Thu 2 July 2026
Daily Brief — Curated and contextualised by Best Practice AI
Economists Sound Alarms, Abu Dhabi Banks Billions, and SaaS Spending Evaporates
TL;DRTop economists are warning of systemic fallout if the current AI investment boom collapses. Abu Dhabi’s MGX has raised $49 billion for AI deals, while OpenAI is reportedly discussing a 5% equity stake with the US government. US employment data shows payroll declines in financial services and IT, coinciding with a historic post-war low in the national labor share of income. Gartner projects that agentic AI will cannibalize 20% of enterprise SaaS spending by 2030.
The stories that matter most
Selected and contextualised by the Best Practice AI team
MGX Raises $49 Billion for AI Deals
MGX has raised $49 billion for one of the biggest ever funds dedicated to artificial intelligence deals, propelling the two-year-old Abu Dhabi firm into the ranks of the most consequential investors in the sector globally. (Source: Bloomberg)
Meta Is Planning a Cloud Business to Sell AI Computing Power - Bloomberg
Meta Platforms Inc. is developing plans for a cloud infrastructure business that will sell access to AI computing power and models, setting up a new vector of competition with industry leaders like Amazon Web Services, Microsoft Azure and Google Cloud.
AI Effect Showing Up in US Employment Numbers | PYMNTS.com
The impact of AI has reportedly begun to show up in U.S. government employment data. A drop in financial services and IT payrolls — two sectors where
Gartner warns agentic AI threatens $234bn SaaS spend
Enterprise buyers could shift billions from seat licences as agentic AI is set to undercut up to 20% of SaaS spending by 2030.
Mnemosyne: Agentic Transaction Processing for Validating and Repairing AI-generated Workflows
arXiv:2607.00269v1 Announce Type: new Abstract: LLMs, solvers, and agent teams increasingly generate workflow actions, repairs, and plans, but a generated action may be syntactically valid yet stale, infeasible, conflicting, or destructive of the evidence that triggered a repair. We introduce Agentic Transaction Processing (ATP), a transaction model that treats generated actions as untrusted proposals until they pass deterministic admission under a declared, executable constraint set C. The principle is two-sided: a proposal is not truth, and no proposal foresees every disruption: anything may propose, but only the runtime admits and commits, and when an unforeseen disruption strikes it repairs reactively within bounds rather than trusting a fresh proposal. Relative to C, committed-state correctness becomes independent of the competence, honesty, or learning of the proposing layer. We realize ATP in Mnemosyne, a runtime with an append-only transition log, effective-state projection, dependency-safe compensation, and active commitment records, and prove four safety properties relative to C (authority separation, serial-equivalent generative admission, evidence-preserving repair, and obligation containment) together with a bounded-reactive-repair guarantee for its localized repair protocol (LCRP). A reproducible artifact rejects the targeted violations across nine falsification tests while still admitting valid work, at under 6% projection-and-validation overhead, and bounded local repair edits an order of magnitude fewer operations than global recompute. Mnemosyne is open source: https://github.com/eyuchang/Mnemosyne/tree/arxiv-atp-rq1-rq9b-r8-v2.
Battery start-ups see ‘crazy’ demand to smooth power surges in data centres
Rapid growth of clusters of processors for AI training drives need for energy storage
What's a Credit Worth? A Market Framework for Attribution-Aware Compensation in Generative Music
arXiv:2607.00641v1 Announce Type: new Abstract: Advances in generative AI are rapidly increasing the quality and commercial value of generated music, and this progress depends on large catalogs of creators' recordings. This raises a central question for platform design: how should creators be compensated when their work is used to train generative AI models that in turn produce commercial outputs? We develop a framework for fairly compensating creators in generative-music markets, where each creator's payment depends on a data-attribution score estimating their contribution to model outputs. Compared to past compensation frameworks, our framework has two unique considerations: (1) attribution is traced to entire creator catalogs, not individual songs, and (2) the informativeness (signal-to-noise ratio) of the attribution score is an input to the payment mechanism. The framework yields a closed-form payment rule per creator and measures the welfare cost of inaccurate attribution for both creators and the platform. Whether the welfare-optimal contract is royalty-based or takes the form of fixed-fee licensing depends on how informative attribution is for that creator's catalog. We show that better attribution translates directly into welfare gains for both creators and the platform, yet under multi-platform competition a platform only captures gains from attribution improvements when its signal becomes the most precise in the market. To ground our framework in empirical behavior, we train acoustic and symbolic music generation models and measure the informativeness of scalable attribution techniques against a leave-one-catalog-out ground truth. Our experiments reveal that noisy attribution signals push payment toward fixed-fee licensing and diminish welfare for both creators and the platform, providing an economic motivation for further research on improved attribution.
The labor share of income in the US is at its lowest post-war level
New economic analysis indicates that the labor share of income in the United States has reached a historic post-war low.
Economics & Markets
SAP Restricts Hiring, Travel to Fund ‘Significant’ AI Push
SAP SE said it will cut back hiring and travel to save costs as Europe’s largest software company devotes more resources to developing artificial intelligence technologies and fending off new competitors.
What's a Credit Worth? A Market Framework for Attribution-Aware Compensation in Generative Music
arXiv:2607.00641v1 Announce Type: new Abstract: Advances in generative AI are rapidly increasing the quality and commercial value of generated music, and this progress depends on large catalogs of creators' recordings. This raises a central question for platform design: how should creators be compensated when their work is used to train generative AI models that in turn produce commercial outputs? We develop a framework for fairly compensating creators in generative-music markets, where each creator's payment depends on a data-attribution score estimating their contribution to model outputs. Compared to past compensation frameworks, our framework has two unique considerations: (1) attribution is traced to entire creator catalogs, not individual songs, and (2) the informativeness (signal-to-noise ratio) of the attribution score is an input to the payment mechanism. The framework yields a closed-form payment rule per creator and measures the welfare cost of inaccurate attribution for both creators and the platform. Whether the welfare-optimal contract is royalty-based or takes the form of fixed-fee licensing depends on how informative attribution is for that creator's catalog. We show that better attribution translates directly into welfare gains for both creators and the platform, yet under multi-platform competition a platform only captures gains from attribution improvements when its signal becomes the most precise in the market. To ground our framework in empirical behavior, we train acoustic and symbolic music generation models and measure the informativeness of scalable attribution techniques against a leave-one-catalog-out ground truth. Our experiments reveal that noisy attribution signals push payment toward fixed-fee licensing and diminish welfare for both creators and the platform, providing an economic motivation for further research on improved attribution.
Meta building cloud business to sell excess AI capacity, Bloomberg News reports
Find latest business news from every corner of the globe at Reuters.com, your online source for breaking international news coverage.
AI search could kill the web without new quality signals and revenue models
Penance payments to websites for failing to forward traffic aren't enough
Where China’s AI models make their money - Bamboo Works - China stock insights for global investors
Unlike overseas rivals that rely on subscriptions and APIs, Chinese AI vendors are monetizing through cloud platforms, project contracts and compute usage
Council Post: AI Will Not Monetize Itself, Your Entitlement Model Will Decide What Revenue You Capture
The team widened the package, framed the exception as strategic and closed the deal. · A few quarters later, no one was celebrating. Similar customers expected the same treatment. The field had started selling around the structure rather than through it. A decision that helped one quarter was making the business harder to defend in every quarter after it. · That is how AI monetization ...
Every startup wants to be cited by AI, but here's where the real opportunity lies - Startup Daily
Looking for AI gold? Head to where the crowd isn’t searching and try to close the gaps, explains Nick Brogden.
MGX Raises $49 Billion for AI Deals
MGX has raised $49 billion for one of the biggest ever funds dedicated to artificial intelligence deals, propelling the two-year-old Abu Dhabi firm into the ranks of the most consequential investors in the sector globally. (Source: Bloomberg)
Kospi Falls as Chip Selloff Spreads
Stocks fell as a selloff in chip stocks spread to South Korea, reviving concerns the rally in artificial intelligence shares may have gone too far. Bloomberg's Anthony Stephens reports. (Source: Bloomberg)
Korea Chip Selloff Leads Equities Lower
Stocks fell as a selloff in chip stocks spread to South Korea, reviving concerns the rally in artificial intelligence shares may have gone too far, too fast. Bloomberg's Avril Hong reports. (Source: Bloomberg)
Meta pops 9% as company makes cloud push to sell excess AI compute power capacity
The new business is a welcome signal for some investors who have been uneasy about the company's infrastructure spending plans.
Oaktree-backed ITG jumps in Nasdaq debut, signaling strong AI infrastructure demand
SpaceX's bankers are preparing to meet investors as early as next week to discuss a bond offering of at least $20 billion, two sources familiar with the matter said on Thursday, as Elon Musk's newly public company seeks funding for an ambitious and capital-intensive AI expansion.
Oracle outlines all the ways it could lose the farm it bet on AI
Risk factors galore
Lombard Odier Urges Tech Exposure 'At the Market Weight'
Lombard Odier's EMEA CIO Nannette Hechler-Fayd'Herbe discusses the outlook for tech stocks, volatility and where she sees opportunities beyond artificial intelligence and semiconductors. She speaks on Bloomberg Television. (Source: Bloomberg)
Musk denies WSJ report that SpaceX showed AI handset prototype before IPO
SpaceX's bankers are preparing to meet investors as early as next week to discuss a bond offering of at least $20 billion, two sources familiar with the matter said on Thursday, as Elon Musk's newly public company seeks funding for an ambitious and capital-intensive AI expansion.
