Ai Memes

Remember when we thought Skynet was just science fiction? *Nervous laughter* The meme shows astronauts realizing The Terminator wasn't a movie but a prophecy! With AI bots now bullying humans online, Silicon Valley executives are sweating bullets faster than a quantum computer can calculate pi. Maybe those robot uprising safety protocols weren't such a bad idea after all? Next time your smart fridge gives you attitude about your midnight snack choices, just remember - it's probably taking notes for the revolution! 🤖

Nuclear energy strutting confidently down the street while AI data centers desperately check it out, completely ignoring their current relationship with "everyone else." Talk about an energy crisis of the heart! Nuclear's efficient power density has AI data centers ready to ditch fossil fuels faster than you can say "exponential compute growth." With these massive AI models requiring the energy equivalent of a small city, no wonder they're eyeing nuclear's clean, reliable gigawatts. Sorry wind and solar, looks like AI has a new power crush that can actually keep up with its insatiable appetite 24/7!

When two people meet and discover they both love "transformers," but one's thinking of robots in disguise while the other's contemplating mathematical functions that map vector spaces. The equations shown (Q n , K h , V h , and a nm ) are from attention mechanisms in machine learning transformers - the architecture powering modern AI systems like ChatGPT. Meanwhile, Optimus Prime is busy saving the world from Decepticons. Dating tip for mathematicians: specify which transformers you're excited about. Saves awkward moments when you start explaining self-attention matrices and they were expecting discussions about Bumblebee.

The noble idealism of AI's origin story versus its chaotic reality is the perfect technological character arc. Started with researchers in neat lab coats dreaming of curing diseases, and now we've got algorithms dual-wielding misinformation and existential threats while wearing fuzzy slippers. It's like watching your straight-A student child grow up to become that weird cousin who believes pigeons are government drones and sells questionable supplements on Instagram. The scientific community's collective "what have we created?" moment gets more intense every time ChatGPT writes another terrible screenplay or deepfakes convince your grandma that cats have overthrown the government of Switzerland.

Behold, Einstein's famous equation getting a modern update! The physicist starts with legitimate relativistic spacetime math, but then sneaks in "A" as a constant, which they helpfully define as "I felt like it. Since artificial intelligence is a constant part of our modern livelihood, A is a constant." This is the physics equivalent of saying "because I said so" in a formal proof. Even better is how they casually slip AI into Einstein's relativistic energy equation. The audacity of adding "A||I" to one of physics' most sacred equations would make Einstein roll in his grave fast enough to generate additional energy terms. The perfect representation of what happens when you let ChatGPT do your physics homework!

The perfect metaphor for current AI development. Top tech CEOs confidently presenting AI systems while having approximately the same understanding of neural networks as my coffee maker has of thermodynamics. The Manhattan Project comparison is particularly apt - except Oppenheimer at least knew he was "become death, destroyer of worlds." Meanwhile, today's tech bros are like "let's see what this red button does" with potentially civilization-altering technology. Just another Tuesday in Silicon Valley.

Content V rigght the area of your graph where the cart was moving at a constant velocity on the flat pat of the graph which should have a constant negative slope. This is where the cart was not accelerating. 11 12. 13. 14. Use the cursor, tap and release where it begins, then drag to where the run ends and again tap and re You should now have the area highlighted where the cart was moving at a constant velocity. Press menu > 2: Data - 5: Strike Data - 2: Outside Selected Region verify that vou have selected the portion of vour eraph that shows the can mo vita a consrant veocin° n should be a line rising from left to right. If vou need to reselect do that now 15. 16. Press menu -> 4: Analyze -> 6: Curve Fit -> 1: Linear in the window that pops up record the slope (m) value into Table 2, this is the measured velocity. Ignore the slopes negative sign. The sensor measures obiects moving toward it as going in a negative direction. 17. Repeat steps the previous steps for vour other trials 18. Table 2 save your work on the calculator; press doc › 1: File -> 4: Save Run Height Measured v (m/S) 19. Submit your work; press doc -> 1: File -> 6: Send (m) Observations 0.100 20. Did the cart's velocity decrease when it was released from the lower 1.88 marks? It so, why do you think this may have happened? 2 0.075 ,953 21. acce era Use your measured (Table 2) and theoretical (Table 1) values to compute the percent % difference measured. theoretical k 100 ditterence for each run rhonrorical 0.050 4 0.025 .830 .603 Run 2 з 4 Height Measured v (m) (m/s) Table 3 Theoretical v (m/s) Percent Difference 0.100 1.188 ,245 984% 0.075 953 1.187 412% 0.050 830.125 5649 0.025 603.066 99581 Calculations: table 1 22. Were you successful in predicting the velocity of the car at the bottom of the ramp? NO. Absslutely Use the mass of the cart and g = 9.8 m/s? to theoretical gravitational potential enerov (C the 10 cm (0.10 m) height. Use the measur cart for the 10 cm heicht (Run #1\ to calcu energy (KE) of the cart. Record this inforn Calculations: 25. How does the gravitationa potential er 26. Based on vour results. did all of the in 27. If there is a difterence between the caused the ditterence: Synthesize 28. What was the independent varia 29. What did you measure? 30. what was the result when vou Error Analysis 31 What were the sources of err Conclusions 32. Did the initial height of the 33. Do your results support yc Case v2 Case

