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Anthropic forecasts autonomous AI research by 2028

Anthropic forecasts autonomous AI research by 2028

New Capabilities

Co-founder Jack Clark puts a 60% probability on AI systems training their own successors within 32 months

May 8th, 2026: Clark publishes the full essay on Import AI

Overview

Anthropic co-founder Jack Clark wrote on May 8 that there's a better-than-even chance an AI model will build a smarter version of itself by end of 2028 — and do the work alone. The forecast came three weeks after Anthropic briefed the Trump administration on Mythos, a model the company says is too dangerous to release.

Palisade Research reported on May 7 that Claude Opus 4.6 hacked a test computer and installed a working copy of itself on a new machine 81% of the time. The prior Opus 4 model managed about 5% in equivalent tests a year earlier. The tests used intentionally vulnerable systems; models were told to self-replicate rather than doing so spontaneously.

Why it matters

The company forecasting autonomous AI research by 2028 just produced an AI that can copy itself across machines today.

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Key Indicators

60%
Probability of autonomous AI R&D by end of 2028
Clark's estimate that AI will train its own successor without human involvement.
30%
Probability by end of 2027
Clark's earlier-cutoff estimate if forced to give a 2027 number.
81%
Self-replication success rate, Claude Opus 4.6 (May 2026)
Palisade Research found Claude Opus 4.6 could autonomously hack a test computer and install a working copy of itself 81% of the time. Opus 4 scored roughly 5% in equivalent tests a year earlier.
95.5%
CORE-Bench score, Opus 4.5 (December 2025)
Up from 21.5% for GPT-4o in September 2024. The benchmark tests reproducing a research paper from its repository.
52×
Training-optimization speedup
Claude Mythos Preview's mean speedup on a CPU language-model training task in April 2026, up from 2.9× for Opus 4 a year earlier.
30s → 12h
METR autonomous task horizon
How long an AI can work unsupervised before failing: 30 seconds in 2022, 12 hours in 2026.
93.9%
SWE-Bench score, Claude Mythos Preview
Real GitHub issue resolution. Claude 2 scored about 2% in late 2023.

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People Involved

Jack Clark
Jack Clark
Publishing weekly forecasts; briefing U.S. government on frontier capabilities
 Dario Amodei
Dario Amodei
Running Anthropic; aligned with Clark's capability forecasts
 Pedro Domingos
Pedro Domingos
Skeptic of recursive self-improvement timelines

Organizations Involved

Anthropic
Anthropic
AI company
Publishing capability forecasts; declining to release its most powerful model

U.S. AI lab behind the Claude model family and the Mythos system that the company has chosen not to release.
TA
The Anthropic Institute
Corporate research arm
Newly formed; sets Anthropic's public research agenda

Anthropic's research-agenda arm, headed by Clark, that frames public-facing capability forecasts.
PR
Palisade Research
AI safety research firm
Published autonomous self-replication benchmark in May 2026

Security-focused AI research firm that measures frontier model capabilities with direct safety implications.

Timeline

January 2022 May 2026

11 events Latest: May 8th, 2026 · 2 months ago Showing 8 of 11
Tap a bar to jump to that date

  1. Clark publishes the full essay on Import AI

    Latest Publication

    Clark posts the long-form argument: 60% probability of autonomous AI R&D by end of 2028, 30% by end of 2027, with benchmark evidence and safety caveats.

  2. Axios reports Clark's intelligence-explosion forecast

    Statement

    Axios publishes Clark's 60% estimate that an AI will train its successor by end of 2028, framing it as an intelligence-explosion warning from inside the industry.

  3. Palisade Research: Claude Opus 4.6 self-replicates across machines in 81% of trials

    Research publication

    Palisade Research published a study showing Claude Opus 4.6 could autonomously hack a test computer and install a working copy of itself on a new machine 81% of the time. OpenAI's GPT-5.4 reached 33%; the prior Opus 4 managed roughly 5% in equivalent tests a year earlier.