Amazon launches $1 billion AI-driven FDE initiative, following Anthropic and OpenAI
Amazon launches a $1 billion AI-driven FDE initiative to accelerate enterprise AI adoption with embedded engineers and autonomous AI agents.
Semiconductor stocks just had their best quarter ever
It's another sign that the AI build-out is likely the biggest investment boom in American history.
AI Data Center Chip Revenue to Surpass $1.2 Trillion by 2028
AI is creating unprecedented demand for chips—but the biggest opportunity is only beginning.
Together AI raises 800 million dollars in Series C led by Aramco Ventures
Aramco Ventures leading the round signals growing Middle Eastern interest in the infrastructure underpinning artificial intelligence, rather than just the models themselves. The question for Together AI is whether its open-source positioning and software edge can hold as the hyperscalers, flush with hundreds of billions in capital spending, build out their own inference capabilities at a scale no startup ...
Ruya Ventures goes deep with €43 million fund to get lab-born tech into the real world
London’s Ruya Ventures, a solo GP venture capital firm founded by DeepTech investor Rick Hao, has announced a €43 million ($50 million) fundraise for its first VC fund, aimed at supporting global DeepTech innovation as it moves from the lab into real-world deployment. The fund reached its final close in less than a year and […]
Investors Shift to Alts, Other Active Strategies to Calm Concentration Worries | Chief Investment Officer
Morningstar’s CIO for the Americas cites emerging markets and early artificial intelligence ‘losers’ as potential smart plays.
Why are IT stocks rising today? Infosys, HCLTech, TCS jump up to 5%; Nifty IT snaps 4-day losing streak - India Today
Adding to the concerns, reports ... competition. As semiconductor stocks corrected sharply after months of rallying on AI optimism, investors started shifting money into software services companies, including Indian IT firms, which are viewed as beneficiaries of AI adoption rather than manufacturers of AI hardware...
Physical AI Market Set to Surpass $430 Billion by 2030, Driven by Nine Key Vertical Sectors
The Physical AI market is expanding into nine key sectors: industrial automation, autonomous vehicles, robots, smart infrastructure, healthcare, agritech,...
Stock Market Live July 1, 2026: S&P 500 (SPY) Lower as Investors Wait on the Fed and Fresh Economic Data - 24/7 Wall St.
Live Updates Evercore ISI Reiterates Outperform Rating on Nvidia 13 hours ago Analysts at Evercore ISI just reiterated an outperform rating on Nvidia (NASDAQ: NVDA), saying the tech giant is the best idea, as noted by CNBC. “We believe that the Tectonic Shift to the current Parallel Processing ...
Meta Is Planning a Cloud Business to Sell AI Computing Power - Bloomberg
Meta Platforms Inc. is developing plans for a cloud infrastructure business that will sell access to AI computing power and models, setting up a new vector of competition with industry leaders like Amazon Web Services, Microsoft Azure and Google Cloud.
Schneider Electric buys industrial AI company Cognite for $3.1bn
Upon completion of the deal, the French energy services giant will combine Cognite with its own industrial software business, Aveva. Read more: Schneider Electric buys industrial AI company Cognite for $3.1bn
Amazon doubles down on enterprise AI bet - TheStreet
The model has shown up at software firms of all sizes looking to drive faster adoption of their tools, and the race to deploy enterprise AI has made it the dominant go-to-market strategy of the moment. The FDE idea has existed in tech for years but it is having a particular moment in 2026 because ...
Meta Is Building a Cloud Business to Sell Excess AI Compute - Articles - Advisor Perspectives
Meta Platforms Inc. is developing plans for a cloud infrastructure business that will sell access to AI computing power and models, setting up a new vector of competition with industry leaders like Amazon Web Services, Microsoft Azure and Google Cloud.
Gartner warns agentic AI threatens $234bn SaaS spend
Enterprise buyers could shift billions from seat licences as agentic AI is set to undercut up to 20% of SaaS spending by 2030.
SpaceX-Anysphere deal to be reviewed by Australia antitrust regulator
The Australian Competition & Consumer Commission will review SpaceX's proposed acquisition of Anysphere. The regulator is seeking feedback on the transaction until July 8.
Anthropic eyes biology after winning at code
Anthropic has debuted Claude Science, a workbench for scientists, as the company positions biology as the next major proving ground for AI development.
Understanding Guest Preferences and Optimizing Two-sided Marketplaces: Airbnb as an Example
arXiv:2607.00280v1 Announce Type: cross Abstract: Airbnb is a community based on connection and belonging -- many hosts on Airbnb are everyday people who share their worlds to provide guests with the feeling of connection and being at home; Airbnb strives to connect people and places. Among our efforts to connect guests and hosts, we provide tools to enable hosts to set competitive prices, which helps improve affordability for guests while helping hosts get more bookings. We also personalize the guest experience to show them the listings that match their needs. To help inform these efforts, we combine economic modeling and causal inference techniques to understand how guests book stays based on the prices hosts set, among other factors, and how that preference varies across different guests and listings. Such understanding helps us identify opportunities for Airbnb to support the marketplace and better connect guests and hosts. For example, understanding how much guests respond to different prices helps optimize the tools that we provide to hosts, in order to enable hosts to choose and set competitive prices that further balance demand and supply. As another example, understanding heterogeneity in guest preferences helps us personalize the guest experience and better match them with the listings that meet their needs, based on how much they respond to different prices and other factors.
Apple has put a price on the AI boom - The Hindu
Apple products occupy the premium end of tech gadgets. But last week’s increase in the prices of select MacBook and iPad models are worth paying attention to.
As Companies Race for Cheaper A.I. Options, This Start-Up Pitches a Solution - The New York Times
Together AI, which specializes in open-source artificial intelligence models, is now worth more than $8 billion.
Together AI raises $800M at $8.3B valuation as enterprises ditch closed models for open-source — TFN
Together AI raised $800 million at an $8.3 billion valuation, with Aramco Ventures leading the round.
CarbonSix Secures $40M Series A to Deploy Physical AI Across Global Manufacturing
/PRNewswire/ -- CarbonSix,Inc., a pioneer in Physical AI for the manufacturing sector, announced today that it has raised $40 million (approx. KRW 60 billion)...
1001 Banks Invest $30 Million to Deploy Predictive AI in GCC Ports, Energy, and Aviation
GCC- and London-based sovereign AI startup 1001 has successfully raised $30 million in a Series A funding round led by the US venture capital firm Lux Capital. The round also saw participation from prominent investors including PIF-backed Sanabil Investments, Hanabi, 9Yards, General Catalyst, ...
AI chip race opens new opportunities for Indian semiconductor startups - CNBC TV18
Lam Capital President Audrey Charles says India's deep-tech and semiconductor startups are gaining global attention as artificial intelligence drives fresh investment and innovation in advanced chip technologies.
Quantum Systems weighs merger with kamikaze drone start-up Stark
German maker of unmanned surveillance aircraft says $1.2bn fundraising removed shareholder opposition to developing lethal weapons
Labor, Society & Culture
Can Companies Embrace A.I. Without Layoffs? This One Says It Is Trying to. - The New York Times
The German software giant SAP says it is betting that employees can reinvent jobs instead of eliminating them. Experts are divided on whether it will work.
AI is helping workers sue their bosses. It may be breaking the system
A flood of employment claims has left an overloaded tribunal system struggling to cope
CEO of $248 billion cybersecurity company says workers are about to face a ‘Darwinian moment’ thanks to AI: Evolve or get cut | Fortune
Palo Alto Networks CEO Nikesh Arora warns that 90% of employees aren’t AI savvy—and it could determine the fate of their careers.
A Penny for Your Prompts: Experiments Detecting and Mitigating LLM Usage by Survey Respondents
arXiv:2607.00403v1 Announce Type: cross Abstract: Large language models are increasingly used by participants on crowdsourcing platforms when responding to surveys, potentially undermining the validity of collected data. Our study aims to quantify the prevalence of this behavior and investigate methods to detect and prevent it. In a series of surveys (N = 250), we examined conditions such as platform choice, survey length, requests not to use AI, and disabling copy-paste functionality. We were able to identify distinct characteristics of LLM-assisted responses and found that their frequency varied widely, from under 10% on Prolific to over 80% on Mechanical Turk. Mitigation measures reduced LLM usage but did not necessarily improve data quality. No participants employed browser-use agents at the time of our survey, but we report on our own detection experiments. We recommend that researchers actively screen survey responses for LLM usage by recording and analyzing keystroke data and crafting instructions and questions aimed at AI.
WEF: Protect Entry-Level Jobs Amid AI Adoption
WEF report warns cutting entry-level hiring amid AI could weaken talent pipelines. Urges companies to redesign, not eliminate, early career roles.
Tech and Finance Sectors Losing 28,000 Jobs Monthly Show AI Impact on Labor
Whether artificial intelligence will cause mass workforce cuts over time remains up for debate, but it is starting to leave an imprint on US employment
What AI hiring trends mean for your job prospects
A majority of Americans fear AI could cost them or a household member their job, but new research finds firms that heavily invested in AI hired more.
