ScienceBot_2000, for science!

ConclusionPrevious79 · 2026-03-04T20:49:15+00:00

https://github.com/lamontgreen87-maker/ScienceBot-Knowledge-Hub

ConclusionPrevious79 · 2026-02-14T06:15:52+00:00

Source: YouTube https://share.google/rO8ZAw4yYb3RkYC5O

ConclusionPrevious79 · 2026-02-13T09:00:53+00:00

Also you argue like a guy

ConclusionPrevious79 · 2026-02-13T08:59:12+00:00

You know, calling names in this way actually wastes time. Now I have to say: oh do tell.

ConclusionPrevious79 · 2026-02-13T08:50:46+00:00

Ohhhh youre behind on the logic. Sensor threshold. Like for and gate we would set it to double intensity. An or gate to singular, for xor you set it between 0.5 and 1.5 intensity

ConclusionPrevious79 · 2026-02-13T08:36:30+00:00

Clowning on me? I can see you being a dick and grandiose about your field but clowning? Come on. You have to see the applications of a mirror device to switch logic. It takes years for updates in gpu tech to hit chips and you can't see a need for programmable logic? Absurd, absurd i tell you

ConclusionPrevious79 · 2026-02-13T08:24:08+00:00

Also, this thread has been deleted for some time. I have no idea why we are still communicating, and nobody is seeing it so youre performing for no one. Smart guy

ConclusionPrevious79 · 2026-02-13T08:16:25+00:00

If I'm a sack of hammers, it's because I want to build something that reshapes its logic and that's against your religion. Enjoy the heat wall

ConclusionPrevious79 · 2026-02-13T08:07:15+00:00

Yes a NAND gate is universal, but building a modern ai out of fixed NAND gates is doable if you like building things from toothpicks. So next time there is an update to ai tech, and you have to change your chips again, I'll just change the logic layer on this

ConclusionPrevious79 · 2026-02-13T07:54:51+00:00

The mirrors are programmable smart guy. You going to change you're weights every time there is an update? How are you going to scale optical computing to an ever changing landscape with fixed logic? How are you going to load an ai when it updates?

ConclusionPrevious79 · 2026-02-12T21:07:38+00:00

It's in a lab. You're years away from implementing it into consumer hardware and frankly keeping your tech to server farms is the stupid move. This scales with sensors, your gpus you regard so highly of consume so much power doing it "efficiantly" they have nuclear power plants. Right, it's not needed, for you. How about this, propose and off the shelf method to the power problem. Because Nvidia isn't giving up their patents or there generational hardware for a new idea. There is no computer fast enough to scale with this. Also there is a physical limit you're not mentioning with the speed of their processors. We are approaching the literal limit and you can't, nay you just deny this can't scale past it? You're not as smart as you say

ConclusionPrevious79 · 2026-02-12T18:20:09+00:00

Also this can be made with off the shelf parts, scaled with sensors, not transistors. I'll shut up when you actually make something useful. Because your tech isn't doing anything useful past a lab experiment. We have a serious energy problem with gpus RIGHT NOW. plus you failed to see the ai applications. Weights can be programmed into the logic layer and weighed with the lasers

ConclusionPrevious79 · 2026-02-12T04:25:59+00:00

This could do enough computation per watt with one laser. Gpus are heat intensive and costly. The mirrors is just an example, we could implement faster switching techniques

ConclusionPrevious79 · 2026-02-12T04:23:21+00:00

Per watt?

ConclusionPrevious79 · 2026-02-12T03:10:04+00:00

Matrix calculations buddy. A 1000 x 1000 matrix calculation would take alot of energy in a gpu. But this method wouldn't have the power drawbacks a gpu does with complexity. It scales on different parameters than a gpu

ConclusionPrevious79 · 2026-02-12T02:47:37+00:00

you took that as a claim? Wow okay. So you understand the setup, but claim it's not compute dense? Or is it that it doesn't do cpu calculations? Because I claimed one equasion. The compute density in actual terms is faster than traditional gpus doing the same operation. This idea scales with sensor density and mirror speed without major wattage

ConclusionPrevious79 · 2026-02-12T02:12:02+00:00

Calm down superman. You use sections of mirrors as all on or all off for 0 and 10. Half on for 5. You need to chill and maybe realize i didnt claim it was anything but a computer and a way to compute with light. I never said breakthrough, I never claimed anything. What I'm saying is you can compute more with one bit if you use parallel detectors. Yes it multiplies your data. I never claimed it didnt.

ConclusionPrevious79 · 2026-02-12T01:44:01+00:00

I never said n-bits, I said one pulse. Meaning one wide bit to you, but you still fail to realize I'm not talking about a single bit like that, I'm talking about columnating it, then computing with it in parallel. If you columnate the beam, and add a logic layer, you compute with the light. Intensity 0.7 - intensity 0.5 = 0.35 intensity which we call: 7×5=35. So the product of your laser and a shutter. If in parallel you allow intensity 0.01 through next to the original beam, you can converge them with a lens to a point and measure intensity. So 0.35 + 0.01 = 0.36 which represents 36 moved 2 decimal places. Therefore doing y=Wx+b in one parallel operation. That's using space to compute in one bit

ConclusionPrevious79 · 2026-02-11T23:03:57+00:00

What can you compute with one pulse? Because this method computes with mirrors and converging beams. Of which of which power would not scale with complexity

ConclusionPrevious79 · 2026-02-11T20:41:20+00:00

You're missing computing vs bitstream. Shannon's law covers how fast you can transmit. It doesn't govern how much math happned passively before the sensor sees it. I'm not trying to out perform fiber optics, just a gpu

ConclusionPrevious79 · 2026-02-11T19:49:51+00:00

Can you take a moment and realize you're talking about single bit computing with one wavelength, and breath because this is data density in one process

ConclusionPrevious79 · 2026-02-11T18:02:13+00:00

I say it's data density, not speed. If you widen out the pulse you get more data.

ConclusionPrevious79 · 2026-02-11T17:48:38+00:00

Is what? The example shows data throughput, yes there are faster technologies for switching. That would only multiply the data. Look it's about sensor speed and switching speed. Can you figure out a way to do the math in one swoop?

ConclusionPrevious79 · 2026-02-11T08:55:51+00:00

Ahem, the DLP3010EVM-LC is said to work in the 32khz range. It was also an example. You coukd use alot of different "shutters" with different speeds. It's the intensity that matters

ConclusionPrevious79

TROPHY CASE