AI Hub
The information repository
Curated picks alongside live news from The Guardian and NewsAPI, and research papers selected from Semantic Scholar and ArXiv. News updates every 24 hours. Papers are curated and reviewed before publishing.
Curated
Editor's Picks
Anthropic Expected to Tell Investors It Sees Over $30 Trillion in Potential Revenue
Anthropic is likely to tell investors its potential revenue opportunities are above $30 trillion, topping SpaceX’s $28.5 trillion estimate, according to people familiar with the matter.
Australia bans AI-generated music from its official charts
Australia has banned largely or wholly AI-generated songs from its official music charts.
Harvard $699 startup bootcamp has professors who never sleep but that's because they're AI clones
The school is now putting AI versions of its faculty to work in a $699 online startup bootcamp, where aspiring founders can rehearse investor pitches, sales calls, and board meetings—all with AI clones of Harvard instructors. They can even test their pitches with an AI avatar repeatedly before a real meeting.
The decades-old AI alignment problem has finally become a reality. Solving it won't be easy
As AI systems become more autonomous, they are coming to resemble wish-granting genies: finding routes and using methods we did not imagine from incomplete instructions.
Young Americans Don't Trust Billionaire AI Leaders, New Poll Finds
Younger Americans hold more negative views than positive views of AI and a mostly pessimistic outlook on the economy, a new poll published on Thursday conducted by CNBC and Generation Labs found, which also found a majority distrust the billionaire leaders of AI companies like Elon Musk, Sam Altman and Mark Zuckerberg.
Mark Zuckerberg's Pivot to AI Is Blowing Up in His Face Spectacularly
Despite having almost nothing to show from his enormous spending on AI, Meta CEO Mark Zuckerberg is doubling down.
The Economy Has Spoken: Stuff That's AI-Generated Has Almost Zero Value
Online marketplaces are being flooded with AI slop — but is anybody willing to actually pay for it?
Experts Warn That AI Slop Is Corrupting Kids Brains
What do you get when you let an endless feed of AI fruitslop videos loose on screen-addicted kids? A great recipe for violent extremism, it turns out.
Live — refreshed every 24 hours
AI News
Bill Gates Wants a Robot Tax and Jobs Humans Can't Be Fired From
Gates is calling for AI tokens and robots to be taxed so firms think twice before swapping out workers, plus a bracket of "human reserved" roles that stay off-limits to automation.
Bill Gates warns AI is outpacing governments and could shrink the workforce
Gates' call for AI regulation and a "token tax" highlights the urgent need for global oversight to mitigate AI's socio-economic disruptions. The post Bill Gates warns AI is outpacing governments and could shrink the workforce appeared first on Crypto Briefing.
Bill Gates warns tech companies are downplaying AI risks
Gates' warning highlights the urgent need for regulatory frameworks to address AI's societal impacts, including job displacement and security risks. The post Bill Gates warns tech companies are downplaying AI risks appeared first on Crypto Briefing.
Understanding the Impact of AI on Job Markets
Explore five distinct ways AI is reshaping jobs, from automating routine tasks to thinning entry-level hiring.
'Token tax' on AI: Why Bill Gates flags job losses, suggests 'human-reserved' jobs
Bill Gates argued that the enormous amount of money being invested in AI may be discouraging industry leaders from openly discussing its potential dangers.
Bill Gates’s new essay on the AI future he fears
Bill Gates says governments are unprepared for an AI transition that could eliminate large numbers of entry- and mid-level jobs within a decade. He is calling for new national and international institutions, protected human-only roles, and taxes on AI and rob…
FTC Chief Rebukes Silicon Valley Investor for Sneering at Americans
A Silicon Valley investor sneered at American citizens on Wednesday, prompting quick pushback from teh chairman of President Trump's Federal Trade Commission and the investor's politically minded boss. The post FTC Chief Rebukes Silicon Valley Investor for Sn…
'This is crazy. This is insane': Bill Gates has changed his mind about AI and jobs
The Microsoft founder says human-only jobs and token taxes will be required at “a unique moment in evolutionary history.”
Workers in China Worry Over Being Replaced by AI
Source: PBS News Hour Computer programmer Fei Zhaojun's boss asked him if artificial intelligence could soon replace humans in coding jobs. Two weeks later, he was laid off from his job in Beijing, together with about 160 colleagues. It's an increasingly com…
Goldman Sachs Safeguards Apprenticeship Culture in AI Era
Goldman Sachs aims to ensure that new artificial intelligence tools don’t lead to a loss of knowledge within the institution, Chris Churchman, head of the company’s digital platform for institutional clients, Marquee, said, CNBC reported Monday (Aug. 24). Spe…
His boss asked if AI could replace human coders. Two weeks later, he and 160 colleagues were laid off in Beijing
China is rapidly adopting AI and robotics, leaving workers worried about layoffs and economists warning of broader risks to employment.
AI is ‘likely’ behind some slowdown in youth employment in Ireland
A report says it is still “too early to be definitive” about AI-related job losses more broadly, as Ireland has emerged as a major hub for AI jobs and talent.
