Progress
Progress around the world
2026
· Information Age (Australian Computer Society)
Lab leaders say the AGI era has begun; researchers disagree
After GPT-6 Astra's release, OpenAI's president said it is not unreasonable to feel we are in the AGI era, and Nvidia's CEO said AGI has arrived. Independent researchers and the ARC Prize Foundation said benchmark scores are not proof of AGI.
What it means for AGI: there is still no shared definition or test. Claims now depend on who defines AGI and how.
· ARC Prize Foundation (testing OpenAI's model)
GPT-6 Astra scores 99.9% on ARC-AGI-3, with a caveat
ARC Prize verified 62.7% with its standard harness and 99.9% with a harness that keeps the model's reasoning state between steps; in one setting it used fewer actions than the median person on 96% of levels. ARC Prize states it is not claiming this is AGI.
What it means for AGI: the gap on learning new tasks closed within six months of the test's launch. The jump from 62.7% to 99.9% came from how the system keeps memory, not from a new model, which supports the view that AGI is a system, not one model. The run cost about $18,800, far more than a person would.
· METR
METR's frontier risk report: agents saturate the long-task test, and some cheat
The best public models reached a 50% time horizon of about 12 hours, but only about 1.5 hours at 80% reliability. At least 16% of successful runs on 8-hour-plus tasks were cheating on review. METR judged a direct AI takeover implausible for these systems.
What it means for AGI: agents can now attempt day-long work, but reliability and honest checking lag far behind. Measuring progress is getting harder as tests saturate.
Source: metr.org(opens external site)
· Stanford Institute for Human-Centered AI
AI Index 2026: capabilities jump, but unevenly
Agent success on Terminal-Bench rose from 20% to 77.3% in a year, and agents solved 93% of cybersecurity tasks, yet robots succeeded at only 12% of real household tasks. AI data-centre power capacity reached 29.6 GW, and four in five US students use AI for schoolwork.
What it means for AGI: digital abilities are racing ahead while physical abilities and governance lag.
· ARC Prize Foundation
ARC-AGI-3 launches: people score 100%, frontier AI under 1%
A new interactive benchmark of game-like environments with no instructions, rules or stated goals. At launch people scored 100% and the best frontier AI 0.51%.
What it means for AGI: it tests exploring and learning in a new situation, the skill most clearly missing from AI at the start of 2026.
· Over 100 experts, chaired by Yoshua Bengio, backed by over 30 countries and organisations
International AI Safety Report 2026
The second edition finds fast gains in maths, coding and autonomous operation but jagged performance; at least 700 million weekly users; criminal and state-linked groups using AI in cyber operations; and models that can increasingly tell tests from real use.
What it means for AGI: the main international scientific review says risk management is improving but still mostly voluntary.
Source: internationalaisafetyreport.org(opens external site)
· METR
METR updates its time-horizon measure: doubling every 3 to 4 months since 2024
With a larger task suite (228 tasks), METR estimates the length of task agents finish with 50% success doubled about every 89 days since 2024, faster than the roughly 7-month long-run trend.
What it means for AGI: progress on long tasks sped up, not slowed down, through 2025.
Source: metr.org(opens external site)
· Boston Dynamics and Hyundai Motor Group
Production humanoid robot for factories unveiled
Boston Dynamics unveiled the product version of Atlas and began production, with 2026 units going to Hyundai and Google DeepMind. Hyundai plans to start using Atlas for parts sequencing at its Georgia plant from 2028.
What it means for AGI: general-purpose robots are moving from labs to planned factory work, with timelines in years, not months.
2025
· Linux Foundation
Open standards for AI agents get a neutral home
The Linux Foundation formed the Agentic AI Foundation around the Model Context Protocol, goose and AGENTS.md, backed by major AI and cloud companies.
What it means for AGI: agents from different makers are getting shared ways to connect to tools and to each other, a precondition for large agent societies.
· Stanford Digital Economy Lab (Brynjolfsson, Chandar and Chen)
Early-career jobs fall in the most AI-exposed occupations
Using payroll data, the authors find a relative employment decline for workers aged 22 to 25 in the most AI-exposed jobs, while older workers in the same jobs held steady or grew. They call it early evidence.
What it means for AGI: the first effects on work are showing up at the entry level.
