05 Sci-Tech

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 As AI agents are integrated into an organization, enterprises will need to pivot from a set of linear processes and steps, to rewiring work in a very different way, explains Shah. That’s because the value in AI agents isn’t as another layer in an existing technology stack but as a connective tissue, he explains, moving between or across layers to coordinate a high-level task or retrieve and interpret data from multiple discrete applications. AI agents can create “a true competitive differentiation for an enterprise” by making decisions based on this capacity to contextualize, he says. “That is where the next battleground will be.”

To build this connective tissue, leaders need to adapt their technology stack to surface higher quality decisions from AI agents, prioritizing access to multiple datasets and applications simultaneously to develop tacit knowledge. “Organizations that make this architectural shift become genuinely more adaptive,” says Chatterjee. “When a new business requirement emerges, you don’t wait six months for a software vendor to build a feature. You configure an AI employee using natural language and connect it to the systems it needs. The time from business to production workflow drops from months to days.”

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Pope Leo XIV called Monday for robust regulation of artificial intelligence and for its developers to work for the common good rather than profit, issuing a sweeping manifesto on safeguarding humankind as the technology impacts everything from work to war.

“Magnifica Humanitas” (Magnificent Humanity), Leo’s first encyclical, has been eagerly awaited ever since history’s first U.S.-born pope announced days after his election that he considered AI to be the biggest challenge facing humanity today.

In the text, Leo denounced the “culture of power” driving the AI race, especially in developing ever more sophisticated methods of remote warfare. He declared that it was “not permissible” to entrust irreversible, lethal decisions to AI systems, setting up another flash point between the American pope and the Trump administration, which has worked aggressively to deregulate AI development.

“Artificial Intelligence now demands to be disarmed, freed from logics that turn it into an instrument of domination, exclusion and death,″ the pope told a special Vatican presentation of the encyclical, one of the most authoritative types of teaching documents a pope can issue.

Experts in the tech industry, academia and Catholic morality said the document will likely become a benchmark in the debate over AI, a point of reference for policymakers, researchers and ordinary folk alike. It comes as the near-daily developments in the technology trigger concerns over AI replacing human jobs and even human intelligence.

Taylor Black, a Microsoft AI executive and director of Catholic University of America’s AI institute, said the document would prompt people “at the forefront of these tools” to ask questions such as “What does it mean to be human?”

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There is a category of production incident that engineering teams are not tracking yet — because it doesn’t fit any existing postmortem template.

The agent initiated an action. The action was technically correct given the agent’s context. The context was incomplete. The infrastructure cascaded. And, by the time the incident review happened, three teams were arguing about whether it was an agent failure or an infrastructure failure,  because the frameworks for thinking about these two things have never been connected.

The scale of this exposure is no longer theoretical. Seventy-nine percent of organizations now have some form of AI agent in production, with 96% planning expansion. Gartner predicts 33% of enterprise software will include agentic AI by 2028, but separately warns that 40% of those projects will be canceled due to poor risk controls.

What neither statistic captures is the failure mode happening between those two numbers: Agents that are running, that are not canceled, and that are quietly generating infrastructure events no one has categorized as risk.

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Chinese AI startup DeepSeek just made one of the boldest pricing moves in the artificial intelligence race so far. The company announced it is permanently slashing the cost of its flagship V4-Pro AI model by 75%, bringing prices down to just a fraction of what developers were paying only weeks ago. AI companies worldwide have been facing two major problems: high infrastructure costs and limited access to high-end AI chips. So when a company suddenly cuts prices this aggressively — and permanently — it usually signals something important is changing behind the scenes.

DeepSeek says usage costs for V4-Pro now range from 0.025 to 6 yuan per million tokens, depending on workload type, down sharply from the previous pricing range of 0.1 to 24 yuan per million tokens. For developers building AI apps, agents, and services, that kind of drop could significantly lower operating costs.

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Microsoft AI chief executive Mustafa Suleyman is warning that artificial intelligence could soon replace large portions of the white-collar workforce, predicting that AI systems will reach human-level performance across most professional tasks within the next 18 months.

The comments mark one of the clearest timelines yet from a major tech executive about how quickly AI could disrupt office-based professions, including law, accounting, marketing, and project management.

Speaking with the Financial Times, Suleyman said that most work involving “sitting down at a computer” is now vulnerable to automation as AI capabilities rapidly advance.

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A familiar warning now shapes much of the discussion about artificial intelligence: A handful of dominant firms will control the technologies, stifle innovation, and require aggressive antitrust intervention. It is a compelling story—and mostly wrong.

