125: Chapter 125 The First Reality Node

Jiang Lin did not post any long statements on social media to respond to the outside world's speculation.

He didn't repost Terence Tao's interview video praising him so highly.

He didn't write a post thanking Mr. Shing-Tung Yau for his public expectations and support.

Nor did he bother to explain what the PFR Conjecture or the Marton Route were, or detail the technical framework that had taken the internet by storm.

He maintained absolute silence, as if the clamor of the outside world were happening in a parallel universe.

Meanwhile, in his own Real World, within that somewhat cramped room, Jiang Lin was engaged in a physical reconstruction entirely different from abstract mathematics.

Jiang Lin was receiving deliveries.

Four massive RTX 3090 graphics cards.

Admittedly, for truly cutting-edge deep learning laboratories or massive supercomputing centers, these amounted to practically nothing.

They were merely top-tier consumer-grade products, not computing behemoths designed for data centers—not A100s with 80GB of VRAM, let alone the newly released H100s that ordinary people couldn't possibly get their hands on.

Yet under current physical conditions, they were the first controllable computing nodes he could rapidly set up and fully manage by himself in the shortest amount of time.

This was his first proving ground for projecting the vast algorithms in his mind into the Real World.

As the city outside the window sank into the flashing neon noise, the interior of Jiang Lin's room retained not a single trace of the cozy atmosphere typical of a high school graduate's bedroom.

For this setup, Jiang Lin had preemptively rewired the outlets by the window with an independent circuit breaker, placed a carbon dioxide fire extinguisher beside the server rack, and temporarily installed an exhaust fan in the window.

Black anti-static rubber mats covered the floor.

An open server rack was securely anchored against the wall.

Jiang Lin used custom support brackets to mount the four huge RTX 3090 graphics cards side by side on the rack.

Thick power cables ran along the edges of the rack like black blood vessels, plugging into an enterprise-grade PDU.

Two sets of expensive NVLink bridges were snapped between adjacent graphics cards.

1:12 PM.

The power switch was pressed.

Accompanied by the sudden roar of industrial fans, the system booted up successfully for the first time.

Dense white characters flashed across the monitor as the Linux hardware detection log cascaded down the screen like a waterfall.

[GPU-0: Initialization Normal, Identified, VRAM 24GB]

[GPU-1: Initialization Normal, Identified, VRAM 24GB]

[GPU-2: Initialization Normal, Identified, VRAM 24GB]

[GPU-3: Initialization Normal, Identified, VRAM 24GB]

[Host ECC Memory: 256GB, Multi-Channel Topology Identified]

[NVMe Array: Striped Cache Zone Built, Read/Write Status Normal]

[PDU Status: Online]

[External Hall Effect Current Sensor: Online, Sampling Frequency 100Hz]

[UPS Status: Online, Battery Capacity 100%]

[External Temperature Sampling Module: Online, Current Ambient Temp 22°C]

[Low-Level GPU Drop Watchdog Daemon: Enabled]

Seeing that all hardware checks passed, Jiang Lin entered a series of commands into the terminal.

PCIe lane link speed test.

P2P direct access test.

Dual-GPU NVLink bandwidth stress test.

High-concurrency VRAM read/write stability test.

Host memory to device memory DMA copy rate test.

NVMe cache array concurrent read/write permissions and throughput test.

High-frequency log flushing I/O latency check.

Only after these fundamental tests—which dictated the survival of the entire high-level structure—all showed green lights did Jiang Lin hit the Enter key, launching the core scheduler he had built over long years in the Wasteland.

[MPS-Scheduler v0.1]

[Quad-GPU Asynchronous Task Slicing Test: Initiated]

The first batch of tasks fed into this computing node was the candidate space slicing verification for the MPS-Kernel.

Within this complex scheduling algorithm, tasks were mercilessly sliced up.

Semantic equivalence class slicing.

To reduce redundant computation, the algorithm needed to identify and merge logically equivalent mathematical structures, drastically trimming what would otherwise be an exponentially expanding search space through symmetry and isomorphic mapping.

Proof cache graph generation.

Dynamic allocation of benchmark sparse matrices.

As well as summarizing and archiving failed exploration branches.

Every grand category of task was sliced by the MPS-Scheduler into tensor blocks that could run independently within the VRAM.

The differently numbered GPUs acted like workers on an assembly line—uninterrupted by one another yet highly coordinated—responsible solely for processing the state interval assigned to their own VRAM.

The massive intermediate computation results were continuously streamed into the high-speed NVMe cache array.

In this ingenious architecture, full bandwidth-hogging state graph exchanges between cards were strictly avoided; they only swapped highly compressed summary information via NVLink or the PCIe bus.

