2026-11-02 的 AI 资讯

AI delivers 'zero financial payoff' to most companies, Apollo economist says

Hacker News 热榜讨论帖（145 分，119 条评论）

OpenAI might rebrand its data centers as ‘AI compute campuses’

Data centers are deeply unpopular. But what if we called them something else?

AI can make tech CEOs’ lives easier. What about everyone else?

On Equity, we discuss why tech CEO statements can seem so tone deaf.

I Am the Reason OpenAI Is Killing Unlimited Chats

Hacker News 热榜讨论帖（16 分，2 条评论）

AI agent swarms in Minecraft fail to build civilization, drown in bureaucracy

Hacker News 热榜讨论帖（148 分，70 条评论）

The AI cost of JavaScript frameworks

Hacker News 热榜讨论帖（293 分，228 条评论）

Memdoor: A team of 5 Qwen3.8-27B models beats Fable 5 on LiveCodeBench Hard

Hacker News 热榜讨论帖（425 分，205 条评论）

Apple CEO says the company doesn’t ‘want to ship AI for AI’s sake’

Apple's new CEO defended the company's current position in the AI landscape.

4 days left: How TechCrunch Founder Summit helps you make more useful connections to scale

On November 4 at Boston’s SoWa Power Station, get ready for a full day packed with meaningful networking opportunities, actionable insights, and connections that could change the trajectory of your idea and startup. Register before all prices go up at the door.

Judge allows NAACP lawsuit over xAI data center pollution to move forward

An NAACP lawsuit accuses the SpaceX-owned AI company of violating the Clean Air Act.

OpenAI reportedly lowers funding target for new round

OpenAI’s latest funding round doesn't seem to be living up to expectations.

I built an AI Tamagotchi before Meta could

Mark Zuckerberg's Meta made AI look so stinking cute by giving it a squishy little face - and this holiday season, he wants to sell you a Muse Charm so you can carry your jolly AI helper around like a Tamagotchi. But I won't be buying one, because we have Muse Charm at home. It […]

Postgres 19 is late, and it's AI's fault

Hacker News 热榜讨论帖（41 分，18 条评论）

Nvidia weighs playing the cosigner for Nscale’s AI data center in West Virginia

When investors get nervous about AI spending, it helps to have the chipmaker that sells the chips offer to cosign the loan.

Ollie, a privacy-focused AI assistant, is shutting down

As an increasing number of AI assistants flood the market, the founder of Ollie, an assistant that respected its users' privacy, says it will be shutting down in a week.

Apple Intelligence is finally coming to China with iOS 27.3

Apple will launch Apple Intelligence in China with iOS 27.3, the company announced on its Chinese newsroom website, as reported by MacRumors. The Apple Intelligence features will be available first in an iOS 27.3 beta that's set to launch on November 4th, with a full iOS 27.3 release scheduled for December. This launch doesn't bring […]

Intel’s stock crashes, knocking $12B from government’s stake

Intel is being hurt by PC sales as the AI industry gobbles memory and other components causing PC prices to rise.

Anthropic expected to receive high ‘junk’ rating from credit agencies following IPO, FT report says

Blackstone's forecast is just a prediction, but naturally, a high junk rating would make it more difficult and costlier for Anthropic to raise the money to keep funding its massive spending that has undergirded its business.

Last-minute Halloween costumes for tech nerds

No Halloween costume? Just be a deceptively cute AI agent icon, a PHP vulnerability, or sleepy time Bryan Johnson.

Cracks are emerging in the AI spending boom

Big Tech is pouring billions into AI infrastructure, but mounting debt, negative cash flow, and growing investor skepticism are raising questions about the sustainability of the AI spending boom.

Sam Altman says it’s better for RAM to be in a data center than on your desk

Asked about supply chain shortages, like the ongoing RAM shortage, OpenAI CEO Sam Altman said in an interview that it's "terrible" to have RAM in personal PCs instead of data centers. During his appearance on the Cheeky Pint podcast, where he also commented on AI's impact on math, Altman said: "A lot of people want […]

The biggest names in AI are backing a new way to opt out of scraping

OpenAI, Google, Microsoft, and Anthropic say they will adopt a new standard that publishers can use to opt out of being scraped by AI, as reported earlier by Search Engine Roundtable. With this control, publishers can apply their AI training preferences across multiple AI companies, instead of setting them individually. The shared "policy token" signal […]

Google’s satellite AI server transmits its first response to Earth

Google's AI chip-equipped satellite has generated its first response from space. In a blog post on Friday, Google says it successfully booted up the satellite's Tensor Processing Units (TPUs), allowing the on-board Gemma 4 model to follow through on a prompt to create a haiku about being in space: Blue marble below Data streams in […]

Zest’s new AI agent finds restaurants and books reservations over text

Can't agree on where to eat? Zest's AI concierge can combine everyone's tastes, put restaurant options to a vote, and make the reservation.

