University of Kwazulu-Natal

When Will We Get Agi Agi Timelines Dashboard

Bonisiwe Shabane
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when will we get agi agi timelines dashboard

From the forecasting site Metaculus, full title: "When will the first weakly general AI system be devised, tested, and publicly announced?" From the forecasting site Metaculus, full title: "When will the first general AI system be devised, tested, and publicly announced?" From the forecasting site Metaculus, full title: "When will an AI first pass a long, informed, adversarial Turing test?" From the prediction market Manifold Markets, full title: "AGI When? [High Quality Turing Test]" From the prediction market Kalshi.

Shows probability (0-100%) that AI passes the Turing test before 2030. Here's what keeps AI researchers awake at night: Every major AI system is accelerating faster than anyone predicted. The question isn't if artificial intelligence will surpass human intelligence—it's when. And according to our analysis of 12+ leading AI models and expert predictions, that "when" might be sooner than you think. // CLASSIFICATION: UNCLASSIFIED // SOURCE: MULTI-MODEL ANALYSIS // UPDATED: REAL-TIME // We asked the smartest AI systems on Earth when they think AGI will happen.Their answers might surprise you.

Median expert prediction for AGI arrival Timelines for AGI have trended down sharply since 2022. View full prediction on Metaculus → Although not the only driver of stock prices, markets price in AGI expectations through AI company valuations. Sudden moves often reflect breakthrough announcements or capability demonstrations before they hit mainstream awareness. Real-time model capability rankings track which models receive the best scores from human evaluators.

For the full rankings and methodology, visit https://lmarena.ai/leaderboard/text. The processing power of AI hardware continues to increase dramatically, enabling larger and faster models. NVIDIAs GPUs are currently the favored AI training platform. The human brain uses roughly 5,000 PFLOPS. Leading edge AI model training is happening in massive data centers that are larger, and consume far more power, than traditional data centers. We analyzed 8,590 scientists’, leading entrepreneurs’, and the community’s predictions for quick answers on Artificial General Intelligence (AGI) / singularity timeline:

Explore key predictions on AGI from experts like Sam Altman and Demis Hassabis, insights from major AI surveys on AGI timelines, and arguments for and against the feasibility of AGI: This timeline outlines the anticipated year of the singularity, based on insights gathered from 15 surveys, including responses from 8,590 AI researchers, scientists, and participants in prediction markets: As you can see above, survey respondents are increasingly expecting the singularity to occur earlier than previously expected. Below you can see the studies and predictions that make up this timeline, or skip to understanding the singularity. TechCrunch's Equity podcast hosts discussed major tech developments from 2025 and made predictions for 2026, focusing on AI funding, physical AI, and AI agents. They noted that AI agents underperformed expectations in 2025 but predicted significant advancement in 2026, while also discussing concerns about AI-generated content in Hollywood and venture capital liquidity challenges.

Skynet Chance (+0.01%): The prediction of AI agents maturing in 2026 suggests incremental progress toward more autonomous AI systems, which could marginally increase concerns about AI control and alignment. However, this represents expected evolutionary progress rather than a sudden capability breakthrough that would significantly alter risk profiles. Skynet Date (+0 days): The anticipated maturation of AI agents in 2026 and continued mega-funding rounds suggest steady acceleration of AI capabilities deployment. The modest negative score reflects incremental speedup in autonomous AI systems entering practical use, though not dramatically faster than the expected trajectory. AGI Progress (+0.01%): The discussion of AI agents approaching practical viability and the rise of "physical AI" indicates progress toward more general and embodied AI systems. The acknowledgment of significant AI funding continuing suggests sustained investment in advancing capabilities toward more general intelligence.

AGI Date (+0 days): The prediction that AI agents will fulfill their promise in 2026 after underperforming in 2025, combined with ongoing mega-funding rounds, suggests acceleration in practical AI deployment. This indicates the pace toward AGI-relevant capabilities may be slightly faster than previously expected, though tempered by the noted 2025 delays. In recent months, the CEOs of leading AI companies have grown increasingly confident about rapid progress: Is it just hype? What explains the shift? And could we really have Artificial General Intelligence (AGI)2 by 2028?

In this article, I interrogate these claims. I’ll examine what’s driven recent progress, estimate how far those drivers can continue, and explain why they’re likely to continue for at least four more years. In particular, while in 2024 progress in LLM chatbots seemed to slow, a new approach started to work: teaching the models to reason using reinforcement learning. In just a year, this let them surpass human PhDs at answering difficult scientific reasoning questions, and achieve expert-level performance on one-hour coding tasks. In recent years, the promise of Artificial General Intelligence (AGI)––AI capable of performing any intellectual task that a human being can––has captured the public imagination and ignited fierce debates across technological, industrial, and political... Major tech CEOs and renowned AI experts have offered divergent timelines and predictions regarding when AGI might become a reality.

This article examines the detailed landscape of these predictions while exploring the technological challenges, societal implications, and economic consequences of AGI development. We will also review insights from key players such as DeepMind’s Demis Hassabis, Anthropic CEO Dario Amodei, OpenAI’s Sam Altman, and others to provide a comprehensive analysis of the trajectory toward human-level and superintelligent... AGI is typically defined as an AI system that exhibits the full range of human cognitive abilities. Unlike narrow AI—which is designed to excel at a specific task such as image recognition or language translation—AGI must generalize its learning across multiple domains, adapt to unforeseen scenarios, and ultimately match or even... As Google DeepMind CEO Demis Hassabis famously explained, AGI would be “a system that’s able to exhibit all the complicated capabilities that humans can” (“Google DeepMind CEO Predicts A Decade-Long Wait For AI To... Despite significant progress in language models and algorithmic planning, current systems remain “very passive,” lacking the breadth and depth required to navigate the complexity of the real world.

Transforming these narrow successes into a robust, general intelligence that understands context, reason, and abstract concepts stands as one of the most formidable tasks in the field. Tech leaders across the globe have provided a wide range of forecasts regarding the timeline for achieving AGI. On one end of the spectrum, some experts are optimistic about early breakthroughs, while on the other, more cautious voices argue for a longer developmental horizon. Demis Hassabis of Google DeepMind has been one of the most measured voices in the arena. Speaking at a recent briefing in London, Hassabis predicted that the first forms of AGI might emerge in the next five to ten years (“Human-level AI will be here in 5 to 10 years,... Although he acknowledged that current AI technologies excel at certain specific tasks, he stressed that significant research remains before these systems can operate with the generalized intelligence of a human being.

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