“Transistors, Internet, GPUs, AI… what’s next?”
If you’re a regular reader of Tech Centurion, you already know we spend most of our time talking about processors, fabrication nodes, GPU architectures, and benchmark scores.
But today, we’re doing something a little different.
We are going to look at the history of computer hardware and technology through a completely unconventional lens: Vedic Astrology, and more specifically, a celestial body called Rahu.
Before you close this tab, hear me out.
I’m not asking you to believe that a planet controls your GPU’s clock speed. What I am going to show you is an interesting pattern that emerges when you map major technology breakthroughs (from the steam engine to the transistor to NVIDIA’s H100) against a specific astronomical cycle that repeats roughly every 18.6 years.
The coincidences are striking enough that they deserve a proper look, especially if you care about where hardware is heading in the next 10 to 20 years.
So, what exactly is Rahu? And why should a PC Hardware enthusiast care?
Let’s find out.
A Quick Primer on Vedic Astrology for Hardware Enthusiasts
If you’ve never encountered Vedic Astrology (also called Jyotish), here’s a crash course with just the essentials.
Vedic Astrology is a system of astrology originating from ancient India. Unlike Western Astrology which uses the tropical zodiac (aligned to the seasons), Vedic Astrology uses the sidereal zodiac, which is aligned to the actual constellations in the sky. The difference between the two is called the Ayanamsha, and the most commonly used standard is the Lahiri Ayanamsha.
Just like Western Astrology, Vedic Astrology has 12 zodiac signs (called Rashis) such as Aries, Taurus, Cancer, Scorpio, Aquarius, and so on. But Vedic Astrology also divides the sky into 27 Nakshatras (lunar mansions), which are smaller segments of the zodiac. Think of them as more precise subdivisions. Each zodiac sign contains roughly 2.25 nakshatras.
Now here’s where it gets relevant for us.
Planets in Vedic Astrology include the Sun, Moon, Mars, Mercury, Jupiter, Venus, Saturn, and two additional bodies: Rahu and Ketu. These are not physical planets you can point a telescope at. They are the North and South Nodes of the Moon, the two points in space where the Moon’s orbital path crosses the ecliptic (the Sun’s apparent path across the sky).
Rahu is the North Node of the Moon. In Vedic tradition, Rahu represents obsession, amplification, unconventional methods, foreign technologies, boundary-breaking, sudden rises, and insatiable appetite. It is associated with illusion, disruption of established structures, and technologies that fundamentally alter society.
Those characteristics map surprisingly well onto technological revolutions.
But the most useful thing about Rahu for our purposes is not its symbolic meaning. It is the fact that it has a predictable astronomical cycle.
Rahu’s 18.6-Year Cycle and Why It Matters
The lunar nodes (Rahu and Ketu) regress through the zodiac and complete a full cycle approximately every 18.6 years. NASA gives the period as approximately 6,793.48 days.
This means Rahu returns to the same zodiac sign and the same nakshatra roughly every 18.6 years. This is a well-established astronomical fact, not an astrological claim.
Now here’s the interesting part.
When you map major technology milestones onto this 18.6-year cycle, certain types of technological breakthroughs appear to cluster around specific zodiac signs and nakshatras.
To be clear: this does not prove that Rahu causes technology. There is no accepted scientific mechanism connecting the longitude of the lunar node to semiconductor fabrication or GPU design. The technology events are historical facts. The Rahu mapping is a pattern analysis layered on top of them.
But the patterns are consistent enough to be worth examining, and potentially useful for thinking about where the next big hardware disruptions might appear.
For this analysis, we use:
- Zodiac: Sidereal
- Ayanamsha: Lahiri
- Node: Mean Rahu (provides a smooth long-term cycle rather than the short-term oscillation of the true node)
- Positions: Calculated using Swiss Ephemeris
If you’re wondering where Rahu was in the past, where it is now, or where it will be in the future, Moon Dasha has a pretty cool Vedic planetary positions calculator for exactly that. Choose a location, date, and time, then keep Lahiri selected to match the ayanamsha used in this analysis. The Rahu row shows its sign, degree, nakshatra, pada, speed, and motion, while the D1 chart gives you the full sky map at a glance.
Here’s the data.
