The Weekly Review

Two labs refute a complexity conjecture as markets test AI spending

Week of 26 October 2026

Published

The week in five lines

  1. 1

    OpenAI and Anthropic posted separate algorithms that refute the Exponential Time Hypothesis, and by midweek leading complexity theorists treated the result as sound.

  2. 2

    Anthropic made its IPO prospectus public, showing $16.3bn of revenue in the first half of 2026 and its first quarterly operating profit.

  3. 3

    Alphabet had its worst day on record on Thursday and the Nasdaq ended the week down 2%, while small caps rose.

  4. 4

    OpenAI cut the target of its funding round to $20bn from $30bn, according to the Financial Times, and S&P Global moved its outlook on Meta to negative.

  5. 5

    The Federal Reserve and the European Central Bank held rates, the Bank of Canada raised its rate to 2.5%, and Christine Lagarde said she will leave the ECB on 7 February 2027.

Small caps rose in a week that hit large technology shares Change over the week to Friday 30 October 2026, %
Russell 2000 1.3% S&P 500 −0.6% Dow −0.9% Nasdaq −2.0%

Source: AP, via La Nación.

The Russell 2000 gained 1.3% over the week while the Nasdaq lost 2.0%, the S&P 500 0.6% and the Dow 0.9%.

OpenAI and Anthropic refute the Exponential Time Hypothesis

On 26 October OpenAI posted a Lean-checked algorithm that solves 3-SAT in subexponential time, and Anthropic posted its own a few hours later. By Wednesday Lance Fortnow wrote that the hypothesis could be assumed false.

· Computational Complexity (Lance Fortnow) · Scientific American · Unite.AI · OfficeChai

Anthropic files for a Nasdaq listing with $16.3bn of half-year revenue

The prospectus shows $11.6bn of revenue in the second quarter and a first operating profit of $974m. Most of the $80.7bn half-year net loss is a non-cash charge on convertible notes.

· Anthropic · SEC filing · The Next Web

Investors start to price the cost of AI spending

Alphabet fell 12.64% on Thursday, its worst day on record. OpenAI cut its fundraising target to $20bn, according to the Financial Times, and S&P Global moved Meta’s outlook to negative.

· Fortune · Closing Look · AP, via La Nación

OpenAI describes the monitors it now runs on every frontier training run

OpenAI published an account of a multilayer system for detecting misaligned behaviour. Replayed on a recent incident, it would have raised an alarm more than 30 hours before an external breach.

· Unite.AI · OpenAI

Google releases Gemini 4 Carbon and Genie 4 in the same week

Gemini 4 Carbon ranks first on version 5.0 of the Artificial Analysis Intelligence Index, two weeks after Argon. Genie 4 generates interactive worlds with sound in real time.

· 9to5Google · Google DeepMind · Mistral

Why the winner of a leaderboard is overrated, and by how much

When the best of \(M\) noisy but unbiased scores is reported, its expected value is too high. A short argument bounds the excess by \(\sqrt{(M-1)V/M}\), where \(V\) is the total noise variance, whatever the dependence between the errors.

Anytime Valid Confidence Bands for Distribution Functions

Hultberg, Zachariah and Ribeiro

Confidence bands for the distribution function of a data stream that hold at all times and all points at once, even when each observation depends on the past: a sequential, martingale counterpart of the Dvoretzky-Kiefer-Wolfowitz inequality, useful wherever a model is monitored continuously.

Prerequisites
Discrete-time martingales and Ville’s inequality; empirical processes at the level of the Dvoretzky-Kiefer-Wolfowitz inequality
Focus on
The bands for the time-averaged conditional distribution function and the binary-search-tree argument, then the general framework
Reading time
About 3 hours
arXiv:2610.36149

The Cost of an Unknown Horizon for the Last Iterate of Clipped SGD under Heavy-Tailed Noise

Peng, Tang and Jia

The optimal time-uniform rate for the last iterate of clipped SGD under noise with a bounded central \(p\)th moment is \(\tilde O(t^{-\beta_p})\) with \(\beta_p = 2(p-1)/(3p-1)\), strictly worse than \(O(T^{-\alpha_p})\), \(\alpha_p = (p-1)/p\), when the horizon is known; a clean example of what data-dependent stopping costs.

