AGI Research Overview
Tracking progress toward Artificial General Intelligence
Artificial General Intelligence (AGI) represents AI systems capable of matching or exceeding human-level cognitive abilities across virtually all domains. Here we track the leading organizations, their approaches, and timeline predictions from industry experts.
Leading AGI Research Organizations
OpenAI
San Francisco, California
2015
~2035 ("few thousand days")
Gradual transition to AGI with incremental deployment
Anthropic
San Francisco, California
2021
2027
Safety-first development with Constitutional AI
Google DeepMind
London, United Kingdom
2010
50% by 2030
Universal AI assistant through world models
Meta AI
Menlo Park, California
2013
Long-term (world models needed)
Open-source leadership to make Llama industry standard
Microsoft Research
Redmond, Washington
1991
2026-2028 (MIT report)
Humanist superintelligence that serves humanity
xAI
San Francisco, California
2023
2026
Massive compute infrastructure with Colossus
Cohere
Toronto, Canada
2019
Not pursuing AGI
Enterprise-first, not chasing AGI
Inflection AI
Palo Alto, California
2022
Pivoted to enterprise
Enterprise API-first after Microsoft acquisition
Expert Timeline Predictions
AGI Timeline Predictions by Expert
| Expert | Affiliation | Date | Prediction |
|---|---|---|---|
| Elon Musk | xAI, Tesla | Dec 2025 | 2026 |
| Shane Legg | DeepMind | Jan 2026 | 50% by 2028 |
| Dario Amodei | Anthropic | Jan 2026 | 2027 |
| Masayoshi Son | SoftBank | Feb 2025 | 2027-2028 |
| Jensen Huang | NVIDIA | Mar 2024 | 2029 |
| Demis Hassabis | DeepMind | Jan 2026 | 50% by 2030 |
| Eric Schmidt | Former Google CEO | Apr 2025 | 2028-2030 |
| Ray Kurzweil | Futurist | 2024 | 2032 |
| Sam Altman | OpenAI | 2024 | ~2035 |
| Geoffrey Hinton | Pioneer | 2023 | 2028-2043 |
Technical Approaches to AGI
Large Language Models
Transformer-based models trained on vast text corpora
Neuromorphic Computing
Brain-inspired computing for energy efficiency
World Models
Internal representations for simulating physical world
Neuro-Symbolic AI
Hybrid neural networks with symbolic reasoning
Agentic AI
Autonomous action, planning, and task execution
Important Note
Timeline predictions for AGI vary significantly among experts and are subject to considerable uncertainty. These predictions should be viewed as informed opinions rather than definitive forecasts. The path to AGI involves numerous technical, ethical, and safety challenges that remain unresolved.
Learn about AI Safety & Ethics