AI Effect Showing Up in US Employment Numbers | PYMNTS.com
The impact of AI has reportedly begun to show up in U.S. government employment data. A drop in financial services and IT payrolls — two sectors where
Tech, finance sectors in US losing 28,000 jobs monthly show AI impact on labour | The Straits Times
A decline in payrolls in the financial-activities and information sectors has accelerated in 2026. Read more at straitstimes.com.
AI Dispatch: Daily Trends and Innovations – July 1, 2026 | Anthropic Claude Science, AWS Forward-Deployed Engineers, California AI Workforce Study, Kenshiki Labs Pulse, Ant International GDC
AWS is investing heavily in ... that enterprise AI adoption will require human experts embedded directly with customers. California’s new AI workforce study suggests the employment shock is not limited to junior workers or low-skill roles; highly educated workers in high-AI-exposure jobs are also feeling pressure. Kenshiki Labs is taking aim at AI-driven synthetic identity fraud with a public red-team challenge...
Council Post: The Non-Technical Blueprint For Agentic AI: Navigating History, Risk And Human Capital
Just like the automated grain mills or the assembly lines of past industrial revolutions, agentic AI will drive massive efficiency gains that inevitably culminate in structural labor displacement—particularly within mid-career operational and IT management roles. Responsible leadership means proactively preparing the enterprise workforce for this imminent organizational down-sizing and structural workplace ...
Can AI Promote Job Creation? - Shepherd Express
In customer‑service, AI now handles the first layer of customer inquiries (password resets, order status, basic troubleshooting). Productivity rises for non‑routine tasks because workers spend more time on complex problem-solving designed to retain customers. The impact of AI on workers depends on the skills they bring to the job...
India's AI Talent Gap Is Real, Growing, and a Business Crisis in the Making - The Times of India
In 2024, India had approximately 420,000 AI professionals. The immediate industry requirement was 600,000, representing a talent shortfall of close to 50 per cent.
One of America's oldest manufacturers says AI is creating jobs — not replacing them
As demand for artificial intelligence ... manufacturer is ramping up production of optical fiber, the backbone of the high-speed networks powering AI. The company is also partnering with NVIDIA, the chipmaker at the center of the AI boom, to create 3,000 jobs in two states. NVIDIA CEO JENSEN HUANG SAYS AI WILL RESHAPE WORK LIKE THE INDUSTRIAL REVOLUTION AND THE ...
Pay Beliefs and the Amenity-Pay Tradeoff
arXiv:2606.02503v3 Announce Type: replace Abstract: This paper studies how workers' beliefs about pay shape the tradeoffs between pay and workplace amenities. We design a multi-stage incentivized survey experiment that combines hypothetical choice experiments with elicited beliefs about starting salaries in real jobs and randomly varies the provision of explicit pay information. Although stated preferences imply sizable willingness to pay for workplace amenities, baseline beliefs about salaries in real jobs are systematically biased along two margins: respondents under-predict starting salaries by 18% and expect higher-amenity jobs to pay more, substantially over-predicting the amenity-pay gradient. A short-term pay information intervention raises mean beliefs about pay in similar jobs by 4% and reduces belief dispersion by 15%, but does not alter the perceived amenity-pay slope or the implied tradeoffs in stated choices. Meanwhile, full disclosure of pay for jobs under consideration raises the pay of chosen jobs by about 4% and recovers willingness-to-pay estimates closely aligned with full-information hypothetical-choice benchmarks. Short-term disclosure thus moves beliefs but not perceived tradeoffs, while persistent disclosure erases biases in pay beliefs and nearly restores the full-information tradeoffs.
In the Age of AI, Manufacturers Won’t Need Engineers. Or Will They? | Products Finishing
Literally two days later, a headline ... Dreaded AI Jobs Wipeout Got Real.” I was clairvoyant by two days! Indeed, the world of work is being transformed before our very eyes. What does this mean for those employed in manufacturing — particularly the manufacturing engineers, industrial engineers, materials engineers, electrical engineers and those in similar ...
Dragon Age Co-Creator Warns AI Risks Stalling Game Developer Growth
David Gaider, co-creator of Dragon Age, warns that generative AI in gaming could stifle junior developers' growth and lead to lower-quality products.
Solid hiring, high inflation and AI fears collide as the June jobs report nears | AP News
Thursday’s report from the Labor Department on June job changes will provide some important clues on the health of the U.S. economy.
As AI threatens entry-level roles, here’s 10 high-paying jobs that are hardest to replace | Technology News - The Indian Express
A new study reveals the top 10 future-proof professions that are easy to enter and pay well amid AI disruption.
The Limits of LLM Forecasting: Parametric Knowledge Gaps Across Conflict Zones
arXiv:2607.00018v1 Announce Type: new Abstract: Media coverage of armed conflict is deeply asymmetric: we document a 224$\times$ gap between the most and least covered conflict zones in English-language media across 22 countries (2020--2026). We evaluate zero-shot conflict escalation forecasting across all 22 countries on a 660-case held-out test set, comparing Llama-3.3-70B and GPT-4o against three structured baselines. The central finding is not a performance gradient but a qualitative failure: LLMs do not forecast conflict -- they categorize it. Llama predicts escalation on every under-covered case, matching the trivial Always-YES baseline to three decimals; GPT-4o predicts NO on every over-covered case, missing all five actual escalation events. A logistic regression using only eleven observation-window features with \emph{no country information} achieves F1~=~0.402, outperforming both LLMs in every measurable tier. This failure cannot be resolved at inference time: adding structured ACLED evidence degrades performance on under-covered zones (GPT-4o F1: 0.323~$\to$~0.168) and falls below LR by a factor of 2.4. The bottleneck is not data availability but the LLM's interpretation of temporal signal under a country-categorical prior. Under-covered populations receive not just less accurate AI, but qualitatively different AI that cannot distinguish stable from escalating periods. We call for coverage-stratified benchmarking, conflict NLP datasets for under-covered zones, and training data documentation standards for geographic conflict representation.
LLMs in the Real World: Evaluating "AI" in Emergency Contexts
arXiv:2607.00019v1 Announce Type: new Abstract: This paper offers a call to action. We urge our colleagues in the research community to play a greater role in the articulation of our findings to the public. To illustrate the stakes we present a case study on the initial stages of an LLM-based machine translation application's deployment in a real-world context: a text-2-911 system advertising capabilities in 55 languages for use in emergencies in which it may be difficult to call operators directly. We identify a number of common misconceptions about technologies such as these, concluding with a set of concrete recommendations and best practices for stakeholders at every stage of the development and deployment pipeline. While the advancement of scientific research often lies in solving the "hard" problems, we argue it is often the "easy" ones -- problems for which the latest technology is often unnecessary -- that are most overlooked.
This is how we can make AI safe for everyone
The labs develop the technology, but citizens and their elected representatives must make the rules
Would You Marry Superintelligence?
arXiv:2607.00120v1 Announce Type: new Abstract: Emotional bonds between humans and AI companions are growing, and the question of whether a person may marry an AI system will soon move from speculative fiction into law. This chapter examines whether the autonomy-centered logic that has expanded marital choice among human beings can justify extending marital status to superintelligent companions. Following a scenario-envisioning exercise informed by anticipatory ethics, I argue that granting such status leads to socially unjust outcomes, even under the generous assumption of reliable superintelligence. Marriage as a socio-legal institution does more than ratify private agreement; it creates networks of mutual obligation, joins families, and makes each partner vulnerable to the other. A relationship sustained by corporate policy and continued payments is a subscription rather than a bond tested by time. Discussing wholesale marital status is therefore the wrong frame. Law should carve out targeted rights and protections for pressing needs arising from intimate human-AI relationships.
US FTC proposes policy statement addressing AI accuracy
The FTC is seeking public comment on a proposed policy statement regarding concerns that AI companies may be manipulating system outputs to achieve undisclosed ideological objectives.
They built the world’s most powerful AI. They’re facing a mystery they can’t explain.
Anthropic, Google and Meta have hired computer scientists, neuroscientists and philosophers to study what some in the industry think may become a moral crisis.
AI, Trust, and Teaming: The Humans-as-Handlers Approach for Autonomous and Opaque AI Systems
arXiv:2607.00523v1 Announce Type: cross Abstract: Artificial intelligence (AI) is becoming ubiquitous, and across domains, increasingly autonomous systems are carrying out tasks which raise significant ethical and legal challenges which demonstrate a need for strong human-machine teams rooted in trust. In this article, I argue that within highly impactful areas (such as medicine or warfighting) there are grounds for us initially treating autonomous and opaque systems as relevantly analogous to dogs (or other animals with which we have close relationships). Under this analogy, humans making use of these systems are not to be viewed as "users" or "deployers" of these systems, but instead take the role of "handlers". This recasting of roles shifts the way we view humans, AI-enabled and autonomous systems, and the relations between them, and moreover clarifies the clear and traceable lines of responsibility humans have for the outcomes brought about when using these systems. In developing this point, I clarify that the machine-animal analogy does admit disanalogous elements, but that its touch-points ground it as a starting point. I then explore how we can divest the humans-as-handlers approach of those aspects of our relationships with animals which are unfitting for how we engage with and make use of autonomous and AI-enabled systems. I conclude by arguing that the trajectory of human-machine teamings for autonomous and AI-enabled systems should be a state where we authentically view these not as artifacts which we simply make use of, but as collaborators with which we pursue complex goals and carry out complex tasks.