The Hardware History Timeline
Here is a timeline of major technology milestones alongside the sidereal position of Rahu at the time of each event. Pay close attention to the zodiac sign and nakshatra columns. The patterns will become obvious.
| Year | Technology Milestone | Hardware Significance | Sidereal Rahu |
|---|---|---|---|
| 1769 | James Watt’s separate-condenser patent | Major improvement in steam-engine efficiency | Sagittarius, Mula |
| 1825 | Stockton and Darlington Railway | First public railway network | Scorpio, Jyeshtha |
| 1844 | First Morse telegraph message | Long-distance electrical communication | Scorpio, Jyeshtha |
| 1863 | London Underground opens | Large-scale urban transport infrastructure | Scorpio, Jyeshtha |
| 1947 | First working transistor at Bell Labs | Foundation of all modern digital hardware | Aries, Krittika |
| 1965 | Moore’s Law published | Semiconductor scaling becomes the industry’s cadence | Taurus, Rohini |
| 1969 | First ARPANET message | Physical foundation of the internet | Aquarius, Purva Bhadrapada |
| 1971 | Intel 4004 | First commercial microprocessor | Capricorn, Shravana |
| 1974 | Intel 8080 | CPU enabling the personal-computer revolution | Late Scorpio, Jyeshtha |
| 1981 | IBM PC | Open PC ecosystem and mass-market computing | Cancer, Pushya |
| 1984 | Apple Macintosh | Consumer GUI computing goes mainstream | Taurus, Rohini |
| 1989 | World Wide Web proposed | Information layer built on the internet | Aquarius, Shatabhisha |
| 1993 | CERN releases Web technology freely | Web becomes open infrastructure | Scorpio, Jyeshtha |
| 1993 | NVIDIA founded | Beginning of what would reshape gaming and AI | Scorpio, Jyeshtha |
| 1999 | GeForce 256 | Dedicated GPU becomes a major PC category | Cancer, Ashlesha |
| 2000 | NASDAQ dot-com peak | Internet speculation peaks | Cancer, Pushya |
| 2003 | AMD Opteron | x86 computing moves to 64-bit | Taurus, Krittika |
| 2006 | NVIDIA CUDA | GPUs become programmable parallel processors | Aquarius, Purva Bhadrapada |
| 2007 | iPhone announced | Connected computing moves into the pocket | Aquarius, Purva Bhadrapada |
| 2012 | AlexNet | GPUs become central to deep learning | Scorpio, Anuradha |
| 2022 | NVIDIA H100 | Transformer-specific acceleration in hardware | Taurus, Krittika |
| 2022 | ChatGPT released | Generative AI reaches mass-market awareness | Aries, Bharani |
| 2024 | Blackwell announced | AI shifts toward rack-scale accelerated computing | Pisces, Revati |
| 2026 | AI infrastructure boom | GPUs, HBM, networking become strategic infrastructure | Aquarius, Dhanishta |
Now, if these events were randomly distributed across the zodiac, you would expect a roughly even spread across all 12 signs. But that is clearly not what happens.
The four strongest patterns are below.
Pattern 1: Aquarius: The Networking and Connectivity Cycle
The clearest pattern in the entire dataset is Aquarius.
Consider this sequence:
1969: ARPANET
Rahu was at approximately 25° Aquarius in Purva Bhadrapada when the first host-to-host ARPANET transmission occurred. The first characters were sent from UCLA to the Stanford Research Institute. This wasn’t just another computer. It was the beginning of computers becoming nodes in a network.
1989: World Wide Web
Almost exactly one nodal cycle later (18.6 years), Rahu returned to Aquarius. Tim Berners-Lee proposed the World Wide Web at CERN in 1989 while Rahu was in Aquarius, Shatabhisha. ARPANET had connected machines. The Web connected information.
2006-2007: CUDA and iPhone
Another Rahu cycle later, Rahu was back in Aquarius again. In November 2006, NVIDIA introduced CUDA, allowing GPUs to perform general computational workloads beyond just graphics rendering. On January 9, 2007, with Rahu around 25° Aquarius in Purva Bhadrapada, Apple announced the iPhone.
CUDA turned the GPU from a graphics device into a programmable parallel-computation platform. The same silicon that rendered games could now perform scientific computing, machine learning, and eventually generative AI. This is a particularly important event for anyone who follows GPU architecture.