The idea that large companies automatically mean less innovation has become conventional wisdom in antitrust circles. European regulators have embraced it, blocking mergers and attacking American tech companies. The Biden administration followed that path, treating size itself as a threat and wanting government-led AI. The Trump administration, by contrast, has signaled a more evidence-based view—one grounded in both economic logic and empirical studies.

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OpenAI CEO Sam Altman said on Tuesday the rapid development and adoption of AI would not lead to a global “jobs apocalypse” and the technology had not claimed as many white-collar jobs as he had feared. 

Speaking virtually at a Commonwealth Bank of Australia (CBA) conference in Sydney, Altman said he was initially concerned about the impact AI would have on global employment levels. 

 

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Beginning this summer, University of California Berkeley School of Law students will be banned from using artificial intelligence to complete coursework or exams.

Under the newly adopted policy, students cannot “conceptualize, outline, draft, revise, and edit their work” using AI.

It also explicitly forbids students from asking AI to correct grammar mistakes or translate a paper into English.

Students are permitted to use AI for “research on papers ONLY for the limited purpose of identifying sources, such as cases, statutes, or secondary sources,” the policy states.

However, professors are permitted to make exceptions to this rule as long as they “do so in writing and with appropriate notice and require students to disclose any authorized AI use,” it states.

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A proposed data center expected to cost more than $5 billion ran into intense resistance Thursday night in rural Pennsylvania, where residents packed a town hall meeting and delivered a clear message: They do not want their farmland and community identity sacrificed for a largely undefined mega-project.

During a three-hour informational session at Bangor Area Middle School, residents of Lower Mount Bethel Township voiced overwhelming opposition to the proposed Lower Mount Bethel Tech Center, according to WFMZ-TV. The event was organized by the project’s major stakeholders, including Peron Development and J.G. Petrucci Co., rather than township leaders.

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The wind picks up dust from the unpaved road one afternoon in December as Jack van Honk turns into a ramshackle neighborhood in Lambert’s Bay, on the west coast of South Africa. A stocky woman in a red patterned sundress steps out of a small home painted palest sea green, her ochre-dirt yard crowded with potted plants, many medicinal. She smiles broadly, deep wrinkles creasing a face that is cherubic and yet careworn beyond her 47 years. “Doctor! I missed you,” she beams, her husky voice barely more than a hoarse whisper.

Maria carries a rare genetic mutation that is almost unknown outside of southern Africa. Its effects have been to calcify a part of the brain called the basolateral amygdala, and to thicken and scar the vocal cords. A friend of Maria with the same condition lives several hours inland, and sometimes they meet when van Honk brings them to Cape Town for brain scans and other tests. “It helps to know I’m not alone,” Maria says.

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China has launched a national programme that will assign every humanoid robot manufactured in the country a unique digital identity code, effectively a citizen ID, but for bipedal machines (those that can balance and walk/run on two legs).

The initiative, called the Humanoid Full Lifecycle Management Service Platform, was announced on Friday. It is led by the Humanoid Robotics and Embodied Intelligence Standardization committee, which is under China’s Ministry of Industry and Information Technology (via South China Morning Post).

Plans by corporate and state America to rapidly build AI data centers could meet stiff resistance is a recent Gallop poll is correct. The poll shows 70% of Americans oppose Data centers, ESPECIALLY in their local regions.

Not only do residents fear the tax on the resources, the taking of land, but also they fear the surveillance capacity of these data centers to enable the state to track the actions of citizens almost in real time.

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Older adults who cut back on dietary fat or reduced the amount of animal-based protein they consumed showed signs of becoming biologically younger, according to new research from the University of Sydney.

The study, published in Aging Cell, found that adults between the ages of 65 and 75 experienced reductions in their estimated ‘biological age’ after following specific diets for just four weeks. Researchers say the findings suggest dietary changes later in life may quickly improve markers linked to aging and overall health.

The research was led by Dr. Caitlin Andrews from the University of Sydney’s School of Life and Environmental Sciences. While the results are promising, the scientists emphasized that the study provides only an early indication rather than definitive proof that diet can reverse aging. They say larger and longer studies are needed to determine whether these biological changes lower disease risk over time and whether the same effects occur in other age groups.

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Somewhere between the orbits of Mars and Jupiter, a giant metallic world drifts silently through deep space. Unlike ordinary rocky asteroids, 16 Psyche has captured global attention because scientists believe it may contain enormous quantities of valuable metals, including iron, nickel, platinum, and possibly more gold than has ever been mined on Earth. The asteroid’s estimated theoretical value has triggered headlines describing it as a “trillion-dollar asteroid” or even a “space treasure chest”. But for NASA, the real fascination is not simply wealth. Scientists believe Psyche could be the exposed core of an ancient lost planet, offering a rare glimpse into how worlds like Earth were formed billions of years ago.