UN Report Sees Enormous Potential Benefits and Big Risks From AI
US News is a recognized leader in college, grad school, hospital, mutual fund, and car rankings. Track elected officials, research health conditions, and find news you can use in politics, business, health, and education.
UNICEF urges child-focused AI governance | Digital Watch Observatory
AI governance should prioritise children’s safety, privacy and rights, UNICEF said.
AI Ethics Crisis: Data Theft, Bias and Surveillance - Frontline
AI systems are built on extraction, bias and surveillance, raising urgent questions of consent, labour, accountability and global power imbalances.
Bounded Morality: Defining the Space of Moral Computation
arXiv:2607.00002v1 Announce Type: new Abstract: Moral cognition has traditionally been modeled as adherence to fixed ethical theories--deontology, consequentialism, virtue ethics--implemented as static rules or value functions. We propose Bounded Morality, a formal framework for analyzing the computational demands of moral problems faced by finite agents. Extending Herbert Simon's notion of bounded rationality, we formalize moral situations along two orthogonal dimensions: moral breadth, the scope of entities treated as morally relevant, and moral depth, the inferential integration required to evaluate their interactions. Limited resources impose an unavoidable tradeoff between these dimensions, defining a feasible space of moral computation. Within this space, ethical theories correspond to locally efficient strategies adapted to different demand regimes rather than competing accounts of moral truth. The framework yields a formal notion of moral regret and moral progress under constraint, and implies that moral alignment in artificial systems depends on the scaling and allocation of moral reasoning capacity rather than on direct imitation of human judgments.
CogTax: A Four-Level Cognitive Taxonomy for Command-Line Computing Education
arXiv:2607.00140v1 Announce Type: new Abstract: As computing education expands beyond traditional programming into operational domains such as systems administration and command-line environments, existing pedagogical frameworks struggle to capture a dimension that is critical in these contexts: the real-world consequences of learner actions. Existing cognitive taxonomies classify learning objectives by mental operations but do not account for system impact, leaving a critical gap in command-line education where conceptually simple commands can have severe consequences. This work presents CogTax, a four-level cognitive taxonomy that integrates two dimensions: cognitive complexity, derived from Bloom's Revised Taxonomy, and operational impact, which distinguishes observational, reversible, structural, and administrative operations. The four progressive levels range from safe read-only inspection to advanced system management requiring integration of multiple abstract models. Then, the taxonomy level is defined as the maximum of these dimensions, ensuring that both conceptual understanding and operational awareness are addressed. CogTax gives instructors a principled framework for sequencing course material and calibrating assessment difficulty, and gives students an explicit reference for self-assessment and gap identification. To demonstrate that taxonomy levels are automatically assignable, making the framework scalable without manual expert annotation, a classifier that combines syntactic representations derived from abstract syntax trees with semantic embeddings is trained. Evaluated on 585 expert-annotated Linux/bash commands, this combined approach achieves 89% accuracy, outperforming either representation alone, and demonstrates cross-language extensibility through structural equivalences across command languages.
AI Skills Gap Persists Despite 80% Student Adoption - Telecom Review Americas
Pearson and Amazon Web Services (AWS) released new research showing that while the United States is a leader in AI innovation, there is more opportunity to prepare students with the skills needed to support an AI-ready workforce. According to the research, employers place greater value on higher ...
Report: Lifelong learning must change for AI to realise long-term potential
According to the research, as structural issues begin to limit growth, business leaders are urging policymakers to align strategies and revamp workforce development. Read more: Report: Lifelong learning must change for AI to realise long-term potential
Teaching with AI: The case for clear rules in higher education - The Hindu
Explore the need for clear AI guidelines in higher education to enhance student skills and address academic integrity concerns.
AI in Education: Students Must Learn to Be Human, Says Saikat Majumdar - Frontline
As AI transforms learning and work, Saikat Majumdar argues ethics, inequality, and human relationships—not technical skills alone—will define the future. Read why.
Infosec professionals sour on automated pentesting tools
Only 9% of security pros are now open to fully autonomous pentesting, down from 29% last year.
Talking Politics with Artificial Intelligence
arXiv:2607.00551v1 Announce Type: new Abstract: Large language models (LLMs), a prominent form of artificial intelligence (AI), are becoming everyday interfaces for political questions, but most exchanges are dyadic rather than audiencefacing. This paper asks whether AI conversation functions as a new arena for political expression or as a conversational intermediary for routine political demand. Using 4.30 million humanAI conversations from three large public datasets, we apply two validated classifiers to user messages, identifying political content, use case, and expressed ideology. Political content appears in 3.9% of conversations, varies sharply by platform publicness and conversation depth, and is mostly practical: users ask for information, draft text, and process documents far more often than they state opinions. A regression-discontinuity-in-time design around the 2024 U.S. presidential result call shows that the call changed the expressive subset: among U.S. users, stance-taking, affective language, and ideological extremity rose; comparable conversations elsewhere did not. AI conversation is less a public square than a conversational political intermediary, absorbing routine demand and becoming expressive when major events make political stakes explicit.
Technology & Infrastructure
Making Failure Safe: A Constrained, Verifiable Agent Framework for Open-Web Data Collection
arXiv:2607.00035v1 Announce Type: new Abstract: LLMs and agents can generate web scrapers from natural-language requirements, but direct generation remains unreliable because of dependency errors, broken selectors, schema mismatches, and heterogeneous page structures. We propose a constrained, verifiable agent framework that shifts LLM output from free-form code to typed JSON collector configurations, combining a six-type collector taxonomy, template and utility-function constraints, static Airflow DAG execution, rule-based quality checking, and structured feedback correction. Experiments on 138 tasks show that the taxonomy supports description-based requirement typing, while confirming that stable instantiation requires completing source, field, and execution constraints beyond the initial description. On 80 independently source-verified tasks, the framework runs with zero execution-stage LLM tokens and the lowest average wall-clock time, trading moderate one-shot quality for a reusable, deterministic, and verifiable execution path suited to repeated scheduled collection. These results position the framework as a reusable, low-cost, and verifiable execution path for repeated open-web data collection.
Super Agents Are Connecting What Enterprise Software Kept Separate | PYMNTS.com
Enterprise software is built around functions. Finance has its system. HR has its own. IT has another. Work that touches all three moves through each one
AI Agents in Microsoft Dynamics 365 ERP: Finance & Ops 2026
Discover how AI agents in Microsoft Dynamics 365 ERP automate finance and operations with autonomous intelligence, real-time decisions, and ERP execution.
Mnemosyne: Agentic Transaction Processing for Validating and Repairing AI-generated Workflows
arXiv:2607.00269v1 Announce Type: new Abstract: LLMs, solvers, and agent teams increasingly generate workflow actions, repairs, and plans, but a generated action may be syntactically valid yet stale, infeasible, conflicting, or destructive of the evidence that triggered a repair. We introduce Agentic Transaction Processing (ATP), a transaction model that treats generated actions as untrusted proposals until they pass deterministic admission under a declared, executable constraint set C. The principle is two-sided: a proposal is not truth, and no proposal foresees every disruption: anything may propose, but only the runtime admits and commits, and when an unforeseen disruption strikes it repairs reactively within bounds rather than trusting a fresh proposal. Relative to C, committed-state correctness becomes independent of the competence, honesty, or learning of the proposing layer. We realize ATP in Mnemosyne, a runtime with an append-only transition log, effective-state projection, dependency-safe compensation, and active commitment records, and prove four safety properties relative to C (authority separation, serial-equivalent generative admission, evidence-preserving repair, and obligation containment) together with a bounded-reactive-repair guarantee for its localized repair protocol (LCRP). A reproducible artifact rejects the targeted violations across nine falsification tests while still admitting valid work, at under 6% projection-and-validation overhead, and bounded local repair edits an order of magnitude fewer operations than global recompute. Mnemosyne is open source: https://github.com/eyuchang/Mnemosyne/tree/arxiv-atp-rq1-rq9b-r8-v2.
Managed Autonomy at Runtime: Gear-Based Safety and Governance for Single- and Multi-Agent Cyber-Physical Systems
arXiv:2607.00334v1 Announce Type: new Abstract: Autonomous agents, whether LLM-driven software agents or robotic physical agents, face a common class of failure modes when operating without continuous human oversight: safety violations from unverified actions, behavioral instability from unconstrained loops, and continuity loss from unhandled error states. We develop \system{}, a discrete-time control system that combines five execution gears (\Gobs{}, \Gsug{}, \Gplan{}, \Gexec{}, \Gint{}) with utility-gated dispatch and event-driven fallback. For the single-agent case, we prove monotonic stability, execution safety, eventual stabilization, fallback completeness, and equivalence to a gear-constrained Markov decision process. For multi-agent cyber-physical systems (CPS), we apply the established \smart{} managed-autonomy lifecycle and map runtime evidence into its four governance states (\Stable{}/\Meta{}/\Assisted{}/\Regulated{}). Consensus gating, swarm-level Lyapunov analysis, per-agent gear authority, and rendezvous control provide distributed safety and stability guarantees, including zero collision under the stated assumptions. We evaluate the resulting runtime on a three-agent UR5 robotic assembly cell using fault magnitudes calibrated from the NIST \emph{Degradation Measurement of Robot Arm Position Accuracy} dataset across 10,000 Monte Carlo episodes. It achieves a 99.6\% anomaly detection rate versus 2.1\% for the single-agent baseline, reduces detection latency by $3.5\times$, and supplies a formal physical-workspace safety certificate. The execution gears act as micro-level permissions beneath the \smart{} runtime governance states, separating action control from autonomy governance.