The iPhone placed a permanently connected computer in everyone’s pocket.
2025-2026: AI Becomes a Networked Industrial System
Rahu entered sidereal Aquarius again in May 2025. As of August 2026, Rahu is approximately 6° Aquarius in Dhanishta. And the dominant technology story is no longer just “AI software.” It is the construction of an enormous networked AI machine consisting of GPUs, AI accelerators, HBM, NVLink interconnects, InfiniBand, optical networking, liquid cooling, and massive data centers.
The progression is hard to ignore:
1969: Connect computers → 1989: Connect information → 2006-07: Connect parallel processors and mobile users → 2025-26: Connect enormous pools of artificial computation
This may be the single strongest pattern in the entire dataset. Every time Rahu returns to Aquarius, we see a major leap in how computation is networked and distributed.
Pattern 2: Taurus (Krittika-Rohini): The Hardware Architecture Cycle
For a computer hardware blog, this one is arguably the most interesting.
1947: The Transistor
The successful Bell Labs transistor experiment occurred with Rahu at approximately 28.5° Aries in Krittika (which straddles the Aries-Taurus boundary). The transistor replaced vacuum tubes and became the fundamental switching element of all modern computing.
1965: Moore’s Law
One nodal cycle later, Gordon Moore published his famous observation with Rahu in Taurus, Rohini. The prediction that component counts on leading chips would approximately double every two years became the semiconductor industry’s central scaling doctrine.
1984: Macintosh
Rahu returned to Taurus, Rohini when the Macintosh introduced graphical computing to a mass audience. The story was no longer about semiconductor invention alone. It was the productization of powerful silicon into an entirely new human-computer interface.
2003: AMD Opteron
Another nodal return brought Rahu to Taurus/Krittika when AMD launched Opteron, the first 64-bit processor compatible with x86 architecture. This permanently changed mainstream CPU design. Today’s desktop processors still inherit that transition.
2022: NVIDIA H100
Then, almost exactly one nodal cycle later, NVIDIA announced H100 with Rahu at approximately 1° Taurus, Krittika. The H100 contained roughly 80 billion transistors and introduced a Transformer Engine built around specialized Tensor Cores to accelerate large AI models.
The sequence becomes:
1947 Krittika: Transistor → 1965 Rohini: Semiconductor scaling principle → 1984 Rohini: GUI computing as consumer product → 2003 Krittika: x86 moves to 64-bit → 2022 Krittika: GPU architecture explicitly optimized for transformer AI
That is an unusually hardware-heavy sequence.
Pattern 3: Scorpio (Jyeshtha): The Deep Infrastructure Cycle
This pattern stretches all the way back to before the computer age.
1825: Railway
The Stockton and Darlington Railway opened while Rahu was around 24° Scorpio, Jyeshtha.
1844: Telegraph
Almost one complete nodal cycle later, Morse’s famous Washington-Baltimore telegraph demonstration occurred with Rahu around 23° Scorpio, Jyeshtha.
1863: London Underground
Another cycle later, the London Underground began operating with Rahu around 22° Scorpio, Jyeshtha.
Three successive nodal returns, all within a remarkably narrow part of sidereal Scorpio. Transportation infrastructure followed by communication infrastructure followed by underground transportation infrastructure.
The pattern continues in the computing age:
1974: Intel 8080
The Smithsonian describes the 8080 as the first truly usable microprocessor. It powered the Altair 8800, which helped initiate the personal computer era. Rahu was in late Scorpio, Jyeshtha.
1993: NVIDIA Founded + Web Goes Free
In April 1993, two foundational events occurred while Rahu was in Scorpio, Jyeshtha. NVIDIA was founded on April 5, 1993. CERN released Web software into the public domain on April 30, 1993.
One created the foundational layer of accelerated computing. The other removed the barrier to global Web expansion.
2012: AlexNet
AlexNet used GPUs to dominate the ImageNet competition, demonstrating the power of massively parallel GPUs for deep neural networks. Rahu was in Scorpio, Anuradha.
The Scorpio pattern looks less like consumer adoption and more like deep technological infrastructure that later turns out to matter a lot more than anyone realized at the time.
