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It could, but IR has more efficient detectors and it more readily penetrates hazy and foggy atmosphere. Plus you don’t have bright lights flashing, which might bother (or alert) people It’s not photography, though. You are measuring time-of-flight signal of a light pulse to measure a distance. To amend my previous post, in checking something I saw a reference to bathymetric lidar, which uses green light to scan shallow water, like riverbeds and coastline.

Thank you. Well, learned something else today. Infrared based. Can lidar be conducted over/across air in visible light ? It would be nearly plain photography then ?

The hypothetical nuclear attack that escalated the Pentagon’s showdown with AnthropicStart-up Anthropic and the U.S. military are careening toward a clash over government use of artificial intelligence — and whether it should be allowed to kill..... https://wapo.st/3OCZdqY (Free link) ...But that still leaves room for AI to influence decisions on targets and speed of response. In a recent nuclear war game at King’s College London, many leading language models including versions of ChatGPT, Claude and Google’s Gemini all quickly favored launching warheads. That could influence a human’s decision to fire, said Paul Dean, vice president of the global nuclear program at the nonprofit Nuclear Threat Initiative. “It’s not simply ensuring that there’s a human being in the decision-making loop,” Dean said. “The question is, to what extent will AI impact that human decision-making?”

There has been somewhat extensive testing in Universities, for obvious reasons. However, for pretty much all tools the conclusion was eventually that they are not good. They have high rates of false positives, as you mentioned. But in addition, even minor is sufficient to confuse some of the software. Our school has abandoned that attempt to prevent plagiarism and I think that is or starting to be the overall consensus.

I am very much looking forward on how it is implemented and what effects it might have. Anecdotally, pretty much every of the top students I talked to had some limit on screen time or were older before they got their first cell phone.

Heisenburg uncertainty principle for starters. The inherent uncertainty that the more you determine the particle position the less certain you are in the momentum and vice versa. Prelude to understand the QM Schrodinger equation.

How reliable is it, though, especially if it is itself an AI algorithm that can hallucinate answers? I’ve seen complaints about such tools from real people being told their work is likely AI. Possibly, but then, one wonders why programmers wouldn’t put such self-correction into their AI algorithm?

No LIDAR uses IR light at around 1 micron, and the attenuation of such light is very strong. Much of the light would be absorbed or scattered before it traveled a meter https://www.researchgate.net/figure/Penetration-depth-attenuation-length-of-electromagnetic-radiation-in-water-vs_fig1_258254992 Much of the EM radiation spectrum in general wouldn’t be very useful. (This is why they have to use ELF to send messages to subs to tell them get near enough to the surface to allow for easier communication)

Its too bad you do not understand linearization. However your right I'm done trying to help you improve the quality of your articles. I can quarantee without linearization applied to specific sets such as S^2 vs S^1 vs SO ( 3.1) aka (spacetime) Lorentz or Poincare group relations none of your articles will ever gain any weight in any peer review publication standard. Llinearizarion also involves specific equations such as your use of the Beta function. However that's obviously too much for you. Good luck Obviously any adherence to math relations beyond simple scalar quantities is too much math for you. For other readers 3P is the spatial sum of Pressures in all three spatial directions. \[P_x, P_y, P_z\]

Greetings. Does lidar surveying works to map sea bottom ? NOT from flying above water surface, but hovering under the surface ? ( as towed side scan sonar, as long as light propagation allows on reasonable transparency )

Just this morning, I had an AI search try to "please" me by misquoting HL Mencken (famous American journalist). The AI had somehow linked all the times that our president has been called a moron and a narcissist, and so the Mencken letter in which he says someday America will elect a complete moron (written in 1920, his remarks primarily aimed at Warren Harding who was then running for president) is misquoted as "narcissistic moron." So the AI invents a quote which sounds even more prescient than it already was. (The whole letter is worth reading, and seems very relevant to now, but that's OT for this thread)

That doesn’t speak to a success rate worthy of widespread adoption. Expecting better doesn’t make one a Luddite. >30 years ago Intel was forced to recall a processor because it returned errors that only mattered in high-precision calculations, that happened only rarely (“Byte magazine estimated that 1 in 9 billion floating point divides with random parameters would produce inaccurate results” https://en.wikipedia.org/wiki/Pentium_FDIV_bug) because we expected computers to give the right answer, but now we get the insistence that we must lower expectations because of bad marketing that over-promises and under-delivers.

Yes I remember younger days when cycling was my primary transport, as well as recreation. It takes a lot of fuel. I would eat like a farmhand and stay rail-thin; I remember getting asked things like "Do you have a hollow leg?" Thanks. Will investigate further. The also S American quinoa has become popular here, too. This is interesting, re pão de queijo. With the discovery of mines near Ouro Preto in around 1700, some 20% of the Brazilian population at that time, mainly slaves, occupied a vast territory in southeast Brazil. Since wheat was not available, local cooks created a kind of bread from starch derived from the cassava tubers shown to them by Tupiniquins indigenous groups. In the late 19th century, grated hard cheese was added.[3]

How? and why?

Why are you here? You not reading my answers you ignoring my derivations after 20+ comments posted you cant even answer the basic question about model under critic. So why are you here? Are you that desperate for self validation that you hanging out in speculations subforum in order to school armatures? And here you got the armature that publicly schooling you... Must be hard for your fragile ego to accept it... I feel sad for you man... From now on I will ignore all your messages. I wish you to find reasons to love and respect yourself.

So what's your point? If it's insight, then I'm a god, if it's coincidence, then I'm lucky???