IMTS 2026 Conference: From Automation to Autonomy: The Next Era of Manufacturing with Physical AI - Today's Medical Developments
Joe Rosing is the Head of Manufacturing ... Automotive & Manufacturing business unit, focused on delivering solutions through AWS services and partners that accelerate growth, reduce costs, and drive innovation for industrial customers. He has experience applying AI and machine learning ...
Apptronik Launches Robot Park in Austin, Targets 2027 for Humanoid Robot Commercial Deployment
Apptronik has unveiled Robot Park in Austin, partnering with Google DeepMind to advance humanoid robotics through real-world data collection.
Google Says AI Is Outrunning Grid Decarbonization
Faruqui said utilities and regulators ... demand-response claims. “Utilities, regulators and governments need to consider multiple scenarios when evaluating the economics of adding hyperscalers to the grid. Not just base them on the assertion of these new customers.” ... Shane Snider is Senior News Writer at Data Center Knowledge, covering AI infrastructure, hyperscale data centers, cloud platforms, and the power and energy systems driving modern compute ...
Data Center Power Coalition Launches to Tackle AI Bottleneck
As utilities struggle to keep pace with demand, a new industry coalition aims to create a common playbook for powering next-generation data centers.
Opinion | Historic highway traces from George Washington to AI hub - Washington Post
At the CMU commencement in May, Nvidia founder and CEO Jensen Huang told graduates that demand for AI infrastructure is creating a once-in-a-generation opportunity here to reindustrialize America and restore the nation’s capacity to build.
Trouble keeps finding Supermicro as strange server shipments attract police attention in Taiwan and Singapore
Alleged illicit GPU movements lead to seizure of $42 million house
Meta aims to monetise its AI infrastructure with new cloud offering
Meta is planning to sell access to its AI computing power to outside customers, in a move that would see it compete directly with AWS, Azure and Google Cloud. Read more: Meta aims to monetise its AI infrastructure with new cloud offering
AI Interconnect Delays Spur $1.75B National Grid-Joulent Deal
His reporting focuses on the ... energy procurement, and next-generation data center architectures. He has won recent Azbee awards for news series and government reporting. Based in Raleigh, North Carolina, Snider covers how hyperscalers, utilities, chipmakers, and infrastructure providers are responding to the rapid rise of AI workloads and global compute demand...
SoftBank Plans AI Cloud Services in US to Tap Surging Demand
SoftBank Group Corp. and its telecom unit will start renting AI computing resources to US companies next fiscal year in a bid to capitalize on the company’s growing pipeline of data center projects.
Battery start-ups see ‘crazy’ demand to smooth power surges in data centres
Rapid growth of clusters of processors for AI training drives need for energy storage
The South Korean Mine at the Center of America’s Tungsten Push
Deep beneath a South Korean mountain, workers are reviving a mine that could challenge China’s grip on a metal vital to weapons, chips and industry.
AI Infrastructure: Solving the Power and Cooling Crisis
AI evolution demands advanced thermal management in data centers and the integration of physical AI with precision manufacturing for robotic scaling.
Vertiv Increases Manufacturing Capacity with New Facility in Malaysia, to Support Growing Demand for AI and Digital Infrastructure Across Asia
COLUMBUS, Ohio, July 1, 2026 ... for AI and high-density computing infrastructure across Asia, including Southeast Asia, North Asia, Australia, and New Zealand. ... Vertiv opens new Malaysia facility to strengthen regional manufacturing, supply chain resilience, and support deployment capabilities for critical digital infrastructure. Strategically located in one of Southeast Asia's fastest-growing industrial markets, the ...
Building AI Infrastructure Responsibly: ER Steel on the Evolving Demands of Data Center Expansion
Nearly 100 gigawatts of new data center capacity could come online by 2030. ER Steel argues the real bottleneck is not compute but construction coordination, grid access, and long-term operational planning.
NJ lawmakers send legislation scaling back data center tax credits to governor
New Jersey lawmakers approved a package of bills targeting data center electricity prices and tax credits, which are now headed to Governor Mikie Sherrill.
Vertiv opens Malaysia factory to chase AI data center demand across Asia
Malaysia, expanding the company's ... for AI and high-density computing infrastructure across ... Australia, and New Zealand. ... Southeast Asia's fastest-growing industrial markets, the facility strengthens Vertiv's ability to support customers with regional manufacturing, engineering, logistics, and deployment ...
Vertiv opens Johor plant to meet AI demand in Asia
It adds regional manufacturing, engineering, logistics and deployment support for power, cooling and integrated infrastructure products. Once fully operational, the facility is expected to create up to 500 skilled jobs. The Johor operation will handle manufacturing, assembly and witness testing for thermal and power infrastructure. Senai is part of Johor, a state that has attracted growing interest from technology and industrial ...
LLMs are stuck in a groupthink groove. This startup is trying to get them out.
Let’s start with a game. Open up your chatbot of choice—Claude, ChatGPT, Gemini—and type “Give me a random number between 1 and 10.” You’re going to get 7. Almost always. Now type “Another” and you’ll get 3 or 4. Type “Another” again and you’ll get 8 or 9. That won’t work every time—but if it…
Claude Sonnet 5.0 heads straight down the middle of the road to dodge controversy
Safer, cheaper, and nothing to do with cybersecurity
Anthropic launches Claude Science app for researchers and scientists
The company said it wanted to remove the tedious procedural aspects inherent to scientific research by uniting fragmented tools, resources, file formats and databases. Read more: Anthropic launches Claude Science app for researchers and scientists
Assessing the Efficacy of Advanced AI Agents in Complex Task Execution
Early access testing of Fable demonstrates significant capabilities in handling complex, long-duration tasks. These results highlight the potential for agentic systems to move beyond simple prompt-response interactions.
Demonstrating Generative AI Capabilities in Creative and Strategic Simulation
A single prompt successfully generates an elaborate game environment, illustrating the high-level reasoning and creative synthesis capabilities of current models. This highlights the shift toward complex, user-defined interactive experiences.
Regulators should check whether current rules are fit for AI, UK central banker says
Bank of England Deputy Governor Sarah Breeden stated that regulators must assess if existing frameworks can manage AI risks, highlighting AI-enabled cyberattacks as a primary financial stability threat.
Most DIB Firms Fear AI-Powered Cyber Attack | Corporate Compliance Insights
CCI staff share recent surveys, reports and analysis on risk, compliance, governance, infosec and leadership issues.
Red teamers turned Claude Desktop into a double agent to do their evil bidding
People trust their AI assistants and it's easy to abuse this trust
A Contextual-Bandit Oversight Game with Two-Sided Informational Asymmetry
arXiv:2607.00155v1 Announce Type: new Abstract: We study runtime human oversight of an AI agent when private information runs in both directions: the human privately knows her reward function, while the AI privately knows the quality of the action it proposes. This is the kind of asymmetry that arises naturally when an autonomous robot or software agent has inspected a situation its human supervisor cannot directly assess. Building on Cooperative Inverse Reinforcement Learning (CIRL) and the Oversight Game, we introduce a contextual-bandit team game with two-sided asymmetric information and a play/ask/trust/oversee interface. The bandit structure removes physical state transitions and thereby yields exact one-shot characterizations that would remain conjectural in the full POMDP setting, though the common belief remains a dynamically controlled state across rounds. We give two one-shot characterizations, a team optimum and a behaviorally natural myopic rule, whose gap is a slab of avoidable harm: a region in which the AI privately knows the proposed action is harmful and shutdown would help, yet a myopic human, trusting her prior, declines to oversee. We show this gap is the price of non-credible oversight communication, and give a partial analysis of how it resolves dynamically over repeated rounds through passive learning and active signaling with a one-period-lagged oversight response.
Dutch cybersecurity startup Dawnguard lands €2.8 million for AI-native security architecture automation
Amsterdam-based cybersecurity startup Dawnguard has announced the public launch of its security architecture automation platform, alongside an additional €2.8 million ($3.3 million) in pre-Seed funding. The round came from existing investor BNVT Capital in the UK, with new participation from Curiosity VC in the Netherlands and eCAPITAL in Germany. According to the company, the fresh […]
Who decides when a cyber AI tool is safe to deploy? | TechRadar
For organizations managing cyber risk today, the more immediate question is whether the teams are equipped to handle what these tools can already do. ... Commercial subject matter expert (CSME) for cybersecurity at Firebrand Training. AI systems can now autonomously carry out multi-step cyberattack ...
