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The “new supercomputer network going live in September” was a proposal announced in 2024—not a September 2026 launch. SingularityNET said its first machine could come online in September 2024, with a wider build-out continuing into late 2024 and early 2025. The project was intended to provide infrastructure for advanced AI and eventual artificial general intelligence (AGI), but the available evidence does not establish that it became operational at the proposed scale or produced AGI.
What was actually announced?
In August 2024, SingularityNET representatives described a planned “multi-level cognitive computing network”: a distributed or federated collection of powerful computers intended to support advanced AI research and the company’s AGI ambitions.
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Company CEO Ben Goertzel linked the project to SingularityNET’s OpenCog Hyperon framework. Reporting by Live Science said the first system was expected to come online in September 2024, while additional machines could be added through the end of 2024 and into early 2025, depending partly on component deliveries.
That timeline matters. The original reporting was published in August 2024 by Futurism and Live Science. “September” referred to September 2024, not September 2026.
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The proposed hardware
Live Science reported a heterogeneous hardware plan involving:
- NVIDIA L40S GPUs
- AMD Instinct accelerators
- AMD Genoa processors
- Tenstorrent Wormhole server racks featuring NVIDIA H200 GPUs
- NVIDIA GB200 Blackwell systems
This should be read as a reported project design, not as an independently verified production cluster. The available sources do not establish the final GPU count, completed installation record, power budget, network topology, sustained performance, or benchmark results.
How the software was supposed to work
SingularityNET said it was developing software to coordinate a federated compute cluster. In principle, this could allow multiple organizations to contribute computing resources while keeping some data closer to its source rather than transferring every raw record into one central facility.
The project also identified OpenCog Hyperon as the open-source framework for its AGI-oriented architecture. SingularityNET described tokenized access as a way for participants to contribute data or obtain computing resources.
Those are architectural intentions, not proof of deployment. The reviewed reporting does not verify that OpenCog Hyperon was successfully run across the proposed hardware, that the federated system coordinated a single coherent AGI workload, or that tokenized access solved the associated security, privacy, governance, and accounting challenges.
Why more computing power could help
Large-scale computing can make it possible to train larger models, run longer experiments, process multimodal data, perform simulation and search, and evaluate systems across more tasks. A distributed network could also give researchers access to specialized hardware in multiple locations.
But compute is an enabling resource, not an AGI result. More hardware does not automatically provide general reasoning, reliable world models, continual learning, safe agency, or robust transfer to unfamiliar problems.
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What “AGI” means here
Artificial general intelligence is not a universally agreed technical specification. In the original coverage, it referred broadly to a hypothetical system capable of exceeding human intelligence across multiple disciplines and improving with additional data.
It helps to distinguish several categories:
- Specialized AI: Systems optimized for defined tasks.
- Frontier foundation models: Broad systems with powerful but uneven capabilities.
- Agentic systems: Models connected to tools, memory, planning, and workflows.
- AGI: A contested concept involving broad, reliable, adaptable intelligence.
- Artificial superintelligence: A hypothetical system substantially beyond human cognitive ability.
Consequently, “could usher in AGI” was a possibility claim associated with SingularityNET’s ambitions—not a measured technical specification or independently verified prediction.
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What can be verified now?
The available sources support the following conclusions:
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- The first machine was expected to come online in September 2024.
- The reported hardware plan was broad and heterogeneous, including NVIDIA, AMD, and Tenstorrent-related systems.
- OpenCog Hyperon and federated-computing software were part of the stated vision.
- No reviewed source verifies that the network reached the advertised scale.
- No reviewed source verifies that it trained or delivered AGI.
The available current material also does not establish whether the specific SingularityNET network was completed, what hardware was ultimately installed, or whether it became a functioning global AGI platform. That is different from proving that the project never advanced; it means the stronger success claims are not established by the evidence available here.
Do not confuse it with newer AI-supercomputing projects
RIKEN’s RIKYU
RIKEN’s RIKYU is a separate AI-for-science supercomputer. RIKEN said it was preparing for full-scale operation in July 2026, with 400 NVIDIA GB200 NVL4 nodes, 1,600 Blackwell GPUs, and NVIDIA Quantum-X800 InfiniBand. It reported more than 15.539 exaFLOPS in FP8 and more than 64.16 petaflops in FP64.
RIKYU is associated with RIKEN’s Advanced General Intelligence for Science Program, but the announcement does not identify it as SingularityNET’s network or claim that it is intended to create general-purpose AGI.
The U.S. Department of Energy’s Genesis Mission
The DOE Genesis Mission is another separate initiative. It describes a national AI-for-science platform connecting supercomputers, experimental facilities, AI systems, and specialized datasets for scientific discovery, energy, and national-security priorities.
OpenAI’s large-scale networking work
OpenAI’s MRC announcement concerns networking technology for very large AI-training clusters, not the SingularityNET proposal. It illustrates the engineering required to keep huge systems productive, but it does not validate the 2024 AGI claim.
What would count as evidence of AGI progress?
A credible evaluation would need more than a hardware announcement. It would ideally include:
- A concrete operational definition of AGI.
- Independent testing across unfamiliar domains.
- Evidence of transfer and adaptation rather than memorization.
- Long-horizon planning and tool-use results.
- Robustness under distribution shifts and adversarial conditions.
- Reproducible experiments and clearly reported methodology.
- Independent confirmation that the network operated as described.
A large cluster can support this research, but it cannot substitute for the architecture, data quality, evaluation standards, safety controls, and scientific evidence needed to establish general intelligence.
Verdict
SingularityNET’s announcement described ambitious proposed infrastructure for AGI research. It did not demonstrate an AGI system, and the September date was September 2024—not a future September 2026 launch. The most accurate description is that the network could have supplied computing resources for AGI development; the evidence does not support saying that it ushered in AGI or became a verified global AGI platform.
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