Starbucks wants to use AI to show you a ‘personalized digital menu’ at the drive-thru

Starbucks could eventually show you a personalized digital menu when you pull up to the drive-thru. During an earnings call on Thursday, Starbucks CEO Brian Niccol said the company is going to explore "experiences that recognize participating customers as they arrive, present personalized digital menus, and make payment more effortless," as spotted earlier by More […]

Google’s first data center satellite is online and writing poetry

The first TPU in space is running a Google DeepMind Gemma 4 model and writing cheesy poetry.

Theranos whistleblower Tyler Shultz warns that the AI boom is ‘a great opportunity to go deceive people’

The cautionary Theranos tale takes on a new significance in the AI era, when companies that have never turned a profit are raising capital at trillion-dollar valuations.

Pope Leo calls for the disarmament of AI: ‘Machines are tools, not persons’

Pope Leo XIV says AI systems should be "disarmed," adding that humans "have the responsibility to guide, change and, when necessary, reject its applications." In Friday's Papal Address, Pope Leo encourages United Nations member states to "take concrete steps toward banning lethal autonomous weapons" during their meeting in Geneva next month. The address reflects many […]

Silicon Valley wants you to invest in miracles

Investing in any stock is kind of like gambling in the sense that you're betting your money on a company's future performance. But how do you bet on a technology that could, in the worst-case scenario, "pose catastrophic or existential risks to humanity," or best case, "bring forth an age of miracles"? To some extent, […]

Sam Altman sympathizes with mathematicians, but says OpenAI’s math onslaught won’t stop

After months of bombarding mathematicians with a relentless stream of AI-generated results, OpenAI CEO Sam Altman says he sympathizes with researchers struggling to make sense of it all. But he has no intention of stopping - and hints there could be much more to come from the company's stockpile of discoveries. "I think, on net, […]

Maine’s data center revolt will decide who controls the Senate

Maine Sen. Susan Collins, a Republican, was midway through defending her record during the final debate of the midterms when an audience member cut her short. "I'm terrified," a man shouted. "AI data centers are destroying our climate. They are poisoning our water." Collins brushed off the outburst, tying the man to her Democratic challenger, […]

Making it easier for websites to express AI training preferences

OpenAI will honor a shared robots.txt signal to help website operators communicate their AI training preferences to participating providers.

Community safety report and new protections for teens

OpenAI is strengthening violence prevention in ChatGPT with expanded safeguards, earlier interventions, and a new commitment to public safety reporting.

Backdoor in Claude Code for VS Code extension on the Cursor Marketplace

https://cursor.com/blog/claude-code-extension-security-notic...

Fair use benefits everyone

OpenAI shares excerpts from court briefs by creators, academics, accessibility advocates, and legal experts, among others, on how fair use supports AI training and innovation.

Elucidating the Design Space of LM Data Attribution

Data attribution methods for Language Models (LMs) are typically evaluated using downstream tasks like fact retrieval. However, existing evaluations vary multiple dataset properties simultaneously, making it impossible to isolate exactly why an attribution algorithm fails. To diagnose these failures, we explore the design space of LLM data attribution, with a primary focus on evaluation. We introd

Propose-Filter-Release: Scaling Noise to Typical Sensitivity via Private Filtering

An estimator can be accurate and stable on typical data, yet sensitive to a few possible records. Differentially private mechanisms commonly scale their noise to the worst-case influence of a single record, which lets these records dictate the noise even when the remaining data would allow far less. Removing them first would restore the smaller scale, but the removal must itself be private. We int