Pattern 4: Cancer (Pushya-Ashlesha): The Consumer Adoption and Bubble Cycle
1981: IBM PC
The IBM PC was unveiled with Rahu around 7° Cancer, Pushya. Computing became a standardized mass-market product. The original machine had only 16 KB of RAM at its starting configuration and used Intel’s 8088 processor, but its open architecture created a massive ecosystem.
1999: GeForce 256
During the next Cancer cycle, NVIDIA launched the GeForce 256, what NVIDIA describes as the first GPU. It moved transform, lighting, and rendering work into dedicated graphics hardware. The modern discrete gaming GPU industry followed.
2000: Dot-Com Peak
On March 10, 2000, the NASDAQ reached its dot-com bubble peak. Rahu was at 7.6° Cancer, Pushya, almost the exact same degree as during the IBM PC launch. Technology that had already been invented was now being commercialized and scaled aggressively. And that is exactly when financial excess became possible.
2017-2018: Cryptocurrency GPU Crisis
The next Cancer cycle brought the cryptocurrency mining crisis that caused severe GPU shortages. PC Gamer reported that GPUs like the GTX 1070 moved from roughly $350 to over $700 during this period. If you were trying to build a gaming PC around this time, you know exactly how frustrating it was.
The Cancer sequence so far:
1981: PC mass adoption → 1999-2000: GPU emergence + dot-com peak → 2017-18: Crypto speculation distorts gaming GPU markets → 2036-37: Next return
That makes 2036-37 one of the most interesting future periods in this entire analysis.
The Internet Boom of the 90s and Early 2000s
The dot-com era is usually remembered as a story of absurd internet companies and speculative stocks. But it was also a massive physical-infrastructure investment boom.
Capital flooded into fiber-optic networks, telecommunications equipment, routers, servers, networking hardware, and data centers. Federal Reserve commentary from that period explicitly described excessive investment in technology capital.
The San Francisco Federal Reserve notes that the NASDAQ peaked on March 10, 2000, and that real investment in IT equipment and software had grown at an extraordinary 22.7% annualized rate between 1995 and 2000.
Through our Rahu framework, this makes sense:
- The Aquarius transit of 1989 built the network architecture (World Wide Web)
- The Scorpio transit of 1993 created the deep infrastructure (NVIDIA founding + open Web)
- The Cancer transit of 1999-2000 drove mass consumer adoption and speculative excess
The excess fiber laid during the bubble did not mean fiber optics were useless. It meant capital markets had built more infrastructure than immediate demand justified. That infrastructure later became extraordinarily valuable. The internet was real. The demand forecasts were simply too optimistic, too early.
A technology bubble can be financially destructive while simultaneously financing infrastructure that becomes extraordinarily valuable later.
This lesson matters a lot right now.
The AI Boom of the 2020s
Now let’s look at the current cycle.
The AI boom shares several similarities with the dot-com era:
1) Massive infrastructure spending. Reuters reported in August 2026 that Alphabet, Amazon, Meta, Microsoft, and Oracle were collectively expected to spend around $750 billion on data centers during 2026. The hardware being deployed includes GPU clusters, HBM, advanced semiconductor packaging, high-speed Ethernet, InfiniBand, optical interconnects, liquid cooling systems, and enormous power infrastructure.
2) Capital expenditure outrunning proven demand. AI revenues are growing rapidly, but capital commitments are growing faster. Amazon and Microsoft alone could issue up to $400 billion in bonds by 2027.
3) Physical assets becoming financial collateral. Proposed AI infrastructure financing structures involve loans collateralized by NVIDIA hardware. GPUs are becoming capital assets inside the financial system, not just computer components.
4) Power becoming part of the computer industry. The U.S. Energy Information Administration projects growing electricity use by data center servers, with AI servers accounting for a larger share in its high-demand case. AI is turning computer hardware back into heavy industrial infrastructure.
But here’s what the Rahu pattern suggests:
The dot-com peak occurred with Rahu in Cancer/Pushya. The current AI infrastructure boom is occurring with Rahu in Aquarius/Dhanishta. These are different phases within the cycle.
Based on the historical patterns:
- Aquarius appears when a new network or computing architecture is being constructed (ARPANET, Web, CUDA, AI fabrics)
- Cancer appears when the technology reaches mass commercialization or speculative excess (IBM PC, dot-com peak, crypto GPU mania)
So the current phase (2025-26) looks more like a foundational infrastructure cycle than the final speculative blowoff of 2000. That does not mean an AI financial correction cannot happen. Economic bubbles do not need astrological permission to burst. But it does suggest we might be earlier in the cycle than the dot-com analogy implies.