This near-draconian logic for squeezing every drop of compute power and bandwidth was something Jiang Lin had deduced and refined countless times over long years in the Wasteland.

Computing power in that environment was far worse than what he had now, but precisely because of that, algorithmic optimization had been pushed to its absolute limit.

These four RTX 3090s in the Real World were merely the first tiny vessel bringing that grand logic into reality.

3:28 PM.

With a sudden surge in fan speed, the results of the first batch of stress tests finally appeared on the terminal.

[Semantic Equivalence Class Slicing: Elapsed Time 12.4s, Completed]

[Standard Candidate Library Isomorphism Deduplication Cache: Hit Rate 87.3%, Completed]

[Benchmark Sparse Matrix Solving: Completed]

[Failed Candidate Summary Archival: Passed Hash Consistency Verification]

[Quad-GPU Concurrent Scheduling Consistency: No Deadlock Detected, Passed]

[End-to-End Throughput: Increased to 6.8x Compared to Legacy Single-GPU Serial Pipeline]

[Parallel Gain 3.4x, Deduplication Cache and Task Reordering Contributed 2.0x]

[Single GPU Power Limit: 285W]

[Peak Total Power Consumption: 1500W, Within Safe Limit of Dedicated 16A Circuit]

[GPU Core Temp: Stable Below 80°C Threshold]

[VRAM Junction Temp: Peak 91°C, Below Preset Throttling Threshold]

[PCIe Bus GPU Drop Events: 0]

High-speed industrial fans tore through the air, producing a deafening noise like an airplane engine idling.

The noise was particularly jarring in the quiet residential building.

It was so loud that even Zhang Xiufen in the living room couldn't help but knock on his door, asking through the panel if something had broken.

Jiang Lin had no choice but to reassure her through the door, explaining it was just normal noise from the computer doing heavy computations.

Towards evening, the first round of full verification tasks concluded smoothly.

Next up was the G-01 prototype test.

On the floor, he had laid out a challenging test track.

To simulate unpredictable, subtle disturbances in the Real World, the height, inclination angle, and spacing of every single obstacle board were generated and cut using a pseudo-random algorithm; no two boards were identical.

This was the first physical hurdle an aperiodic embodied mobile platform had to cross to move from theory to reality.

Traditional quadrupedal or multipedal robots often relied on preset periodic gaits.

The premise of periodic gaits was that the ground was relatively flat, allowing the robot to generate forward momentum by repeatedly executing fixed phase differences.

But in a Real World environment full of rugged, unknown terrain, that assumption easily collapsed.

What it truly needed to verify was not a fancy gait pattern, but whether an event-triggered state machine could stably take control of every stance phase switch under non-repetitive contact conditions.

G-01's white polyoxymethylene (POM) foot assemblies were already installed.

Under the sidelight of the desk lamp, the fine machining grooves covering the foot surfaces were clearly visible.

A special elastic cushioning layer was tightly pressed onto the foot force sensor mount at the bottom.

Complex control and power supply cables were neatly bundled along the inner grooves of the alloy linkage arms with dustproof tape to prevent interference during movement.

The complex kinematic chains formed by the six supporting leg linkages had their spatial zeros calibrated repeatedly via mathematical matrices at the software level.

Jiang Lin picked up the control terminal beside him and opened the control program.

[G-01_Public_Demo_v0.1]

[Basic Acceptance Test: Initiated]

As the command was issued, the machine resting on the floor emitted a faint high-frequency electrical hum.

Motor drivers began sending energizing signals to the brushless motors.

The machine first entered a brief self-diagnostic mode.

On the terminal screen, status indicator lights for various subsystems flashed in sequence.

High-precision IMU calibration.

Foot strain gauge array reset.

Joint spindle motor peak current test.

Mechanical pawl position encoder zeroing.

Linkage spatial angle calculation.

Low-level hardware safety emergency shutdown link connectivity test.

As the self-diagnostic routine progressed, metrics on the screen turned from yellow to green one by one.

[Sensor Spatial Zero Matrix: Passed]

[Foot Contact Deformation Response Curve: Passed]

[Mechanical Pawl Damping Lock Status: Passed]

[Spindle Continuous Current Warning Threshold: Passed]

[Low-Level Safety Shutdown Isolation Link: Passed]

Confirming that everything was normal, Jiang Lin took a deep breath and pressed the test button on the interface.

A low hum of gears meshing echoed through the room.

G-01's first supporting leg lifted slowly, tracing a trajectory precisely calculated by inverse kinematics through the air, before landing gently on the slanted obstacle board ahead.

The moment the POM foot contacted the rough wooden board surface...

On the terminal screen, the sensor curve representing contact stress rapidly spiked upward.

The curve was smooth and continuous, showing no burrs from mechanical vibration or false peaks from misjudgments.

