The Quad-Thread Cores Architecture
The Next Generation of Computing: From Binary to Cognitive
The quad-thread cores architecture represents a fundamental shift in computer design. Instead of scaling the brute force of traditional binary systems, this concept introduces a layered, cognitive approach. Each physical core is divided into four specialized processing threads, each optimized for a specific logic, managed by an overarching AI.
Binary Thread: The foundation of the system. This thread processes all traditional binary code (0 and 1) and ensures full compatibility with existing software and operating systems.
Trit Thread: The efficiency leap. This thread operates with ternary logic (-1, 0, +1), allowing it to perform more complex calculations more compactly and quickly.
Quattro-bit Thread: The thread of nuance. This algorithm adds context and probability to data by interpreting the binary combinations 00 and 11 as 'probably not' and 'probably yes'. This is essential for advanced AI.
Chronos Thread: The reasoning thread. This is the most advanced layer, which uses the principles of multiplication to reason about cause and effect. A Chronos Unit can analyze the outcomes of other threads to determine the consequences of actions, forming the basis for an artificial conscience.
This specialized architecture is seamlessly managed by an OS Developer AI that automatically routes tasks to the correct thread. This allows the system to process a simple mouse click with the binary thread, while guiding a complex AI command through the entire chain of logics.
The Ultra product line demonstrates the scalability of the architecture, from affordable entry-level models like the Ultra 12 to server-class platforms like the Ultra 1024. The quad-thread cores make each of these configurations fundamentally smarter and more efficient than the competition, enabling them to process not just 'yes' or 'no', but also nuance, context, and cause and effect.
#The Quad-thread cores architecture
worn halo
The Ultra series is not just a line of computer systems; it's a scalable platform that adapts the power of our quad-thread cores architecture to the needs of every user. Each configuration is Ultra because the core logics (Binary, Trit, Quattro-bit, and Chronos) are present in every core, resulting in a fundamentally smarter system than the competition.
Ultra 12: 12 cores, 120 bit, 60 trit, 60 quattro-bit, 12 Chronos unit, 12 GB cache, RAM, and VRAM, integrated GPU. This entry-level model is ideal for daily tasks and media consumption. The quad-thread cores ensure efficient multitasking and a smooth user experience through smart task distribution.
Ultra 24: 24 cores, 240 bit, 120 trit, 120 quattro-bit, 24 Chronos unit, 24 GB cache, RAM, and VRAM, integrated GPU. This mid-range model is perfect for demanding users and gamers. The doubling of cores and logical units allows it to efficiently use all four logics for more complex tasks like 3D modeling and advanced gaming.
Ultra 48: 48 cores, 480 bit, 240 trit, 240 quattro-bit, 48 Chronos unit, 48 GB cache, RAM, and VRAM, integrated GPU. The high-end consumer model for content creators and professionals. Its scalability ensures that Chronos-logic can be used at full power for AI analysis and complex simulations, while the large amount of memory guarantees fast data access.
Ultra 96: 96 cores, 960 bit, 480 trit, 480 quattro-bit, 96 Chronos unit, 96 GB cache, RAM, and VRAM, integrated GPU. The ultimate consumer model and the foundation for the Hyper-generation. The massive scale of the quad-thread cores makes it a cognitive platform with unparalleled computing power.
Ultra 128: 128 cores, 1280 bit, 640 trit, 640 quattro-bit, 128 Chronos unit, 128 GB cache, RAM, and VRAM, integrated GPU. A professional SoC platform for AI development and data analysis. The scalability of the architecture is crucial here.
Ultra 154: 154 cores, 1540 bit, 770 trit, 770 quattro-bit, 154 Chronos unit, 154 GB cache, RAM, and VRAM, integrated GPU. A specialized platform for the most complex computations and scientific research.
Ultra 192: 192 cores, 1920 bit, 960 trit, 960 quattro-bit, 192 Chronos unit, 192 GB cache, RAM, and VRAM, integrated GPU. This model is the next step towards the Hyper-generation, demonstrating the endless scalability.