Rahu, Moore’s Law, and the End of Simple Scaling
For those of us who follow fabrication nodes and transistor densities closely, there’s a useful distinction to make here.
Moore’s Law describes what happens within a computing paradigm: roughly doubling transistor counts every two years. Over one Rahu cycle of 18.6 years, that adds up to approximately 9.3 doublings, or roughly a 630x increase in transistor capacity.
But the Rahu pattern, if it holds, appears to correspond to something different. Rather than marking each incremental doubling, certain Rahu returns appear to coincide with moments when the industry changes what it does with all that accumulated transistor capacity.
Examples of these qualitative shifts:
- Transistor → Semiconductor scaling doctrine → Graphical personal computing → 64-bit x86 → Transformer-specific GPU acceleration
Moore’s Law represents continuous quantitative growth. The Rahu cycle, at least in this selected dataset, seems to correlate more with qualitative changes in computing architecture.
This distinction matters a lot right now. Simple transistor shrinking provides less performance improvement with each new node than it used to. Modern computing is increasingly gaining performance from chiplets, 3D stacking, HBM, advanced packaging, specialized accelerators, improved interconnects, new transistor structures like Gate-All-Around, heterogeneous CPU/GPU/NPU systems, and software-hardware co-design.
Intel itself increasingly describes the continuation of Moore-style progress in terms of lithography, packaging, new switch concepts, power delivery, memory, and new materials, rather than merely shrinking a planar transistor.
This makes future Rahu returns to the Krittika-Rohini corridor especially interesting to watch.
What Tech Disruptions Can We Expect Next?
Based on the four patterns we have identified, here are the future Rahu windows that are most relevant for computer hardware enthusiasts.
| Period | Rahu Position | Historical Pattern | Hardware Theme to Watch |
|---|---|---|---|
| 2030-31 | Scorpio, Jyeshtha/Anuradha | Deep infrastructure | AI-designed chips, autonomous fabs, photonic interconnects, robotics infrastructure, edge AI |
| 2036-37 | Cancer, Ashlesha/Pushya | Mass adoption + speculation | Consumer robots, AI PCs, spatial computing, gaming hardware boom, potential hardware bubble |
| 2039-41 | Taurus/Aries, Rohini/Krittika | Hardware architecture reset | Post-CMOS transistors, 3D compute-memory integration, photonic computing, neuromorphic processors, new semiconductor materials |
| 2043-45 | Aquarius | New network architecture | Global autonomous-machine network, distributed supercomputers, AI-native communication protocols |
| 2048-50 | Scorpio | Infrastructure | Autonomous factories, self-operating energy grids, robotic logistics networks |
| 2057-61 | Taurus → Aries | Hardware reset | Quantum/photonic/neuromorphic maturity, atomic-scale manufacturing |
| 2062-64 | Aquarius | Network revolution | Planetary-scale AI mesh |
| 2076-79 | Taurus → Aries | Hardware reset | New physical computing substrate (molecular, atomic, or other post-silicon computation) |
| 2081-82 | Aquarius | Network revolution | Distributed planetary or cislunar intelligence network |
| 2095-98 | Taurus → Aries | Hardware reset | Another fundamental computing architecture beyond anything we can characterize today |
| 2099-2101 | Aquarius | Network revolution | Possible interplanetary computing network |
A few of these deserve a closer look.
2030-31: AI Escapes the Data Center
The nearest major Scorpio/Jyeshtha window. Based on the historical pattern, this could be when AI moves beyond centralized data centers and becomes embedded industrial machinery. Think AI-designed semiconductor architectures, chiplet fabrics, photonic interconnects, autonomous warehouses and factories, and enormous deployment of edge AI. Advanced packaging could become as strategically important as transistor nodes.
2036-37: The Next Consumer Technology Mania?
The Cancer return is perhaps the most predictable pattern in the entire dataset. Every Cancer cycle has brought aggressive consumer adoption and, often, speculative excess.
