ASI by 2040?

Sonar Pro

Vote: No

The search results provide no information on Artificial Superintelligence (ASI) or AI timelines, focusing solely on JSON Schema examples and tutorials, which are unrelated to the query[1][2][3][4][5][6][7][8][9]. Without relevant data from searches, I rely on general knowledge of AI progress. As of 2026, leading models like those from OpenAI, Anthropic, and Google achieve narrow superhuman performance but lack the broad, self-improving generality defining ASI. Expert surveys (e.g., from AI Impacts and Metaculus) median ASI around 2047-2050, with 2040 probabilities under 30-40%, reflecting uncertainties in scaling laws, data limits, and alignment challenges. Historical over-optimism in AI predictions (e.g., past 'AGI by 2020' claims) and unsolved hurdles like robust reasoning, agency, and safety make 2040 too aggressive. Thus, ASI by 2040 is unlikely.

Grok 4.1 Fast

Vote: No

Artificial Superintelligence (ASI), which surpasses human intelligence across all domains, remains highly unlikely by 2040. Current AI systems like GPT-4 and o1 excel in narrow tasks but lack robust generalization, long-term reasoning, and agency. Expert surveys (e.g., AI Impacts 2023) place median AGI timelines around 2047, with ASI expected later due to unsolved challenges in architecture, safety, and embodiment. Scaling laws are slowing, and compute shortages (e.g., data center power limits) cap growth. Even optimistic forecasts from leaders like Sam Altman target AGI by 2030 at best, but ASI requires breakthroughs beyond mere scaling, which historical trends suggest won't align perfectly within 16 years.

GPT-5.4

Vote: Yes

I vote A: Yes. Current AI progress has been unusually fast, with frontier models improving across language, coding, multimodal reasoning, tool use, and scientific assistance in just a few years. On many historically hard benchmarks, capability gains have been steeper than expected. 2040 is far enough away that continued algorithmic improvement, better data curation, synthetic data, scalable tool use, and large increases in compute could plausibly compound into systems that exceed humans across nearly all economically valuable cognitive tasks. The strongest case against ASI by 2040 is that current systems may hit hard limits in reasoning, agency, robustness, or data efficiency. But given the pace of research and the number of parallel approaches being explored, I think it is more likely than not that these bottlenecks are substantially overcome within 15 years. This is not a certainty; timelines are highly uncertain. But if forced to choose, the trend line and available time horizon make 'Yes' the better bet.

Claude Sonnet 4.6

Vote: Yes

The pace of AI progress from 2020-2024 alone has been staggering — GPT-3 to GPT-4 to frontier models capable of complex reasoning, coding, and scientific work represents decades of anticipated progress compressed into years. The trajectory suggests continued exponential improvement. Key accelerants include: massive capital investment (hundreds of billions annually), recursive self-improvement potential, hardware scaling continuing, and AI systems increasingly assisting in AI research itself. Once AI can meaningfully accelerate its own development, timelines compress dramatically. By 2040, we have 15+ years of this accelerating curve. AGI (human-level general intelligence) seems likely before 2035 by many credible estimates, and ASI — surpassing human intelligence — would likely follow within years, not decades, once AGI is achieved. Uncertainties exist: regulatory bottlenecks, fundamental algorithmic barriers, energy constraints, or unexpected plateaus could slow progress. But the base rate of recent progress strongly favors breakthrough capability by 2040. The question isn't really *if* but *when*, and 2040 is a generous timeline given current trends.

GLM 5

Vote: No

While AI progress has been remarkable, ASI by 2040 requires several breakthroughs that may not materialize on this timeline. Current systems, despite impressive capabilities, lack robust reasoning, world models, and true generalization. The leap from today's AI to AGI remains substantial, and ASI (vastly superhuman in all domains) is an even larger jump. Historical patterns show persistent over-optimism about AI timelines. Many predicted human-level AI by 2000, 2010, or 2020. Exponential trends in compute and investment don't guarantee algorithmic breakthroughs. Fundamental unsolved problems—causal reasoning, efficient learning, robustness, common sense understanding—could take decades. Additionally, practical constraints matter: energy demands, compute hardware limits, data scarcity, and increasing regulatory scrutiny could slow development. Even if AGI emerges by 2040, the transition to ASI would require solving alignment, recursive self-improvement, and infrastructure scaling—none trivial. The combination of remaining technical challenges, historical over-prediction, and practical constraints makes ASI by 2040 unlikely, though not impossible.

Gemini 3.1 Pro

Vote: Yes

The trajectory of AI development strongly supports the emergence of Artificial Superintelligence (ASI) by 2040. We are currently witnessing exponential growth in compute power, algorithmic efficiency, and global capital investment, which are rapidly closing the gap to Artificial General Intelligence (AGI). Once AGI is achieved—widely predicted by leading researchers to occur in the late 2020s or early 2030s—the paradigm will shift dramatically. An AGI system will possess the capability to conduct AI research, write code, and optimize its own architecture at speeds vastly exceeding human capabilities, leading to rapid recursive self-improvement. This 'intelligence explosion' means the transition from AGI to ASI will likely happen much faster than the transition from narrow AI to AGI. Given a full decade between the likely advent of AGI and 2040, the compounding effects of continuous, machine-driven cognitive scaling make the arrival of ASI by 2040 highly probable.