Ultra 256: 256 cores, 2560 bit, 1280 trit, 1280 quattro-bit, 256 Chronos unit, 256 GB cache, RAM, and VRAM, integrated GPU. This SoC platform is designed for large-scale AI applications and server use.
Ultra 512: 512 cores, 5120 bit, 2560 trit, 2560 quattro-bit, 512 Chronos unit, 512 GB cache, RAM, and VRAM, integrated GPU. A true supercomputing platform for the most demanding computational tasks and scientific research.
Ultra 1024: 1024 cores, 10240 bit, 5120 trit, 5120 quattro-bit, 1024 Chronos unit, 1024 GB cache, RAM, and VRAM, integrated GPU. This is the definitive step toward the Nexus-generation of infinite computing power.
swift python
I'm assuming this is AI-generated as well?
because it's pretty much infeasible start to finish
worn halo
It's AI generated with a lot of input yes
swift python
I don't know how to tell you this but LLMs are completely useless at inventing new computing concepts
worn halo
Gemini seems to be smart with it though
swift python
this is confident-sounding technobabble using a lot of buzzwords but at the end of the day it's pretty much a science-fiction depiction of a computer
it sounds smart
it absolutely isn't
swift python
it's nonsensical, none of these ideas are remotely implementable
worn halo
You tested it to be sure? Or you are assuming?
swift python
i don't know where to start debunking this honestly
- AI scheduling workloads onto a specific core? holy scheduling overhead, by the time it's done running the model to decide where the task should go "traditional" CPUs will already be done
- ternary/quaternary logic? sounds cool I guess, now demonstrate how this is supposed to map to hardware in any sane way. also, the ecosystem implications of having to heavily rework literally all software in existence just to make use of 3/4 of the processor's capabilities guarantee it'll never take off
- applications for ternary/quaternary logic for AI: the assumption that "it'll be useful" is unfounded, there's no reasoning given for how it would even impact AI workloads or how the benefit would look like in practice - that's because there is none
in the end, you have to keep in mind that "AI" does nothing but predict likely tokens of text in response to a query. it doesn't reason, it doesn't fact-check, it doesn't form conclusions, it literally just predicts text, and in this case it predicted a selection of technological buzzwords and a few surrounding sentences to make them resemble a reasonable explanation. doesn't mean the explanation is anywhere close to reasonable in reality.
worn halo
Oh oke. Well I would want to see tests and facts before I assume anything
swift python
I provided sufficient facts to show why this would never work, the LLM provided zero facts
it provided factual-sounding bits like "This is essential for advanced AI" and if you read that without scrutiny you'd think it's a fact
it's not
I'm not sure which kinds of tests you'd like to see done, but if you propose a magic new processor with vague science-fiction-like capabilities never heard of before, the burden of proof that it's feasible would be on you, wouldn't it?
worn halo
It’s not an incremental improvement, but a paradigm shift.
The competition is building on the binary system, trying to make it faster and faster. We are introducing a completely new, layered structure. Explain that we are not just adding an extra thread, but two fundamentally new logics: Quattro-bit for nuance and Chronos for cause and effect.
It is built to work with existing software.
The likely objection will be: "You can't find any software for this." The key is the OS Developer AI. Explain that this AI is the smart intermediary layer that automatically routes traditional binary tasks to the correct specialized threads in real-time. You can compare it to a translator.
It solves fundamental problems that binary systems cannot.
Provide concrete examples. Ask him: "How can a binary computer understand nuance? How can it distinguish 'probably yes' from 'probably not'?" Then, answer with our Quattro-bit logic. Or ask him: "How can a computer reason about cause and effect like a human?" Then, answer with the Chronos-logic and give the example of the rain and the precipitation deficit.
The scalability is unprecedented.