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A new working paper by Philip Moreira Tomei and Bouke Klein Teeselink, posted to arXiv in early May, makes claims that, if correct, should reorient the workforce policy conversation. In short, the authors argue that the AI exposure indices that have shaped most current thinking are looking at an incomplete subset of digital work. They identify which jobs and tasks current language models can already accelerate but they miss the jobs with features that make them amenable to automation later.

Tomei and Klein Teeselink build a new index that scores all 17,951 task statements in the federal O*NET database. The authors propose a measure what they call “reinforcement learning feasibility” which asks whether a task has the structural features (e.g., verifiable outcomes, use environments amenable to simulation, discrete decision/feedback loops) that allow AI systems to be trained on it through the post-training methods that are becoming the main drivers of AI capability. They then compare their index to the most-cited existing measure, from Eloundou and colleagues, which looks at whether tasks can be automated with current technology.

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Mathematicians have calculated a “golden rule” for abstract art that famous artists tend to follow when they compose their works. Artificial intelligence, the team found, does not follow such implicit rules about shape placement, possibly explaining why computer-generated art doesn’t usually evoke awe from viewers.

Scientists and philosophers have long tried to decipher why art moves people: Are there underlying features shared among masterpieces? Do painters unconsciously use similar shapes, contours or compositions to elicit an emotional response? Many of the ways researchers have tried to categorize shapes or complexity in paintings are “arbitrary,” however, says Jacek Rogala, a neuroscientist at the University of Warsaw and co-senior author of the new study.

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Modern air and missile defense is approaching a structural limit. The model that protected forces over the past two decades remains effective, but only within a narrower envelope than current threats demand. A new approach is required, built on fire-control-level integration, disaggregated survivable architectures, affordable magazine depth, and the integration of offensive action as the central element of defense.

I am a retired U.S. Air Force brigadier general and now lead international business development and strategy for Northrop Grumman in Europe, North Africa, and the Middle East. I previously served as chief operating officer of DEFCON AI. As a defense industry executive, I have a direct commercial interest in the integration and command-and-control issues covered here. Northrop Grumman is the prime contractor for the Integrated Battle Command System, the U.S. Army program most closely associated with the fire-control-level integration concepts discussed, so readers should weigh that overlap most carefully in the procurement section, where my analytical argument and my employer’s commercial position are closest. The argument is not for my company’s solution specifically, but for any architecture or federated set of systems that can deliver sensor-shooter integration, disaggregation, survivability, and coalition interoperability.

The reason is simple: The threat has changed faster than the defensive architecture. Ballistic missiles, cruise missiles, one-way attack drones, and loitering munitions are no longer niche capabilities employed in small numbers. They are becoming routine instruments of coercion and war, used in combinations designed to overwhelm decision-making, exhaust magazines, expose seams between sensors and shooters, and force defenders into bad cost exchanges. Recent combat has shown that even capable defenses can perform well tactically while still revealing strategic fragility. It is time to invest in systems that are not just able to intercept threats, but do so at the scale, speed, cost, and survivability required for a sustained campaign.

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The ‘cloud-native’ architecture of the last decade is built on a 20-year-old assumption: that state
lives in the database, and compute is stateless. If you want to scale, you scale the database
vertically (get a larger machine) [1][1] or design the database schema around partition the data
and you scale your application servers horizontally (add more
boxes). Any request can hit any server, the loadbalancer doesn’t care, and the database is the
single source of truth.

LLMs and agents are quietly violating this assumption, and making this architecture increasingly
hard to work with. Not all at once, but in three subtle ways:

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For decades, scientists believed the Japanese population largely descended from two ancient groups: the Jomon hunter-gatherers who lived in the archipelago for thousands of years, and later migrants from East Asia who brought rice farming and new technologies to Japan.

But a major genetic analysis from researchers at RIKEN’s Center for Integrative Medical Sciences suggests the picture is far more complicated.

Using whole-genome sequencing on more than 3,200 people from across Japan, the team found evidence supporting a third ancestral group tied to northeastern Asia and possibly linked to the ancient Emishi people. The findings, published in Science Advances, add powerful support to the increasingly discussed “tripartite origins” theory of Japanese ancestry.

Immigrations and Customs Enforcement have been using a Palantir tool to track far more than illegal aliens, critics allege. ICE has over 20 million people worldwide in a database that some suspect includes American citizens.

DHS told 404 Media, “U.S. Immigration and Customs Enforcement is committed to achieving the nation’s mandate to clear the backlog of illegal aliens who pose a threat to the security of our communities. Like other law enforcement agencies, ICE employs various forms of technology while respecting civil liberties and privacy interests.”

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