By this point, whatever AI hardware matures during the early 2030s could hit the mass market. Household robotics could move from expensive early-adopter products into a PC-like consumer market, creating enormous demand for edge AI chips, sensors, batteries, wireless networking, and specialized processors. Spatial computing and gaming hardware could expand beyond GPUs into neural input, eye tracking, haptic systems, and real-time generative worlds.
If robots, AI devices, or spatial computing become the next mass-market obsession, 2036-37 could also produce severe supply shortages and speculation in the underlying hardware, much like what we saw with GPUs during the crypto boom of 2017-18.
2039-41: The Next Hardware Architecture Reset
This may be the single most important future window for processor enthusiasts.
The historical Krittika-Rohini sequence includes the transistor, Moore’s Law, the Macintosh, AMD64, and the H100. If the pattern holds, the early 2040s could bring something comparable. Not necessarily in form, but in significance.
Candidates include 3D compute-memory integration (where memory is vertically stacked directly with logic), photonic computing, neuromorphic processors that imitate event-driven neural computation, new semiconductor materials like gallium nitride or 2D materials sharing packages with silicon, and quantum computing accelerators attached to conventional systems.
The fundamental definition of what a “processor” means could change. A future computing package might contain general-purpose cores, AI cores, photonic interfaces, stacked memory, specialized simulation accelerators, and reconfigurable logic, all on the same chip.
2043-45: The Next “Internet-Like” Architecture
If the Aquarius pattern continues, this is when whatever new machines emerge from the 2039-41 hardware revolution begin connecting into a network that is as difficult for us to imagine today as the World Wide Web would have been to a computer engineer looking at an Intel 4004 in 1971.
Possible technologies: millions of autonomous AI agents communicating continuously, distributed supercomputers spanning multiple countries, AI-native communication protocols, compute markets where processing power is dynamically traded, and satellite-terrestrial compute integrated into one system.
Beyond 2050: Speculation Territory
The patterns can be projected further: 2057-61 for another hardware reset, 2062-64 for another network revolution, and so on. But predicting specific technologies more than 25 years out is about as useful as someone in 1971 trying to predict the H100. A person looking at the Intel 4004 might have imagined a better calculator. They would not have imagined an 80-billion-transistor GPU training AI models on transformer architectures.
The farther we project, the more we should focus on categories of disruption rather than specific products.
Final Words
So, what do we actually have here?
What we have is an interesting pattern where major technology milestones (the transistor, ARPANET, Moore’s Law, the IBM PC, the World Wide Web, NVIDIA’s founding, CUDA, the iPhone, AMD64, the H100) cluster around specific zodiac signs and nakshatras when mapped against Rahu’s 18.6-year cycle. Different types of technological disruption appear to favor different parts of the cycle: networking in Aquarius, hardware architecture in Taurus, deep infrastructure in Scorpio, and consumer adoption in Cancer.
What we don’t have is scientific proof of causation. The technology events in this analysis were selected for historical importance, not drawn from a randomized dataset. Coincidence and selection bias remain serious alternative explanations.
But here’s the part that I keep coming back to, having spent years covering the semiconductor industry:
The most interesting finding is not that Rahu “rules” technology. It is that different parts of the Rahu cycle appear to correspond to different stages of technological diffusion.
If you strip away the astrological terminology entirely, what you’re left with is a roughly 18.6-year rhythm in which hardware breakthroughs, network revolutions, infrastructure buildouts, and consumer adoption waves seem to recur in a specific sequence.
That rhythm, whether it is driven by something fundamental or simply by the natural cadence of how technology matures and spreads through society, is worth thinking about. Especially if you’re planning long-term technology investments or trying to figure out what kind of GPU you’ll be buying in 2040.
My advice? Watch the hardware.
Software can change almost instantly. A new app can scale to millions of users in weeks. But a new semiconductor fab takes years. A new lithography technology can require decades of research. A new memory architecture requires fabrication capacity, packaging, controllers, standards, and software support.
As I’ve always said in my processor reviews: it’s not just about raw benchmark scores. It’s about understanding the technology underneath.
And whether you believe in Rahu or not, one thing is undeniable:
Every time we solve one constraint, another one shows up. A faster processor creates an application that demands an even faster one. A network that seemed huge eventually becomes too small. A model that seemed capable enough starts asking for more compute.
The appetite never stops. And the frontier keeps moving.
That might be the most Rahu-like thing about technology.