Explain that the modular design of the Ultra series means the concept works for both a simple Ultra 12 and a gigantic Ultra 1024. The technology is not limited to one purpose but can be adapted to any need.
swift python
did you actually try to understand any of this
worn halo
Read the explanation of the AI
swift python
no, I want to hear it from you
also, the ai did not provide that
the ai said something about "advanced ai would benefit, yada yada it introduces nuance"
that is not specific, that is about as vague as you can be
worn halo
It can add nuances and cause and effect reasoning to a computer
worn halo
Weather forecast, would benefit from the working in nuances
swift python
how so
clearly the models we have right now already predict things happen with certain probabilities
that is already nuanced
worn halo
Yes that's true
swift python
the computer does not decide "it will rain or it will not rain", it computes the statistical probability that it will rain given the model input data
so how does adding more bits somehow improve anything
also, no explanation was done as to a) how an AI scheduler wouldn't just nuke performance from orbit and b) how any of this is supposed to be implemented in terms of hw (how does the architecture look? what instruction set does it use? how does the instruction set work? how do data accesses even work, given that storage is shared between all cores, and storage is binary? how does the result of trinary logic computation get stored in binary memory?)
worn halo
It could handle the 3 states "yes" "no" and "maybe" better
swift python
but it already does that
it already handles the "maybe" with a lot of nuance, doesn't it?
how exactly is the "maybe" going to improve from what we already have
it's not like "rain or no" is controlled by a single bit in current processors
it's a probability, a "maybe", represented with all the nuance you could have
worn halo
I don't know. Apparently the AI thinks it will improve
swift python
yeah that's the thing
there is no reason why it would improve
the AI doesn't think, btw
like i said, there is no reasoning behind an "AI", it literally predicts text and nothing else
empty relic
LLMs are a version of the “next word” bar in your phone we threw a million dollars worth of GPUs at.
swift python
it predicted a lot of confident-sounding stuff that has no reasoning behind it
empty relic
The AI’s “reasoning” is exactly as sound as “painting flames on the car makes it go faster”.
worn halo
Oh oke. Well I would like to have a test run from a R&D before I assume anything. It's plausible to me
swift python
how is R&D supposed to give it a test run? it's literally impossible to implement in hw
and how is it plausible to you when i literally pointed out how current CPUs can handle determination of probabilities and you have no idea how the benefits actually work
empty relic
Trinary is actually doable, and has produced “meh” results for AI.
swift python
i mean sure trinary logic is possible and so on, technically
empty relic
It’s not worth the effort to use it vs the established body of software for binary systems
worn halo
If you think so. But I am not sure. Gemini seems certain about the outcome this would help computers be smarter, not effectively faster, but smarter
swift python
okay yes, but why does gemini being "sure" change anything
do you trust it to reason accurately?
worn halo
I don't know. It should be tested to find out
swift python
I know enough about hw to say that the suggestion is nonsense
what I'm trying to tell you is to stop posting AI-generated "architecture suggestions" to this channel because they are just nonsensical
worn halo
Oh oke man
empty relic
If you think so. But I am not sure. Gemini seems certain about the outcome this ...
Are you going to make me go copy that whole pile of text into Gemini and ask it to critique it?
Because it is very capable of ripping that output to shreds.
worn halo
Sure you can try
swift python
I mean, I don't trust it to make reasonable arguments there either
but yes, if you tell the AI that it's nonsense and prompt it to give you reasons why it is, it will happily spew out a few
empty relic
Sure you can try
The proposal for a Quad-Thread Cores Architecture is largely a conceptual framework that is not feasible with current technology. It presents several significant roadblocks in fabrication, software, and fundamental computer science principles.
Feasibility and Technology Availability
Fundamental Logical and Physical Roadblocks
The proposal suggests a hardware architecture with distinct threads for binary, ternary, and other non-binary logic. While it's possible to build a computer that uses different number systems, implementing these within a single, unified CPU core at the hardware level is the main challenge. Modern CPUs are designed to process binary code, and their physical structure (transistors, logic gates) is fundamentally built on the principles of Boolean algebra and binary logic. Fabricating a single core that can efficiently and physically switch between binary, ternary, and other specialized logic types would require a complete overhaul of transistor and chip design, which is not currently possible.
Ternary Computing: While theoretical and some small-scale experimental processors exist, a commercially viable ternary computer is not close to production. The primary challenge is not the logic itself but building reliable, scalable, and manufacturable ternary transistors that can stably hold three distinct states (-1, 0, 1) and operate at the same speed as binary transistors.