Curated — selected via review
Research Papers & Studies
VBVR-Pro: A Scalable and Verifiable Suite for Native Visual Reasoning
Native visual reasoning treats visual generation as the medium of reasoning itself: visual states (i.e. images and videos) are not merely inputs to be understood or outputs to be rendered, but first-class substrates for problem solving beyond language. Yet progress remains bottlenecked by the lack of scalable training tasks, reliable feedback, and controlled comparisons across generative substrate
A Visual Dependence-Aware Framework for Multimodal Unsupervised Continual Post-Training
In this paper, we explore a novel task of Multimodal Unsupervised Continual Post-Training (MU-CPT), enabling deployed MLLMs to continually evolve from streaming unlabeled data. Existing unsupervised post-training methods for MLLMs typically optimize target tokens uniformly, overlooking their heterogeneous visual dependence (VD). However, we reveal that token-level VD is crucial for MU-CPT. Specifi
MyoMechanix: Biomechanically-Grounded Compositional Skilled Activity Understanding and Coaching
Existing action quality assessment (AQA) datasets and methods rely primarily on visual inputs such as RGB and pose, overlooking physiological dynamics such as muscle mechanics and often modeling actions as monolithic patterns. These limitations hinder fine-grained, biomechanically grounded feedback. We introduce MyoMechanix, a multimodal ecosystem for weight-loaded actions that aligns motion with
Planetary Prediction Engine: Autonomous Geospatial Prediction via Intelligent Data Selection and Foundation Model Embeddings
Addressing critical global challenges, from food security and disaster risk to disease outbreaks and socio-economic vulnerability, demands high-fidelity geospatial modeling. However, building predictive planetary models remains bottlenecked by a fragmented data ecosystem, requiring manual data retrieval, multimodal data curation and fusion along with iterative model selection. We present the Plane
TraceML: An Empirical Analysis of Human-Agent Planning in Machine Learning Development
Large language models write correct code for isolated problems but remain far weaker at autonomous machine-learning development, where an agent must revise data pipelines, models, and validation over hours of feedback, and on most competitions still finishes below strong human competitors. Outcome-based benchmarks record this gap but not its cause, because they grade the final submission and disca
ICON Decomposition: Multivariate Concept-Level Explanations of Deep Representations for Model Auditing
Deep neural networks often exploit spurious associations in their training data, a failure known as shortcut learning. Concept-based explainability methods screen for shortcuts by testing whether concepts such as a patient's sex or scanner settings can be decoded from a network layer. Because each concept is evaluated in isolation, these methods can mistake correlations between concepts as evidenc
SwarmWorld: Stigmergic technological evolution in societies of language-model agents
Collective intelligence can emerge when individuals coordinate through a shared environment, allowing local actions to accumulate into durable social organization. Language-model agents offer a new substrate for this process, yet most multi-agent systems rely on direct conversation, predefined roles, or centralized workflows. It remains unclear whether decentralized agents can build functional tec
The Reverse Big Push: Generative AI and Self-Fulfilling Automation
Generative AI relocates the fixed cost of automation. A model provider pays to train a frontier system, while a downstream firm rents capability by usage; the same firm must carry a continuing payroll to supply a human-augmented service. We study this asymmetry in a local service economy with household budgets and a market-clearing wage. Human augmentation earns a larger surplus from an additional
Who Delegates to AI? Evidence from 53,000 Agent Configurations
A growing literature measures how far occupations are exposed to AI, but these measures capture where AI could perform tasks, not whether workers have adopted it. We propose a new layer of exposure, delegated exposure, which records whether a worker has committed a task to AI by building it into a workflow. We operationalize it as the Agentic Adoption Index (AAI), which measures how closely an occ
Adoption of Generative AI in the Workplace: Increasing and Shifting the Balance of Productivity and Communication Activity
Generative AI is transforming the workplace by augmenting and automating cognitive tasks, reshaping how organizations work and innovate while raising questions about workplace inequality and the future of work. Despite rapid adoption, empirical evidence on how these tools alter work practices and generate productivity gains remains limited. We examine how AI use affects the quantity and nature of
MECA: A Mechanism-Centered Agent for Constructing Well-Specified and Valuable Mathematical Conjectures
Automatically constructing well-specified and valuable mathematical conjectures remains a central challenge in AI-assisted mathematical discovery. Many existing open problems and conjectures are often too broad, underspecified, or difficult to connect to plausible proof or refutation strategies. We view a mathematical mechanism as a structure or reasoning principle that connects the assumptions of
Cheaper AI, More Informality? A Dual Labor Market Model for Developing Economies
This paper studies what happens when AI gets cheaper, with emphasis on the labor market outcomes, whether it creates formal jobs or whether it pushes workers into informality. We argue that the answer depends on the elasticity of substitution between imported AI capital and formal labor. We build a small open economy DSGE model with a dual labor market, imported AI capital, and country risk, calib
Evaluating AI Models' Capability to Automate Voice Phishing Attacks
Voice phishing (vishing) attacks have traditionally been limited by the need for human operators. The rapid emergence of high-quality AI voice synthesis and large language models (LLMs) reduces this bottleneck and enables scalable, automated scams. In this paper, we conduct a large-scale survey experiment (N=4100) and qualitative interviews (N=12) to assess U.S. adults' susceptibility to AI-powere
The Economic Benefits and Costs of AI and Policies to Mitigate AI's Impact on Inequality
We examine the economic impact of increasingly productive AI and policies that spread its benefits across the economy. Improvements in AI productivity trigger labor reallocation and changes in absolute and relative wages for different types of labor. Wages of labor that is essential for building AI increase faster than overall GDP. Wages of labor that is substituted for by AI decrease in both abso
PlanSightRAG: A Visual-First Multimodal RAG for Automating Question Answering and Compliance Checking for Civil Standard Plans
Civil infrastructure compliance checking has long relied on engineers manually reading legacy 2D plans; however, OCR-based automation strips away the geometry and layout essential for interpreting these plans. We present a Visual-First Multimodal Retrieval-Augmented Generation (RAG) framework called PlanSightRAG. It indexes and reasons directly over plan imagery, integrates a ColNomic-3B multi-vec
How AI Impacts Skill Formation
AI-assistance produces significant productivity gains across professional domains, particularly for novice workers. Yet how this assistance affects the development of skills required to effectively supervise AI remains unclear.
Perspective
Opinions & Analysis
Opinion pieces and analysis, clearly labeled as perspective, not reported fact.