The system confirmed a stable touchdown, and the dynamic center-of-mass transfer matrix began calculating.

The second leg followed suit.

The third.

The fourth.

...

The heavy metal chassis began creeping forward across the irregular terrain.

Its movements were hardly seamless or natural like those of wild animals.

Nor did it feature the visually pleasing, fluid gaits seen in commercial robot promotional videos that were heavily edited and polished through motion capture.

Its gait could even be described as sluggish.

Every leg lift and every placement carried a mechanical, tentative caution.

Like a blind person using a cane to slowly feel out the abyss ahead.

Yet it was extraordinarily stable.

As it moved, its six legs did not adhere to any fixed stance phases.

The footholds of its feet did not cycle according to simple periodic formulas either.

Confronted with non-repetitive combinations of obstacle boards, the control hub did not try to force its way through using preset gait parameters.

Instead, during each fleeting physical contact, the system used the massive matrix data returned by the sensors to recalculate the environment's local stable zone within milliseconds, dynamically generating stance control variables for the next frame.

Green confirmation logs popped up continuously on the terminal:

[Non-Repetitive Obstacle Group A Local Terrain Reconstruction: Passed]

[Low-Speed Aperiodic Stance Phase Dynamic Switching: Passed]

[Lateral Micro-Physical Disturbance Introduced: Recovery Response Passed]

[Abnormal Slip Contact Shutdown Protection Logic: Passed]

[Public Video Prototype Overall Appearance and Control Status: Ready for Filming]

Jiang Lin quietly watched this machine made of metal, plastic, and wires crawl like a cautious beetle, traversing the final uneven obstacle board step by step without a single error, before coming to a steady stop on the flat ground at the finish line.

There were no cheers in the room.

Nor did Jiang Lin's face show any wild excitement over the success.

Because this seemingly breathtaking scene was something he had witnessed far too many times in the deep recesses of his long memories, in that sand-swept Wasteland World.

Only after countless tear-downs and start-overs, modifying low-level code in the ashes of failure time and again, and reshaping foot contact curves repeatedly, did G-01 finally evolve from the mechanical noise of scrap metal into an aperiodic state machine capable of surviving in extreme environments.

The version currently sitting in his Real World room was merely a basic video prototype meant for public demonstration.

Constrained by current funds and manufacturing techniques, it had been drastically scaled down and greatly simplified.

It sacrificed many redundant structures and high-voltage protection modules painstakingly designed into the Wasteland original to withstand harsh conditions.

But its core soul—the underlying mathematical logic framework—remained unchanged.

It could walk.

And in an unpredictable world, it could carve out its own aperiodic trajectory.

That was enough.

Jiang Lin walked to his desk, exported the test footage from the camera, and dragged it into the editing software timeline.

He skillfully tapped the keyboard, naming the new folder:

[Low-Entropy Workshop_G01_Public] (Low-Entropy Workshop_G01_Public Version)

Next, in the title bar of the video project file, he set a provisional title without any extra fluff:

[G-01: Aperiodic Embodied Mobile Platform Concept Demonstration]

Having done all this, Jiang Lin stood up straight.

To the left of his desk, the computing node housing four graphics cards continued to blink its faint green status lights in the dark.

The roar of the background high-speed fans had settled into a rhythmic ambient hum.

The terminal log in the background scrolled quietly and regularly.

[MPS-Scheduler: Currently in Low-Power Standby Mode]

[Next Tensor Slicing Compute Task Batch: Queue Idle, Awaiting User Input]

To the right of the desk, the G-01 test video was paused on the final frame.

That mechanical creation, which could hardly be called elegant, stood as steady as Mount Tai at the end of the non-repetitive obstacle boards, its cold metal feet gripping the floor firmly.

"Ding."

A prompt for a new unread email popped up on the computer.

The sender was Professor Han Yanshan.

The subject line of the email was very direct, devoid of any polite pleasantries:

[Jiang Lin, which day are you free recently? Can we find some time to talk about the details of that technical framework you mentioned?]

Jiang Lin merely glanced at the banner notification in the bottom right corner of the screen out of the corner of his eye.

He currently had no spare time to explain to anyone in detail what PFR was, what the Marton Route was, or what formal entropy compression built on Ruzsa distance was.

Nor was there any need for him to prove anything to the outside world through words.

The laws of mathematics are cold; they require no defense, only the process.

When the chain of deduction reached its end, and that irrefutable proof was uploaded to the preprint server, everything would naturally come to light.

Until that moment arrived, his sole task was to stay focused.

To let that GPU computing node continue devouring the shredded candidate spaces after every task input.

To let the quantitative trading plan push forward, letting the numbers in his bank account snowball to pave his staircase to higher dimensions.

And to let the public G-01 video open his first door on the engineering side.