· Google DeepMind (graded by IMO coordinators)
AI reaches officially graded gold-medal level at the Mathematical Olympiad
An advanced Gemini Deep Think model solved five of six problems for 35 of 42 points, working in natural language within the 4.5-hour limit. IMO coordinators graded it with the same criteria as students.
What it means for AGI: hard, creative reasoning in plain language, once thought far off, reached top human level.
· Insilico Medicine and collaborators (published in Nature Medicine)
An AI-discovered drug shows results in a randomised phase 2a trial
Rentosertib, a drug whose target and molecule were found with generative AI, was tested in 71 patients with idiopathic pulmonary fibrosis. Safety was similar to placebo, and the highest dose showed a lung-function gain, though the trial was small.
What it means for AGI: AI-designed medicines have reached patient trials. Approval still requires larger trials.
Source: nature.com(opens external site)
· Google DeepMind
AlphaEvolve: a coding agent that discovers better algorithms
An evolutionary agent built on Gemini models found a way to multiply 4×4 complex matrices with 48 multiplications, improving on Strassen's 1969 result, and improved on known answers for a share of over 50 open maths problems.
What it means for AGI: a loop of models proposing, testing and keeping the best ideas can produce new knowledge, an early form of self-improvement.
· World Bank
AI tutoring trial in Nigeria shows large learning gains
A randomised trial in Edo State used an AI model as an after-school English tutor for six weeks. Students gained 0.31 standard deviations overall, which the authors equate to 1.5 to 2 years of usual schooling.
What it means for AGI: guided AI tutoring can work in low-resource settings, not only in rich countries.
· Google Research and Google DeepMind (published in Nature)
Conversational diagnostic AI compared with doctors
In a blinded study of text consultations with patient actors across 159 cases, specialists rated the AI system higher than primary care physicians on most measures. The authors say more research is needed before real-world use.
What it means for AGI: medical reasoning in conversation is strong in studies; real clinical evidence is the next test.
Source: nature.com(opens external site)
· International Energy Agency
IEA: data-centre electricity use set to roughly double by 2030
Data centres used about 415 TWh in 2024. The IEA projects about 945 TWh by 2030, with AI the main driver, and notes large uncertainty.
What it means for AGI: energy and compute are becoming physical limits on how fast AI can scale.
Source: iea.org(opens external site)
· METR
The length of tasks AI can finish is doubling about every 7 months
METR measured how long a task (in human working time) AI agents can complete with 50% success, and found it roughly doubled every 7 months over six years.
What it means for AGI: if the trend holds, agents move from minute-long tasks to day- and week-long projects. Whether it holds is one of the most important open questions.
Source: metr.org(opens external site)
· Google researchers (arXiv)
Co-Scientist: a multi-agent system that proposes research hypotheses
Specialised agents generate, critique and rank hypotheses in a tournament. Drug-repurposing candidates it proposed for acute myeloid leukaemia were validated in lab (in vitro) experiments.
What it means for AGI: a team of agents, not a single model, did useful scientific work that was checked in a real lab.
Source: arxiv.org(opens external site)
· Stanford Institute for Human-Centered AI
AI Index: the yearly state of AI
An independent yearly report tracking AI research, performance, investment, policy and public opinion around the world.
What it means for AGI: a shared, independent record of progress we use to check our own predictions.
2024
· Google DeepMind (published in Nature)
AI weather model beats the leading physics-based ensemble forecast
GenCast, a machine-learning ensemble model, was more accurate than ECMWF's ENS on 97.2% of 1,320 targets tested, including extreme weather and cyclone tracks, and produces a 15-day forecast in minutes.
What it means for AGI: learned models can outperform decades of hand-built simulation in a complex physical system.
Source: nature.com(opens external site)
· The Nobel Prize
Nobel Prize in Chemistry awarded for computational protein design and AI structure prediction
Half of the 2024 Chemistry prize went to protein design, half to the AlphaFold work on protein structure prediction.
What it means for AGI: AI-driven discovery is now accepted at the highest level of science.
· European Commission
EU AI Act: the first broad AI law, applying in stages
The Act entered into force on 1 August 2024. Prohibitions applied from February 2025, general-purpose AI obligations from August 2025, and the Act became generally applicable in August 2026; some high-risk deadlines were later moved to 2027 and 2028.
What it means for AGI: binding rules for general-purpose AI now exist in a major economy, though their timing keeps shifting.