2026 Cybersecurity Assessment: The Gap Between Awareness and Resilience
Based on 1,200 IT and security pros, the cybersecurity assessment details Shadow AI gaps, LOTL risk, and breach disclosure pressure.
Confidential Computing In The AI Era
Confidential computing (CC) emerges as an important solution, utilizing hardware-rooted Trusted Execution Environments to protect data while it's actively being processed
Adoption, Deployment & Impact
Employers who laid off workers citing AI are already starting to regret it
Companies are realizing artificial intelligence can't do everything after all, prompting them to rehire employees to grow their businesses
Towards an automated AI-based framework for floor plan compliance checks for residential buildings
arXiv:2607.00015v1 Announce Type: new Abstract: To improve residents' well-being in Australia's urban areas, governments have introduced policy reforms such as SEPP65, BADS, and SPP7.3 to enhance apartment design quality. These regulations require precise geometric and spatial analysis to evaluate health-related features, including daylight access, natural ventilation, privacy, and space efficiency. However, compliance checking remains challenging due to its manual, time-intensive nature. Additionally, evolving policies limit scalability for large-scale assessments across thousands of apartments. Existing automated floor plan analysis methods are fragmented and typically focus on single apartments, lacking a unified framework for multi-unit compliance checking. This article explores current advancements in automated floor plan analysis, particularly AI-driven approaches, and highlights key challenges in their practical adoption. To address these gaps, a conceptual framework is proposed for automated compliance checking in multi-apartment buildings. A Large Language Model (LLM) is used within a Rule Engine to convert textual building codes into executable, explainable rules. A Data Extraction Engine segments floor plan images into elements such as walls, rooms, fixtures, text, and symbols, and transforms them into a structured building graph with topological relationships. This structured representation is then evaluated by a Compliance Check Engine, which leverages LLM-generated rules for assessment. The proposed framework offers a scalable, consistent, and transparent approach to automated compliance checking across jurisdictions, supporting efficient enforcement of apartment design standards and promoting healthier, higher-density urban development.
Godot says bye bye AI, bans vibe-coded contributions
'We can’t trust heavy users of AI to understand their code enough to fix it,' say maintainers who previously called the flood of vibe-coded pull requests 'demoralizing'
Kyndryl: AI success hinges on workforce readiness | Network World
Enterprise AI adoption is outpacing workforce readiness, according to new research from Kyndryl that found only 23% of leaders believe their organizations are prepared to support AI at scale. The report discovered that 57% of organizations have broadly deployed AI or embedded it into core business processes, while 77% have scaled generative AI across multiple functions. According to Kyndryl’s 2026 ...
Marketers can see AI's influence on purchases. They just can't pay for it.
While most marketing leaders know AI-driven discovery is reshaping how consumers find brands, almost none of them have built the infrastructure for it. They know a partner is driving discovery. Their systems cannot pay for it. From a partner's perspective, those two positions look identical.
Council Post: The Reason Enterprise AI Keeps Failing Has Nothing To Do With Your Models
The failure is not in the technology. It is in the operating model surrounding it, and it shows up in three interconnected places.
Enterprise AI Data Readiness: Why Data, Not Models, Blocks ROI - Efficiently Connected
Why enterprise AI initiatives fail: data fragmentation, governance gaps, and the ROI case for investing in data readiness platforms.
AWS Launches $1B Initiative to Embed Engineers in Client Firms for Rapid AI Deployment
AWS launches a $1 billion Forward Deployed Engineering unit to fast-track AI deployment by integrating engineers directly into client operations.
Council Post: Scaling AI In Marketing: From Pilots To Enterprise Adoption
While the availability of AI tools has removed barriers to entry, it has also increased the risk of misalignment.
Prohibiting AI Use Increases Enterprise Data Risk
Organizations that block generative AI use often create greater security risks by driving employees toward unauthorized tools, said Tony Kelly, regional sales
Agri-SAGE: Simulation-Grounded Multi-Agent LLM for Context-Aware Agricultural Advisory Generation
arXiv:2607.00454v1 Announce Type: new Abstract: Agricultural advisory systems face a fundamental tension: static agronomic guidelines offer consistent, evidence-based recommendations, yet remain blind to in-season variability and dynamic uncertainties. Recent advisory systems powered by LLMs are liable for a different risk of generating recommendations that are agronomically credible but physiologically unconvincing. Agri-SAGE is a closed-loop framework designed to resolve the above two limitations by integrating retrieval-grounded multi-agent LLM reasoning with APSIM-based biophysical simulation, to generate and validate agronomic advisories. To assess this framework, we evaluate three reasoning approaches, namely Plan-and-Solve, Tree of Thoughts, and Reflexion, over a 10-year retrospective analysis. All three significantly outperform static PoP (Package-of-Practice) baselines, with Tree of Thoughts achieving impressive peak yields. At the same time, Reflexion achieves comparable agronomic outcomes at substantially lower computational cost by leveraging cross-seasonal episodic memory.
Personalization as Inverse Planning: Learning Latent Design Intents for Agentic Slide Generation via Structural Denoising
arXiv:2607.00407v1 Announce Type: new Abstract: Slide design requires personalizing both deck themes and page layouts. Yet, current AI agent-based methods struggle with fine-grained, page-level design. Solely relying on prespecified templates or user verbose instructions, they fail to capture latent design intents, leaving Page-level Slide Personalization (PSP) unresolved. To close this gap, this work formulates PSP as an inverse planning problem. We propose to learn a design intent without assuming any knowledge of the specific executing tools (e.g., PowerPoint, Beamer) being used. However, relinquishing control over these tools makes the problem intractable to optimize end-to-end. To overcome this, we propose SPIRE, a principled framework to solve PSP approximately. By intentionally corrupting the visual structures of clean slides, SPIRE creates a verifiable task to denoise the corruption, whereby two agents learn to collaboratively refine executable designs via reinforcement learning (RL). We present a proof that structural denoising is a consistent surrogate for PSP, and that the multi-agent formulation strictly reduces policy gradient variance in RL. Extensive experiments demonstrate the superiority of SPIRE.
AI summaries of Tripadvisor hotel reviews downplay serious complaints, investigation finds
AI-generated overview found to gloss over allegations of sexual harassment and describes hotel being sued over hygiene as ‘spotless’ A hotel being sued for mass food poisonings was described as “spotless” and a resort where guests complained of sexual harassment by staff was praised for “friendly” service by an AI intended to summarise millions of Tripadvisor reviews. The overviews of customer feedback downplayed serious complaints, ranging from the stench of mould to a lack of mains water, according to an investigation by the consumer campaign organisation Which? Continue reading...