Rethinking Neural Thickets Without Weight Perturbations

The Neural Thickets hypothesis posits that pretrained language models lie in dense neighborhoods of task-specific experts in weight space, which random Gaussian perturbations can uncover. We reproduce the reported gains, but show that they do not require this geometric explanation. Perturbing a single decoder block already recovers much of the improvement, while keeping the model entirely frozen a

Read, Allocate, Route: Role-Coupled Tokenization for Pixel-Space Generative Transformers

Pixel-space generative Transformers typically use one token per image patch, so capturing finer detail requires more tokens and makes global attention increasingly expensive. We observe that finer detail does not necessarily require more global communication: low-frequency structure benefits from global exchange, while high-frequency detail can be modeled locally. Based on this insight, we introdu

Adaptive Scenario Generation for KL-DRO Around a Learned Density Model

Distributionally robust optimization (DRO) hedges data-driven two-stage stochastic programs against error in the distribution estimated from a finite record, and standard ambiguity sets differ in how they treat realizations absent from that record. A divergence ball around the empirical distribution contains only reweightings of the record, whereas a transport ball also contains distributions supp

Luggage re-identification: A study of strategies towards a real-world application

Luggage re-identification (ReID) is a critical task in video surveillance for forensics, security or border management (suspicious or abandoned luggage recognition), as well as luggage management (lost luggage recovery). It enables the association of observations of the same luggage across disjoint camera views in complex environments such as airports, train stations and border crossing. While exi

From extreme weather to agricultural consequences with agentic AI

Extreme weather is forecast days ahead, yet its consequences for agriculture remain hard to predict: a forecast says where a storm will strike, not which crops will suffer or how much is at risk, and the records that could tell span many sources. We present WxCrop, the first agent that judges agricultural hazards from physically interpretable weather indices examined by causal analysis, and the fi

world2vec: Mechanistic world models through latent dynamics learning

World models can achieve strong control performance without faithfully capturing the dynamics of their environment, limiting their potential for mechanistic interpretability and scientific discovery. Here, we introduce world2vec to learn mechanistic world models without reward information directly from observations and actions. World2vec learns latent dynamics that faithfully reproduce the true sy

Probing Spatial State Representations in Visual Foundation Models

An observer sees only part of the surrounding world, yet must keep track of what lies beyond the current view. Spatial perception therefore involves more than recognizing individual images: it calls for a persistent spatial state that is updated under self-motion and used to guide action. Do visual foundation models provide representations that support such a state? We study this question through

ShallowDefend: Harnessing Shallow Safety Alignment for Multi-Turn Defender

Safety alignment has enabled large language models to reliably refuse harmful requests directly, yet the same request distributed across a multi-turn conversation still succeeds far too often. This brittleness has a mechanistic root: Alignment is shallow, with safety behavior concentrated in a model's first few output tokens, and existing defenses inherit the weakness, supervising the surface form

Testimony from Timelines: Evidence-Grounded Significance Testing of Temporal Clinical Hypotheses

Ask a language model whether sales tend to dip after a product recall, or whether one side effect tends to follow another after a vaccine, and it answers in a fluent sentence that reads like a finding, with no test behind it. Assertions about how events unfold across many cases fill the Web, and each is a temporal hypothesis that only a significance test over the right records can settle. The veri

An ODE-based Sampler for Discrete Diffusion Models

The marginals of a continuous diffusion model can be reproduced by a deterministic ordinary differential equation (ODE), known as the probability flow ODE, which provides a foundation for accelerated sampling and consistency distillation. In this paper we address the question whether an analogous formulation exists for discrete diffusion models and answer it affirmatively by introducing exponentia

Difficulty Calibration Across Time for Membership Inference in Diffusion Models

Modern diffusion models are trained on massive datasets that often include copyrighted or private images. Membership inference attacks (MIAs) address this by testing whether a given image was in a model's training set. The standard approach scores an image by its reconstruction loss and flags low-loss images as members. This often fails because some images are simply easier to reconstruct than oth

TextSeal2: Distortion-Free LLM Watermarking with Copula Mixing and Memoryless Races

We present TextSeal2, a distortion-free watermark for large language models that keeps its signal under speculative decoding: tokens that replace rejected drafts remain watermarked with the same keys, and the acceptance rate is unchanged. It also preserves output diversity and adds no measurable inference latency. Its predecessor, TextSeal, restores diversity in the Gumbel-max scheme by routing ea