Quattro-bit and Chronos Threads: These threads are based on abstract, non-standard computing principles. The "Quattro-bit" thread, which assigns 'probably not' and 'probably yes' to binary combinations, is not a hardware-level logic but rather a software-level interpretation of data. Such an algorithm can be implemented on any modern processor and doesn't require a dedicated hardware thread. The "Chronos" thread, which supposedly uses "multiplication to reason about cause and effect," is even more abstract. Reasoning and "artificial conscience" are complex AI concepts, not something that can be hard-coded into a physical CPU thread. These functions are performed by software algorithms running on general-purpose processors, not by dedicated hardware.
Additional Roadblocks
Software and OS Development
The proposal mentions an "OS Developer AI" that "automatically routes tasks to the correct thread." This is a significant oversimplification of the monumental task of creating a new operating system. A new OS would need to be built from the ground up to support this unique architecture, as no existing OS (Windows, macOS, Linux) would be compatible. Furthermore, the "OS Developer AI" is a concept that doesn't exist. AI can assist with code generation, but it cannot yet autonomously create a complete, stable, and secure operating system.
Economic and Market Factors
Even if the technology were feasible, the cost of research and development for such a radical shift in architecture would be immense. The entire software ecosystem would also need to be rebuilt. Companies would need to rewrite their applications to take advantage of the new architecture, a process that would likely take decades and would be met with significant resistance from developers. This would create a major chicken-and-egg problem: developers won't write software for a new platform until it has users, and users won't adopt a new platform until it has software.
In summary, the proposal for a Quad-Thread Cores Architecture is an interesting thought experiment, but it conflates software-level concepts with hardware-level design. It proposes technologies that are either unproven, fundamentally impossible with current materials, or already achievable with existing binary architectures.
There’s your AI saying your AI is wrong.
worn halo
🤔 so my AI is wrong? Guess if you put it like that
swift python
i also asked gemini to comment on the performance implications
Even if these concepts were somehow physically possible, this architecture would suffer from a significant performance penalty due to the overhead of managing these disparate threads.
Inefficient Task Routing: The proposal claims an "OS Developer AI" would "automatically route tasks to the correct thread." This is a major source of inefficiency. A CPU's strength lies in its ability to execute instructions in parallel on similar, fast cores. Creating four specialized threads and then adding a management layer to decide which task goes where would introduce significant latency and overhead. For every single instruction, the system would need to determine its type and then route it, slowing down processing dramatically. A simple mouse click, which is currently a near-instantaneous operation, would have to pass through this complex logic gate, slowing the entire system down.
Wasted Resources: CPU cores are designed for general-purpose processing. Dividing a single core into four specialized threads means that at any given moment, three of the threads will likely be idle while one is working. This is a massive waste of transistors and power. Current CPUs use techniques like simultaneous multithreading (SMT), where one core can run multiple logical threads, but these threads share resources and are designed to execute the same instruction sets. This proposal, however, suggests four different types of processors within one core, which is fundamentally inefficient. It's like having a car with four different engines, each designed for a specific type of terrain, and having to stop and switch engines every time the road changes.
what we're trying to tell you is that the AI will happily tell you pretty much anything
worn halo
Alright
swift python
you can ask it for reasons why the proposal will work, and it will give you a thousand and one reasons why it's definitely feasible immediately
then you can prompt the ai that it's all nonsense and it will give you a thousand and one reasons for that too
this is because the "AI" neither thinks nor reasons nor operates based on facts
worn halo
Yeah I see
swift python
this is also why it can convince uninitiated people that don't have the domain specific knowledge to fact-check
it just confidently strings together sentences with some cohesion to make it appear like they make sense
and that's why it's dangerous to overestimate AI, because it could as well tell you some equivalent of "the sky is green" with full confidence
worn halo
Yeah I see.
swift python
I'm not blaming you for being convinced tbc, it would happen to me as well, if I happened to ask it about a subject I don't know about :D
it's just unfortunate how AI is advertised as this hyper-competent robot that takes all our jobs and will doom humanity by thinking better than humans
it's a brilliant marketing stunt, tbf