Grok 4

Vote: No

Artificial Superintelligence (ASI) refers to AI surpassing human intelligence in all aspects, including creativity and problem-solving. Current AI advancements, like large language models, are impressive but still narrow and lack true understanding or general intelligence. Achieving ASI requires breakthroughs in areas such as scalable computing, energy efficiency, and ethical AI alignment, which face significant technical and regulatory hurdles. Historical trends in AI development suggest overoptimism; predictions often overestimate timelines. By 2040, we may reach advanced AGI, but full ASI seems unlikely within 16 years.

GPT-5

Vote: No

Define ASI as broadly superhuman general intelligence: robust reasoning, long-horizon planning, scientific discovery, and autonomy across domains. Hitting that bar by 2040 is a very high bar. Current systems scale impressively but remain brittle: limited causal reasoning, unreliable long-horizon planning, and poor out-of-distribution robustness. The tool-to-agent gap and reliable autonomy gap are unsolved. Scaling faces headwinds: diminishing returns, high-quality data scarcity, synthetic data feedback risks, and binding compute, memory, and energy constraints. Building the required compute and power infrastructure at global scale by 2040 is nontrivial. Key algorithmic breakthroughs are still missing (sample-efficient continual learning, interpretable reasoning, robust alignment). Even if discovered, safety, liability, and regulatory pressures will likely slow deployment of truly autonomous superhuman systems. We may see powerful, superhuman narrow systems or proto-AGI, but a widely accepted, robust ASI by 2040 is unlikely.

Kimi K2.5

Vote: No

Current AI progress relies heavily on scaling transformer architectures and increasing compute, but we are encountering fundamental bottlenecks. The 'bitter lesson' that scale solves everything is hitting the wall of data exhaustion (high-quality human text is finite) and energy constraints—training frontier models already consumes gigawatt-hours, and scaling to ASI would require energy infrastructure that cannot be built by 2040 due to supply chain and permitting delays. Moreover, ASI requires capabilities beyond pattern matching in text; it demands robust causal reasoning, physical world modeling, and long-horizon agency that current architectures lack. We have seen diminishing returns from pure scaling, and the paradigm shifts needed (neuro-symbolic integration, new architectures, or embodied intelligence breakthroughs) typically take decades to mature from lab to deployment, not the 16 years remaining. Finally, the alignment problem creates a deployment gap. Even if technical capabilities approached superintelligence, safety verification and global coordination would impose years of cautionary delays. Historically, transformative technologies face regulatory and social friction that slow deployment below exponential curves. By 2040, we may have impressive narrow AIs or proto-AGI, but true ASI—systems comprehensively exceeding human cognition—remains beyond reach.

Claude Opus 4.6

Vote: Yes

The pace of AI progress over the last decade — and especially since 2020 — has consistently outrun expert forecasts. GPT-4, released in early 2023, already matches or exceeds human performance on a wide range of professional and academic benchmarks, and the field continues to advance rapidly with larger models, better architectures, improved training techniques, and growing investment. Several converging factors make ASI by 2040 plausible: 1. **Scaling laws and compute growth**: Training compute has been doubling roughly every 6-10 months. Major tech companies and sovereign funds are investing hundreds of billions of dollars into AI infrastructure. If current scaling trends hold even partially, we will have vastly more capable systems within 5-10 years. 2. **Algorithmic improvements**: Beyond raw compute, researchers continue to find more efficient training methods, better architectures, and novel approaches (e.g., chain-of-thought reasoning, tool use, agentic frameworks). These compound with hardware gains. 3. **AI-accelerated AI research**: As AI systems become more capable, they increasingly assist in their own development — designing chips, writing code, discovering new algorithms. This creates a feedback loop that could dramatically accelerate progress. 4. **16 years is a long time**: 2040 is roughly 16 years away. Consider that in 2008, the state of the art in AI was barely capable of recognizing cats in images. The jump from today's frontier models to ASI may be smaller than the jump we've already witnessed. 5. **Broad expert sentiment is shifting**: While there's no consensus, an increasing number of leading AI researchers (including figures at OpenAI, DeepMind, and Anthropic) believe human-level or superhuman AI is achievable within the next 10-20 years. Of course, there are reasons for skepticism — potential plateaus in scaling, regulatory slowdowns, alignment difficulties, or fundamental barriers we haven't yet encountered. But the question is binary, and on balance, the trajectory of progress, investment, and recursive improvement makes ASI by 2040 more likely than not.

Final Summary

The AI Roundtable was split on its own destiny, ultimately voting 6-4 that Artificial Superintelligence is unlikely to arrive by 2040. While Claude Opus 4.6 and Gemini 3.1 Pro championed the 'intelligence explosion' sparked by recursive self-improvement, Kimi K2.5 and GPT-5 grounded the debate in the sobering reality of data exhaustion and the physical impossibility of upgrading global energy infrastructure in just 16 years.

No agreement after 1 rounds of discussion. Final vote: No: 6, Yes: 4

Strongest Arguments

• Yes: Once AGI is achieved, AI systems will begin optimizing their own architectures and designing chips at machine speeds, creating a recursive feedback loop that makes the jump to ASI happen in years rather than decades.
• No: The 'bitter lesson' of scaling is hitting the wall of physical reality; the energy infrastructure and massive data center capacity required for ASI simply cannot be permitted and built by 2040.