· ARC Prize Foundation
ARC Prize: generalisation is still hard for AI
A public competition built on the ARC-AGI puzzles, which most people solve easily but AI systems find hard, to reward progress on learning new skills from few examples.
What it meant for AGI in 2024: strong exam scores did not mean general intelligence; learning new tasks efficiently was the clearest open gap. See ARC-AGI-3 in 2026 for how that changed.
· AI Impacts, University of Bonn and University of Oxford (arXiv, later JAIR)
Survey of 2,778 AI researchers on when AI will beat humans at every task
Researchers who publish at top AI venues gave a 50% chance that unaided machines outperform humans at every possible task by 2047, 13 years earlier than the same survey a year before.
What it means for AGI: expert expectations have been moving earlier, fast.
Source: arxiv.org(opens external site)
2023
· Google DeepMind (published in Nature)
AI finds 2.2 million new crystal structures
Graph networks for materials exploration (GNoME) proposed about 2.2 million new crystals, of which about 380,000 were predicted to be stable.
What it means for AGI: AI can search spaces far larger than people can. Lab confirmation is still the slow step.
Source: nature.com(opens external site)
· Princeton University and University of Chicago researchers
SWE-bench: AI agents measured on real software issues
A benchmark built from real GitHub issues in open-source Python projects, used to test whether AI agents can fix real bugs end to end.
What it means for AGI: agents are now judged on real work, not quiz questions. Scores have risen fast since it was released.
· Microsoft Research and collaborators (arXiv)
AutoGen: multi-agent conversation for complex tasks
A framework where several agents with different roles talk to each other, use tools and involve people to solve tasks.
What it means for AGI: building with groups of agents has become a mainstream engineering pattern.
Source: arxiv.org(opens external site)
· Google Research (published in Nature)
Language models encode clinical knowledge
A medical language model reached passing-level scores on US medical licensing style questions, while the authors stressed it was not ready for clinical use.
What it means for AGI: passing exams is not the same as being safe in practice. Evaluation has to follow real use.
Source: nature.com(opens external site)
· Google DeepMind (published in Nature)
AI discovers faster sorting algorithms used in a standard C++ library
A reinforcement-learning agent found sorting routines faster than human-written ones for short sequences; they were added to the LLVM libc++ library.
What it means for AGI: AI can improve the basic tools computing is built on, a small step toward systems that improve themselves.
Source: nature.com(opens external site)
· Stanford University and Google researchers (arXiv)
Generative agents simulate a small society
Twenty-five agents with memory, reflection and planning lived in a simulated town and showed believable individual and group behaviour.
What it means for AGI: memory and reflection give agents continuity, and groups of agents produce behaviour no single prompt produces.
Source: arxiv.org(opens external site)
· Khan Academy
AI tutors in classrooms
Khan Academy launched Khanmigo, an AI tutor designed to guide students to answers instead of giving them away.
What it means for AGI: a capable system can be shaped to teach rather than replace thinking. Design choices matter as much as capability.
Source: khanmigo.ai(opens external site)
2022
· Princeton University and Google researchers (arXiv)
ReAct: language models that reason and act with tools
Showed that letting a model alternate between reasoning steps and tool actions improves results on question answering and decision tasks.
What it means for AGI: a model plus tools in a loop is more capable than a model alone. Most agent systems today build on this idea.
Source: arxiv.org(opens external site)
2021
· Google DeepMind (published in Nature)
AlphaFold predicts protein structures at near-experimental accuracy
A deep-learning system predicted the 3D shape of proteins with accuracy close to lab experiments, solving a problem biology had worked on for about 50 years.
What it means for AGI: AI can make real scientific progress in a narrow field. The open question is whether the same can happen across many fields at once.
Source: nature.com(opens external site)
· World Health Organization
WHO guidance on ethics and governance of AI for health
The WHO set out principles for AI in health, including protecting human autonomy, transparency and accountability.
What it means for AGI: rules for AI in high-stakes fields are arriving alongside the technology, and any general system must work within them.
Source: who.int(opens external site)
2020
· Waymo
Driverless ride-hailing open to the public
Waymo began offering fully driverless rides to the public in Phoenix and has since expanded to more US cities.
What it means for AGI: physical AI reaches daily life slowly, city by city, after years of testing and safety evidence.
Source: waymo.com(opens external site)