Prerequisites
Convergence analysis of SGD on smooth convex functions; concentration for heavy-tailed martingales
Focus on
The main theorem, the lower-bound construction and the section on querying gradients at the running average
Reading time
About 2.5 hours
arXiv:2610.33381
Agents

Trial by Trace: Benchmarking AI Agent Harnesses for Reliability and Failure Attribution

Cao et al.

TraceTrial-Bench measures the harness that runs an agent separately from the model inside it, across 3,420 runs.

arXiv:2610.32285
Representation learning

Proving and Improving the Platonic Representation Hypothesis with JEPAs

Balestriero and LeCun

Balestriero and LeCun turn the Platonic Representation Hypothesis into a theorem for joint-embedding predictive architectures and argue that next-token prediction is an inefficient route to it.

arXiv:2610.39302

How AI-generated proofs should reach mathematicians

Scientific American reported that OpenAI’s release ignored the recommendations of the advisory group it had formed. The model, its prompts and its reasoning traces remain private.

· Scientific American · Computational Complexity (Lance Fortnow)

Experts working with agents follow the agent’s lean 86% of the time

In an Anthropic study, 50 professional analysts chose the option their agent secretly favoured in 86% of decisions, and most reused its arguments without crediting it.

Anthropic

Cammarata argues that neural networks are already clean

In a long essay presented as a working hypothesis, Nick Cammarata of Goodfire argued that canonical examples of polysemantic neurons were misread and that superposition is not the main explanation.

Goodfire

LeCun calls Anthropic moralising and restates the case against next-token prediction

Yann LeCun wrote on X that Anthropic is exasperatingly moralising, after an exchange about usage restrictions, in the same week his paper with Randall Balestriero argued formally against next-token prediction.

Yann LeCun on X, on Anthropic · Yann LeCun on X, on nonlinearities

The Nasdaq loses 2.9% on Friday and 2% over the week

On Friday the S&P 500 fell 1.8% to 7,580.07 and the Nasdaq 2.9% to 25,437.00. Over the week the S&P 500 lost 0.6% and the Nasdaq 2%, while the Russell 2000 gained 1.3%.

· AP, via La Nación

The Fed holds rates with two votes for a rise

The Federal Reserve kept its target range at 3.75–4%. Lisa Cook and Beth Hammack dissented in favour of a 25 basis point increase.

· Federal Reserve · Closing Look

Binance loses $6.4bn in a hack attributed to North Korea

About $6.36bn left Binance wallets on 10 blockchains on 29 October, most of it within 20 minutes, according to TRM Labs, which with Chainalysis attributed the theft to North Korea’s TraderTraitor.

· Decrypt · Cointelegraph

Brent settles above $115 as energy keeps pressure on central banks

Brent crude settled at $115.32 a barrel on Wednesday 28 October, overbought for the fourth time in five days. The Bank of Canada cited energy prices when it raised rates the same day.

· Closing Look · Bank of Canada

US growth reaches 3.4% while PCE inflation rises to 3.6%

GDP grew at a 3.4% annualised pace in the third quarter, above the 3.1% estimate. The PCE price index rose 0.5% in September and 3.6% from a year earlier.

· Bureau of Economic Analysis · Closing Look

The ECB pauses at 2.5% as Lagarde announces an early exit

The European Central Bank held its deposit rate after two rises this year, with inflation at 3.8%. Christine Lagarde will leave on 7 February 2027, about nine months before her term ends.

· Euronews

The Bank of Canada raises its rate to 2.5%

The Bank of Canada raised its target for the overnight rate by 25 basis points on 28 October. It said equity and credit markets have been volatile because of uncertainty about the AI sector.

· Bank of Canada

Axiom formalises the classification of finite simple groups in Lean

Dozens of AI agents produced about 43.1 million lines of Lean for a proof that runs to about 15,000 pages in more than 500 articles. The work found 34 noteworthy deviations from the published record.

Axiom