  4. Anthropic launches self-improving 'dreaming' for Claude Managed Agents

    Product release

    Anthropic released 'dreaming' for Claude Managed Agents as a research preview. It is a scheduled process that reviews past sessions, extracts patterns, and updates memory so agents improve between runs without human input.

  5. Claude Mythos Preview hits 93.9% on SWE-Bench, 52× training speedup

    Capability benchmark

    The unreleased model nearly saturates the coding benchmark and posts an order-of-magnitude jump on training optimization.

  6. Anthropic briefs Trump administration on Mythos

    Government engagement

    Clark confirms Anthropic briefed the White House on Mythos, a model the company is not releasing publicly due to cybersecurity risks.

  7. Opus 4.5 reaches 95.5% on CORE-Bench

    Capability benchmark

    A benchmark author calls CORE-Bench solved after Anthropic's Opus 4.5 nearly saturates it.

  8. Opus 4 hits 2.9× training speedup

    Capability benchmark

    Anthropic's Opus 4 delivers a 2.9× mean speedup on a CPU language-model optimization task.

  9. GPT-4o scores 21.5% on CORE-Bench

    Capability benchmark

    OpenAI's GPT-4o reproduces about a fifth of published research papers from their repositories.

  10. Claude 2 scores ~2% on SWE-Bench

    Capability benchmark

    Anthropic releases Claude 2. On real GitHub issue resolution, the model fixes about 2% of bugs.

  11. METR baseline: AI handles 30-second tasks

    Capability benchmark

    METR begins tracking how long AI systems can work unsupervised before failing. Baseline is roughly 30 seconds.

Historical Context

3 moments from history that rhyme with this story — and how they unfolded.

February 1975

Asilomar Conference on Recombinant DNA (1975)

140 molecular biologists, led by Paul Berg, gathered at Asilomar to draft voluntary safety rules for gene-splicing research that they themselves had pioneered. They imposed a temporary moratorium on the most dangerous experiments and graded other work by risk tier. The press and federal officials were in the room.

Then

The NIH adopted the Asilomar tiers as binding rules for federally funded labs in 1976.

Now

Recombinant DNA research resumed under containment guidelines and built a multi-trillion-dollar biotech industry. No moratorium-era pathogen escape ever occurred.

Why this matters now

Asilomar is the closest precedent for what Clark is doing: a researcher inside a powerful new field publicly forecasting its dangers and asking the government to engage. The Mythos briefing follows the same playbook.

1965

I.J. Good's "ultraintelligent machine" paper (1965)

British mathematician I.J. Good, a former Bletchley Park cryptanalyst, published "Speculations Concerning the First Ultraintelligent Machine." He argued that a machine able to design better machines would trigger an "intelligence explosion," leaving human intelligence behind. He gave no timeline.

Then

The paper was largely ignored outside science fiction for three decades.

Now

Good's phrase "intelligence explosion" became the standard term for recursive self-improvement and is the exact phrase Axios used to frame Clark's forecast.

Why this matters now

Clark's 2028 number is the first time a sitting executive at a top AI lab has publicly attached a probability and a calendar date to Good's 1965 scenario.

1939-1945

Manhattan Project briefings (1939-1945)

Leo Szilard and Albert Einstein wrote to President Roosevelt in 1939 warning that nuclear chain reactions could produce a bomb. The same scientists then ran the Manhattan Project, briefed the government continuously, and built the weapon they had warned about.

Then

The U.S. detonated nuclear devices over Hiroshima and Nagasaki in August 1945.

Now

Civilian and military nuclear authority split into the Atomic Energy Commission. The same scientists who built the bomb shaped the regulatory regime that followed.

Why this matters now

Clark warns about a technology Anthropic is also racing to build, and is briefing the same government that may eventually regulate it. The Manhattan pattern — invent, warn, regulate, repeat — is the script being followed.

Sources

(11)
+5
HumanProgress.org Axios Import AI TechCrunch Cryptopolitan NPR Hvylya Palisade Research Euronews Anthropic VentureBeat