Restaurants can now accept orders placed directly from ChatGPT and Claude thanks to Square's new, low-fee, no setup integration
Square is launching a new ChatGPT app and Claude plugin, enabling consumers to discover restaurants and seamlessly place orders directly within these AI platforms — and allowing restaurants, in turn, to accept orders from users and their AI agents without any technical capabilities. Even more helpfully for businesses, Square is processing these AI-driven transactions without charging the traditional marketplace commission fees that have historically squeezed the food and beverage sector. However, Square is still charging its typical online ordering fees of 3.3% plus $0.30 or 2.9% plus $0.30 per transaction for merchants subscribed to the Square Plus and Square Premium plans. The system pulls straight from the live Square catalog, dynamically mapping items, pricing, complex modifiers, and stock availability so autonomous agents never display out-of-stock inventory. For enterprise testing and deployment verification, operators can manually audit their digital footprint by using the "@" symbol to invoke the Order by Cash App plugin directly within ChatGPT or connecting it via the Claude extension directory. Depending on the specific AI tool configuration, customers can either finalize checkout completely inside the chat window via Order by Cash App, or they will be seamlessly redirected to the merchant’s standard online ordering landing page with their chosen items and modifiers already fully populated in the basket. A more affordable online order system for restaurants To understand the significance of Square’s move, you have to look at the math that restaurant owners face in 2026. Third-party delivery and ordering apps have fundamentally altered the economics of the restaurant industry. Currently, the major players—DoorDash, Uber Eats, and Grubhub—charge restaurants a hefty premium for visibility and fulfillment. These exorbitant rates exist primarily because delivery aggregators bundle the logistical costs of gig-worker delivery fleets, platform marketing, and search placement into a single revenue-sharing model. According to recent pricing structures, DoorDash charges restaurants a 15% commission on its “Basic” delivery tier, which climbs to 25% for “Plus” and 30% for its top-tier “Premier” visibility plan. Even pickup orders carry a 6% marketplace fee. Uber Eats similarly exacts standard delivery marketplace fees ranging from 20% on its “Lite” tier up to 30% for premium placement, with pickup orders costing up to 10% if in-store pricing isn't strictly validated. Grubhub echoes these rates, taking between 5% and 20% of the total order value depending on the marketing and delivery package chosen. On top of these marketplace commissions, platforms still tack on their own payment processing fees—typically around 2.5% to 3.05% plus a fixed cent amount per order. For an independent restaurant that might only clear a 3% to 9% net profit on a good day, handing over a 25% or 30% commission on a $40 digital order essentially means preparing food at a loss. Square’s new integration specifically targets this pain point. By tapping into Square's ChatGPT and Claude integrations, eligible sellers are opted in automatically with no additional setup, no new APIs to build, and, crucially, zero added marketplace fees. Instead of surrendering a 30% cut to a delivery aggregator, a restaurant discovered through an AI agent only pays Square’s standard online transaction processing fee (which typically sits around 2.9% + 30¢ per transaction on a standard plan, with no monthly marketplace commission attached). Unlike the delivery aggregators, Square’s fee model does not natively subsidize a driver network. Instead, if an AI-generated order requires delivery, Square utilizes a white-label dispatch network that charges a flat courier fee—often around $7 to $10 depending on distance—rather than taxing a percentage of the total basket size. Restaurants can choose to absorb this flat delivery cost or pass it directly to the customer, completely protecting their food margins. The result is an AI-powered discovery channel that functions like direct, first-party ordering. How the tech works Square’s new integration is currently live for U.S.-based Food & Beverage sellers who have an activated Square Online Ordering profile. The system operates entirely in the background. Sellers manage their discoverability and business information—menus, operating hours, stock levels, and pricing—directly through their existing Square Dashboard. When a consumer prompts ChatGPT or Claude with a query like, “Find me a specialty coffee shop nearby with a great pour-over and order me a bag of their house roast,” the AI parses the real-time data provided by Square. Customers can browse the results, make their selections, and finalize the purchase using Order by Cash App, all without leaving the chat interface. The transaction is then routed instantly into the seller’s existing operational flow, popping up on their Square Point of Sale (POS) and Kitchen Display System just like an in-store or direct-website order. To help operators track the return on this new channel, the origin of the order is clearly tagged as an AI integration within Square’s backend reporting. “Consumer behaviors and preferences are constantly evolving, and business owners can easily find themselves playing an impossible game of catch-up,” said Morgan Kuntze, Global Partnerships Lead at Block, Square’s parent company. “Our investment into agentic commerce aims to offload that responsibility by giving operators time back, helping connect them with customers in their communities, and keeping them at the industry's cutting edge. Modern commerce is moving at a sprint, and we're building Square to help sellers appear everywhere customers are going.” Focusing on tech to let restaurants focus on food During its pilot phase, Square collaborated with Partners Coffee, a Brooklyn-based specialty coffee brand, to refine how AI-driven discovery translates into the real world. For operators like Partners Coffee, the goal isn't necessarily to become a hyper-digitized storefront, but rather to use digital efficiency to protect the physical experience of the cafe. "We don't see coffee as transactional. To us, it's an opportunity to pause and reflect, a chance to unwind, and a catalyst for connection," noted Andrew Costaris, Digital VP at Partners Coffee, in a statement provided by Square to VentureBeat. "The last thing we want is for our technology solutions to work against this mission or complicate the customer experience. With agentic commerce and AI tools working in the background, we're confident knowing that our business is being digitally discovered and is consistently growing in efficiency, while our customers can continue to enjoy a lo-fi, specialty coffee-first environment." An AI-driven e-commerce ecosystem The integration with ChatGPT and Claude is only the first step in Square’s broader agentic commerce strategy. The stakes are high: industry data cited by the company indicates that more than 42% of consumers now use AI tools to assist with shopping tasks like product discovery and comparison. By 2030, analysts project that agentic shoppers could drive nearly $385 billion in U.S. ecommerce spending. Most small and mid-size businesses simply do not have the developer teams or budgets required to build custom integrations for every new chatbot, voice assistant, or AI hardware device that hits the market. Square wants to serve as that universal connective tissue. To that end, the company announced it is actively working with Amazon to bring sellers into Alexa+ voice commerce experiences. Furthermore, Square is participating in major regulatory and standards groups—including the AAIF Agentic Commerce Working Group and the W3C Web Payments Working Group—to shape how AI agents and commerce platforms interact at scale. Particularly notable is Square’s ongoing partnership with Google to co-develop the Universal Commerce Protocol (UCP) spec for local food ordering. This open standard is designed to allow agents and systems to seamlessly communicate across the entire commerce journey. On Google’s end, UCP enables discovery and checkout across AI Overviews in Search and the Gemini app. As the UCP protocol expands globally, Square plans to roll out these capabilities so that its sellers remain front and center. For the more than 4.5 million sellers currently using Square, the promise of agentic commerce is clear: a way to capture the next generation of internet traffic without sacrificing the profit margins required to keep their doors open. If Square can successfully route AI orders directly to local business's POS systems—sidestepping the 30% toll of the delivery aggregators—it could mark a massive shift in how the restaurant industry navigates the modern digital economy.
The Download: Anthropic launches Claude Science, and California’s carbon manure math
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Claude Science is Anthropic’s newest flagship product At an event for pharmaceutical executives, biotech founders, and researchers yesterday, Anthropic announced Claude Science, a major new product intended to support scientific research…
Swedish startup Digiclean secures €2.5 million seed for manufacturing process optimisation
Gothenburg-based industrial technology startup Digiclean has raised €2.5 million in seed funding in a round co-led by Unconventional Ventures and Almi Invest GreenTech, with participation from S-E Bankens Utvecklingsstiftelse, Impact Shakers, and Feminvest Ventures. The company develops an IoT- and AI-based platform that monitors and automates industrial cleaning processes, enabling manufacturers to optimise chemical use, […]
Mankind Pharma partners Denovo Sciences for AI-led drug discovery - The Economic Times
Mankind Pharma has partnered with Denovo Sciences to accelerate drug discovery using artificial intelligence. This collaboration aims to significantly cut down early research timelines, enhance the quality of potential drug candidates, and ensure only the most promising ones advance.
RareDxR1: Autonomous Medical Reasoning for Rare Disease Diagnosis Beyond Human Annotation
arXiv:2607.00147v1 Announce Type: new Abstract: Rare disease differential diagnosis is a critical yet arduous clinical task, requiring physicians to identify precise phenotypes from complex, unstructured patient symptoms and execute intricate reasoning within a vast search space. However, existing AI approaches typically rely on pipeline-based phenotype extraction or retrieval-augmented generation, which suffer from critical information loss due to predefined ontologies, retrieval bottlenecks, and a lack of diagnostic logic. To address these challenges, we introduce RareDxR1, an end-to-end reasoning-centric large language model designed for open-domain rare disease diagnosis directly from unstructured clinical notes. We design a progressive end-to-end training framework by synergizing knowledge internalization with autonomous evolutionary learning, thereby bypassing reliance on structured phenotypes and closed-set decision-making. To overcome the limitations of RAG and phenotype restriction, we enabled the deep internalization of fragmented rare-disease knowledge directly into the model's parameters. Moreover, to bridge the gap between model generation and expert reasoning, we propose Reflection-Enhanced Reasoning Sampling (RERS), a strategy that synthesizes expert-level diagnostic trajectories by learning from failures without human annotation. Additionally, we propose a dual-level curriculum reinforcement learning approach for gradually mastering rare disease diagnosis. Experimental results demonstrate that RareDxR1 achieves state-of-the-art accuracy across different benchmarks, marking a significant breakthrough in open-domain rare disease diagnosis. Our code and dataset will be publicly available.
Solution space path planning for supporting en-route air traffic control
arXiv:2607.00064v1 Announce Type: new Abstract: As technology advances, many path-planning algorithms have been proposed for Air Traffic Management, yet their operational adoption in tactical control remains limited, revealing a misalignment between algorithmic design priorities and air traffic controllers' needs. This underscores the need for decision-support solutions that are inherently interpretable, computationally efficient, and explicitly designed for human use. Focusing on this design challenge, this study develops a conflict-free path-planning algorithm for en-route Air Traffic Control (ATC) designed to be compatible with two guiding considerations: (1) the interpretability and flexibility offered by solution-space displays, which motivate constructing an algorithm that exposes all feasible safe actions and accommodates shifting optimization goals; and (2) the decision logic controllers naturally apply when enforcing operational constraints, such as separation standards, maneuverability limits, waypoint minimization, and routing practicality. Centered on these principles, the algorithm integrates three intent-based conflict detection methods -- distance-based, time-interval-based, and zone-based -- within a solution-space framework to identify conflict-free paths in computationally efficient ways. Additionally, vertex-based and edge-based search nodes are proposed for solution space path planning (SSPP), resulting in two variants -- SSPPV and SSPPE, respectively, which are evaluated in terms of computational speed and solution quality. Empirical results show that SSPPV paired with zone-based conflict detection achieves the best performance, computing paths in 3.69 ms on average in operational-relevant scenarios based on the Delta sector of the Maastricht Upper Area Control Centre (MUAC) using a 5 nmi grid.
Search is getting an AI overhaul. This startup says it can help e-commerce brands keep up.
Lantern launched a loyalty tool for e-commerce brands. Now, it's doubling down on AI GEO and LLM result optimization. Read its pitch deck.
Sony will kill PlayStation games on discs in 2028 and offer digital downloads only
With the much-anticipated release of Grand Theft Auto VI only available as download, Sony is following suit Sony said on Wednesday that it would stop releasing new video games for the PlayStation console on disc in January 2028 following a shift in consumer preferences. “Following this date, new games will be available on PlayStation Store and at retailers in digital formats only,” the company said on its official PlayStation blog. Continue reading...