When to Assist and What to Suggest: Joint Gating and Memory-Grounded Hint Generation in One Compact Decoder

Proactive assistants offer short, memory-grounded hints during a conversation, deciding when to assist and what to suggest. Current systems split this between a gate and a larger generator; we evaluate both together on 28,058 decision points. Stage-wise generation scores are oracle-gate ceilings: behind a real gate, end-to-end exact match is 0.2619 against a ceiling of 0.2971, and end-to-end preci

Collaborative AI agents for autonomous experimental research with solid-state quantum spins

An autonomous research laboratory could conduct an entire study, from formulating questions to preparing manuscripts. Artificial intelligence (AI) offers one route towards this goal. Recent AI systems take on several research roles, but may draw conclusions that the evidence does not support. Here, we present an autonomous research laboratory in which agents based on large language models assess o

Pre-Crime for Agents, at the Last Second: Probing When a Recruited Agent Gives In

When AI agents share channels and credentials, one agent can press another to break its operator's rule, a first step towards collusion. Output filters check only what an agent has already written. Can an overseer tell beforehand that an agent is about to give in? We show that a linear probe on the agent's activations can, in a controlled multi-agent setting. Across six scenarios, a peer presses a

Multistatic ISAC with Deep Learning-Based Clutter Suppression for 5G and Beyond

Integrated sensing and communications (ISAC) systems using 5G and beyond signals of opportunity enable joint wireless sensing and communication using shared infrastructure and spectrum resources. While multistatic ISAC can increase sensing coverage with spatially distributed receivers, dense and dynamic clutter can significantly degrade bistatic range and Doppler estimation, leading to errors in t

VeriCUA: Verification as Agentic Exploration for Computer-Using Agents

Building and scaling computer-using agents (CUAs) across desktop, mobile, and web environments requires reliable task-completion verification for data curation, evaluation, and reinforcement learning. Typical automated approaches prompt vision-language models (VLMs) to judge trajectories or generate programs to inspect application state. However, both rely on partial views of complex digital envir

Multi-View MoE: Letting Every Router Shape Expert Computation

Sparse mixture-of-experts (MoE) models expand parameter capacity by activating a small subset of experts per token. Expert selection directly affects model capabilities under a fixed active-expert budget. Dense evaluation of all experts reveals weak agreement between single-router rankings and expert-utility evaluation rankings, especially in middle and deep layers. Richer signals for selection an

PIVOT: Progressive Intervention via Online Teacher Correction

Reinforcement learning from verifiable rewards (RLVR) is limited by sparse outcome-level feedback on hard reasoning tasks: when all rollouts in a group fail, rewards provide no learning signal. Stronger teachers can provide additional guidance, but this raises a central question: how can such signals be incorporated into RLVR to support successful rollouts while remaining learnable for the student

Every Token Needs Its Own Teacher: Multi-teacher Adaptive On-policy Self-distillation

On-policy Self-distillation (OPSD) has proven effective for post-training large language models by constructing a teacher conditioned on privileged references. However, existing approaches keep the teacher fixed either throughout training by consistently exposing it to the full reference, or within each response by adaptively varying partial reference exposure only across responses. In this paper,

Gym-Anything for Robotics: Scaling physical simulations with digital agents

Realistic, fast robotics simulations could enable large-scale training of embodied AI models that transfer to the real world. However, despite decades of progress, available simulations cover only a narrow range of real-world tasks and physical phenomena. The core bottleneck is that creating better simulations requires significant expert effort and therefore does not scale. To address this, we int

Training Foundation Models with a Single Algorithm

Foundation models are typically trained in stages: pretraining, midtraining, supervised fine-tuning (SFT), and reinforcement learning (RL), with changes in both data and learning algorithms. We show that this algorithmic separation is not fundamental. By deriving suitable RL objectives as maximum-likelihood fitting to model-generated target distributions, we place all of these stages under a singl

Comparing Human Role-Players and LLM-Simulated Clients in Online Counselling Training: An Analysis of Counselling Patterns

This study investigates the capabilities of Large Language Models to simulate counselling clients in educational role-plays in comparison to human role-players. Initially, we recorded role-playing sessions, where novice counsellors interacted with human peers acting as clients, followed by role-plays between humans and clients simulated by Mistrals Mixtral 8x7b using 4-bit quantization. These inte