false? Shouldn't it stop right there?

Dear sir can you write the code to draw the flag of india

Iow=what the hell are photons?

Wow, this takes me back to undergrad QM. Sets good foundation for QED. Well done professor!

Too bad they only teach what gender photons are now.

Great video!

Okay, now I no longer have beef with weird names on scientific terms or experiments anymore. Thank you, Dr. Nancy

what a great Prof

Which app should I download for Python?

rest in peace proffesor Jesus be with you

Most, if not all, of this, can be learned in a quick Internet search, in less than one hour. No biggie.

I don’t even like math and now I’m thinking of getting a masters in finance 🤔