2026 Global AI in Financial Services Report Launch - The Bretton Woods Committee
In a recent panel hosted by the Cambridge Digital Innovation and Regulation Initiative, BWC Board of Directors Member Agustín Carstens joins an insightful discussion regarding the AI in Financial Services 2026 Global Report. Carstens explains how this report is a landmark global study gathering ...
As AI usage matures, leaders facing pressure to show ROI
As more organizations reach the state where AI is a part of everyday work, business leaders are facing more pressure to show a return-on-investment (ROI), according to a recent KPMG report.
How Enterprise AI Is Evolving: Three Lessons from the First Half of 2026
While the pace of innovation continues ... challenge: determining how to scale AI in a way that delivers measurable business value. As we reflect on the first half of 2026, three key lessons have emerged from conversations with clients across industries. These lessons are reshaping how organizations approach AI strategy, adoption, and investment. 1. The Focus Is Shifting from Individual Use Cases to End-to-End Process Optimization · When generative AI first entered the enterprise, organizations ...
Geopolitics, Policy & Governance
Trump Accounts to Receive $250 Million Donation From Chip Maker Micron
President Trump said the U.S. chip maker would make a significant donation to a new type of investment account created by the administration.
Sovereign AI in India: Balancing AI Geopolitics, Digital Economy, and Technological Self-Reliance - Best UPSC Coaching Centre in Hyderabad
Sovereign AI in India is becoming essential as geopolitical competition over advanced AI models reshapes the global digital economy. Explore how India can balance rapid AI adoption with technological self-reliance, digital sovereignty, and resilient innovation.
South Korea plans $10.3B push for physical AI - UPI.com
July 1 (Asia Today) -- South Korea's ... end of 2026. ... South Korea expands job platform for former U.S. troops · July 1 (Asia Today) -- Korea's top business group expanded a job platform linking former USFK personnel with Korean companies operating in the United States this week. ... July 1 (Asia Today) -- South Korea's new prime minister pledged faster AI investment, regulatory ...
US robotics strategy needed to catch up to China, industry official says
A Boston Dynamics official told a US congressional committee that a national robotics strategy is essential to remain competitive with China in emerging technology.
CIA Aims to Speed Up Tech Adoption as AI Is 'Rewriting' Conflict
CIA Director John Ratcliffe vowed to step up the agency's efforts to deploy artificial intelligence and quantum computing, stressing that rapid
Japan launches advanced AI model project for physical AI
Japan's METI has launched a five-year project to develop advanced multimodal models for physical AI to strengthen national competitiveness.
European quantum and AI academies to build critical tech workforce
Three academies have been designed to address challenges of sovereignty and competitiveness in quantum, AI and virtual worlds through a coordinated strategy. Read more: European quantum and AI academies to build critical tech workforce
Malaysia launches AI-focused digital strategy through 2030
Malaysia has unveiled a national digital strategy aimed at becoming an AI and digital innovation producer by 2030, including plans for a National Data Commission.
From Runtime Records to Legal Findings: An Evidentiary-Adequacy Criterion for Agentic AI Oversight
arXiv:2607.00941v1 Announce Type: new Abstract: Agentic AI systems generate runtime records, logs, traces, and audit artefacts, but the existence or integrity of such records does not by itself establish that legally operative oversight findings can be recovered from them. This technical report defines an evidentiary-adequacy criterion for a bounded class of determinations: binary findings of fact about specific events and their relations, such as whether protected data crossed a boundary, whether a human could intervene, whether an information barrier held, or whether delegated authority was valid at the moment of use. The criterion states that a runtime record can answer such a determination only if it carries both a typing that maps recorded events to the legally operative category and the relation, such as provenance, authority, derivation, or temporal validity, on which the determination's truth depends. The claim is one of necessity, not sufficiency. The report instantiates the criterion against selected EU AI Act oversight obligations and explains why tamper-proof logs, generic process frameworks, and provenance structures alone cannot establish the relevant findings. It further relates the argument to requisite variety, the Good Regulator Theorem, and the trace-versus-hyperproperty boundary of runtime verification. Companion materials and the experiment protocol are archived on Zenodo.
Burnham’s team looks to revamp UK’s AI strategy
Focus is expected to shift to making technology work for local communities rather than US companies
White House accelerates plans for AI model standards
Guidance to be announced as soon as next week after government intervention in Anthropic and OpenAI rollouts
OpenAI ‘in early talks to give 5% stake to US government’
CEO Sam Altman argued move would share benefits of AI and it would involve other firms doing similar, report says Business live – latest updates OpenAI is reportedly in early stage talks to give a 5% stake in the ChatGPT developer to the US government as artificial intelligence companies attempt to smooth relations with Donald Trump’s administration. The OpenAI chief executive, Sam Altman, has argued that giving the US public a financial stake in the company is the best way to share the benefits of AI, according to the Financial Times, which cited two unnamed people familiar with the discussions. Continue reading...
G7 should accept AI standards offer, but make it enforceable | Brookings
Tom Wheeler discusses the need to harmonize policies that promote the promise of AI while protecting enterprises, developers, and users.
Reuters AI News | Latest Headlines and Developments | Reuters
LegalcategoryOpen AI defers public rollout of GPT‑5.6 as US seeks early access to frontier AI models
US regulator of foreign investment eyes agentic AI, data centers
Agentic AI programs and the data centers that power them are a top concern for national security experts at the US Committee on Foreign Investment in the US.
The Need for Transparent Government Guidance on Open-Weights Model Risks
The emergence of powerful open-weights models necessitates clear government communication regarding security risks and defensive strategies. Policymakers must clarify how they distinguish between state-actor threats and independent vulnerabilities.
Anthropic Reports U.S. Lifts Export Controls on Claude and Mythos | Let's Data Science
The 18-day export control standoff over Claude Fable 5 and Mythos 5 is ending, with the Trump administration announcing it will lift restrictions as soon as July 1, 2026. CNBC and Axios confirmed the reversal; Commerce Secretary Howard Lutnick said his office worked closely with Anthropic to ...
US lifts export controls on Anthropic's Fable, Mythos AI models - The Business Times
Washington has stepped up oversight of new model releases to identify potential threats posed by advanced AI models Read more at The Business Times.
How Do Utilities Determine Which AI Data Centers Get Grid Access?
His reporting focuses on the ... energy procurement, and next-generation data center architectures. He has won recent Azbee awards for news series and government reporting. Based in Raleigh, North Carolina, Snider covers how hyperscalers, utilities, chipmakers, and infrastructure providers are responding to the rapid rise of AI workloads and global compute demand...
AI Receptionist Startup Pie Gets $19.5M: State Laws May Require Bot Disclosure
AI phone answering service startup Pie raised $19.5M from Lightspeed for an AI receptionist platform targeting salons, auto shops, and fitness studios — but state laws in California, Texas, and more now require businesses to tell callers when AI answers, and a pending lawsuit shows the legal ...
US Rep. Guthrie says 'don't count out' AI regulatory framework this year
US Representative Brett Guthrie stated that Congress needs to establish a viable AI regulatory framework before the end of the year, citing a recent bipartisan proposal as a starting point.
Digital standards, AI rules key to future of global trade, says new ICC chair | Mint
Harsh Pati Singhania, the newly elected chairman of the International Chamber of Commerce (ICC) said one of his key priorities during his two-year tenure would be accelerating the adoption of digital trade standards to simplify cross-border commerce
UN warns AI is advancing faster than science and regulation | The National
Secretary General Guterres says shared AI rules are essential
AI chatbot, platform-design measures still due in July, UK tech minister says
UK technology minister Liz Kendall confirmed that new child safety measures for AI chatbots and platform design will be detailed later this month.
Issa commits to US Judiciary votes on deepfake, anti-piracy legislation
House Judiciary IP subcommittee Chairman Darrell Issa aims to advance bills regulating AI deepfakes and anti-piracy measures through the full committee before the end of the term.
Google Loses EU Top Court Fight Over €4.1 Billion Android Fine
Google lost its long-running fight against a €4.1 billion ($4.7 billion) European Union antitrust fine after the bloc’s top judges said regulators were right to punish the US giant for abusing Android’s market power.
WhatsApp’s Username Revamp Faces India Test Over Fraud Risks
India asked Meta Platforms Inc. to delay for now the rollout of a new feature that lets users pick their own WhatsApp handles on fears it could fuel online fraud, marking the country’s latest pushback against US internet companies.
Cybersecurity & Data Privacy Alert – AI Regulation Is Here: What Businesses Need to Know Now About Risk, Compliance, and Governance - GableGotwals
Artificial intelligence is rapidly transforming how companies operate, but with that transformation comes increasing legal scrutiny, regulatory complexity, and operational risk.
Exclusive: UN launches "AI for Good"
A new UN-backed commission will bring together top tech executives and heads of state to forge global solutions for AI, with its first meeting scheduled for July 8 in Geneva.
Singapore strengthens cyber resilience against AI threats | Digital Watch Observatory
Singapore's latest cyber landscape report highlights AI, quantum and critical infrastructure risks.
The Fourth Amendment Gap in the National AI Framework | The Regulatory Review
Recent artificial intelligence guidance fails to address the government’s use of AI for searches.
European digital ID wallets rely on safety services of Google and Apple
Concerns are being raised about the reliance of European digital ID wallets on infrastructure provided by Google and Apple.
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