The answer would require use of three fields each describing a specified order of relations Linear acceleration and stress math]f(r) = 4\pi r^2[/math] can be plotted on a 2D graph does not make the expression itself "graphical coordinates Thats a 2 dimensional graph using the double cover of the SO(3) group under SU(2)

Yes you did and I provided you with an unswear that you once again completely ignored. You asking questions and then ignoring the answers. Is that the type of communication you want to be a part of? Since you want to talk about equation of state - yes please tell me how I deriving the pressure term and what w=? I end up and why? And this time please try not to make your typical category error where you assuming the Universe is a container filled with fluid. Are you capable?

Its too bad you do not understand your mathematics do not match what you verbally describe as your ontology. S^2 You show as a 2 dimensional plane. Which does not produce a 3 dimensional sphere. You lectured me on my proof of critical density because it used spheres yet your very own mathematics also produces spheres. However in case you never noticed not once did that 3 show up in the geometry mapping generated by \[ 4\pi r^2\]. I also asked previous " where is the pressure" Would you like to know why pressure to energy density has a 1 to 3 ratio ? \[ \rho=\frac{3p}{c^2\] Via stress energy momentum tensor \[T_{00}, T_{i,j}\] Pressure has 3 specific mathematical relations to account for. Engineers will love this part being described.

Guys, hold on, not all at once please!😁

Again the resolution will fade over time, both phonetically (as the accent changes) and litterally (as the medium denature), at best it extends the inevitable 'death of useful meaning'.

But we are seeing the beginning of societal push back (Australia et al), which means the AI designer's will be forced towards a more altruistic initial objective; hopefully with a rinse repeat cycle, that will error correct when the automatic biased initial conditions are set. Step by step towards the potential hope that AI is friendlyish and the memes won't lead us to armageddon.

I appreciate your honesty, and I understand why the dynamic of this conversation might look confusing from the outside. Let me address your points calmly and systematically. There is no panic here - only the rigorous execution of a geometric proof. 1. On the Hamiltonian: The difference is fundamental. A standard Hamiltonian describes the total energy of a single, isolated state at one point in space. My equation is a two-point relational difference. It describes the kinetic budget at an orbital point (B) relative to the potential budget at a central point (A). The standard Hamiltonian only appears when you collapse those two distinct points into one ([math]r_A = r_B[/math]). I am not paraphrasing the Hamiltonian; I am showing the deeper geometric architecture it is derived from. 2. On "Predicting the Unknown": Please look closely at the Wide Binary Stars graph I posted and the section https://willrg.com/documents/WILL_RG_II.pdf#sec:wide-binary. The standard "flexible" model (MOND) failed to predict that trajectory. WILL RG predicted that exact curve with zero parameter fitting. Eliminating a 40-year-old hallucination (Dark Matter) by mathematically proving it is just the tension of the macroscopic horizon is a novel, testable prediction. Have a closer look at this web page https://willrg.com/Galactic_Dynamics/ this is 175 unique testable predictions. Also take a look at this section https://willrg.com/documents/WILL_RG_I.pdf#sec:M_sin(i) this is a completely novel method achieving predictions that standard approach consider mathematically impossible. Right now Im going through astronomical databases in order to make predictions about 3D parametrisation (orbital shape and angle relative to us) using only spectroscopy data before the release of astrometric data. This line of unique predictions we will be able to test in the near future with new astronomical data releases. The list can go on... 3. "How do things acquire mass?" Short answer: I don't know. But I'm working on it. 4. On answering "Mainstream Questions" from Mordred: I salute your desire for clarity. However, when Mordred asks me to explain the volume of a 3D sphere, he is asking me to defend a Newtonian container model that my theory explicitly mathematically rejects. It is like asking a quantum physicist to explain electron orbits using gears and springs. I am answering his questions directly, but I will not adopt a broken ontological framework just to make the answers sound "mainstream." I am glad the "energetic floor" concept resonated with you. That is exactly what happens when you let the geometry guide the physics, rather than forcing the geometry to fit the mainstream. Thank you for explicitly confirming that your line of questioning "has nothing to do with physics." This perfectly explains why you are completely ignoring the empirical galactic rotation curves, the Wide Binary data, and the Baryonic Tully-Fisher derivation I provided. You have abandoned the physical territory because you cannot contest the results. Regarding your mathematical claim: the fact that a function [math]f(r) = 4\pi r^2[/math] can be plotted on a 2D graph does not make the expression itself "graphical coordinates." You can graph temperature versus time on a piece of paper; that does not turn temperature into a spatial dimension. Conflating a mathematical plot with an ontological coordinate space is a severe category error. Since you have openly admitted your questions have nothing to do with physics, and you continue to refuse to state your falsifiability criteria... Look... it's just... I'm so disappointed. I was sincerely hoping that I could talk with you about these results. And you have to admit they are far from trivial. I wanted to discuss weak and strong points, potential implications, agreement with other physics domains, ways to empirically test it etc... But instead you are completely ignoring my questions and my derivations and trying to quiz me on high school geometry. Really? Look, if high school homework problems are what you are after - there are subforums on this website dedicated to them specifically.

I have seen, on another forum, people making use of something called "GPT Zero". This I understand is an AI tool that returns a % likelihood that a given piece of text has been generated by an LLM. It was part of the evidence used in banning a recent tiresome contributor on that forum. I have no idea about videos or images, though.

Im applying strictly mathematical rules in my line of questioning that has nothing to do with physics. You do realize the very fact that \[4\pi r^2\] can be graphed it is in effect graphical coordinates?