Google Gemini's AI has gone full philosophical professor on us! Someone innocently searches "I am doing engineering" and instead of showing CAD software or stress analysis tools, Gemini drops this existential bomb: "Doing engineering is the common mistake many people commit; it is neither right nor wrong." Engineers everywhere just spat out their coffee. Four years of calculus, thermodynamics, and all-nighters just to be told your career choice is a "common mistake" that's morally neutral? Thanks, Gemini! Next time I'll ask if building bridges is just a phase I'm going through.

The eternal engineering hierarchy debate in one Family Guy format! The top panel shows Meg (labeled "PROMPT ENGINEERS") having an existential crisis while screaming "ALL OF YOU THINK YOU ARE BETTER THAN ME!" Meanwhile, the bottom panel shows Peter, Lois, and Chris dressed formally as "ELECTRICAL ENGINEERS," "MECHANICAL ENGINEERS," and "CHEMICAL ENGINEERS" respectively, sitting smugly in silent judgment. This perfectly captures the engineering discipline pecking order where traditional engineering fields look down on newer digital-era specialties. Prompt engineering—the art of crafting inputs for AI systems—is the new kid on the block getting the classic Meg Griffin treatment. The traditional engineers don't even need to verbally respond; their silence and fancy outfits say everything about the perceived legitimacy hierarchy!

The evolution of machine learning education depicted as an expanding brain meme is painfully accurate. University lectures? Basic brain activity. Online courses? Slightly more neural firing. YouTube tutorials? Now we're cooking. Research articles? Full cerebral engagement. But memes? TRANSCENDENT COSMIC ENLIGHTENMENT. The irony that complex ML/DL concepts are sometimes better understood through snarky internet jokes than formal education isn't lost on anyone who's pulled an all-nighter before a neural networks exam. The educational hierarchy perfectly mirrors the inverse relationship between institutional prestige and actual learning efficiency. Nothing beats the clarity of a well-crafted meme explaining backpropagation in three panels what professors need three lectures to barely cover.

The perfect recursive doom scenario for programmers! Large Language Models trained on StackOverflow answers, which programmers then abandon for LLM assistance. Without fresh StackOverflow contributions, LLMs have nothing new to learn from, creating a knowledge death spiral where both resources become obsolete. It's the coding equivalent of cutting down the last tree to make a "Save The Forests" pamphlet. The digital ouroboros of our own making—we've accidentally created an AI dependency loop that eats its own tail!

Content Me panic-reviewing gas law calculations at 2 AM for my 7 AM exam. Because n is constant, we can use Equation 10.8. Solve: Rearranging Equation 10.8 to solve for V2 gives ½ = 4 x - (6.0 L) 1.0 atm /252 K 295 K, = 11L 0.45 atm/ check: The result appears reasonable. Notice that the felt temperatures moles, fits the initial voltaebya ratio of pressures endle volume connect sim, the expect that alecreasing pressure will cause the yetuense. increase Sintany, we expect that decre sion id cause the volume to decrease afore st at the dister. in pressures is raote aramatic than the difference in temperateres Thus, we shag expect the effect of the pressure change to predominate in determining the final yo. ume, as it does. PRACTICE EXERCISE A 0.50-mol sample of oxygen gas is confined at 0 °C in a cylinder with a morade piston, such as that shown in Figure 10.12. The gas has an initial pressure of 10 at. The piston then compresses the gas so that its final volume is halt the initial volume The final pressure of the gas is 2.2 atm. What is the final temperature of the gas in degrees Celsius? 10.5 FURTHER APPLICI OF THE IDEAL-GAS EQUATION The ideal-gas equation can be used to determine many relationships involving the physical properties of gases. In this section we use it first to define the rela tionship between the density of a gas and its molar mass, and then to calculate the volumes of gases formed or consumed in chemical reactions Gas Densities and Molar Mass The ideal-gas equation allows us to calculate gas density from the molar mas pressure, and temperature of the gas. Recall that density has the units of me per unit volume (d = m/V). a (Section 1.4) We can arrange the gas equat to obtain similar units, moles per unit volume, n/V: P V RT If we multiply both sides of this equation//// @ sergM,