"PROCESSED" · 총 49건
필터 보기현재 지수
50.3
0 = 부정 우세
50 = 중립
100 = 긍정 우세
최근 7일 기준 81,453건을 분석한 결과, 뉴스 심리지수는 50.2(균형)입니다. 긍정 3,988건(4.9%)·중립 75,539건(92.7%)·부정 1,926건(2.4%)이며, 중립 비중이 뚜렷하게 높습니다. 성향 지수는 종합 14.7(중도 균형)입니다.
A new policy is sparking concerns about a nightmare scenario that could force applicants to leave the country while their cases are processed.
Northern Mozambique has been absorbing what humanitarian groups call “multiple shocks” for years. Conflict, cyclones, cholera, displacement; each arriving before the last has been processed, each landing on a health system already buckling. What happens to people's minds in conditions like these? And who is there to help?
The Israeli Embassy in South Korea claimed Tuesday that Israeli forces had neither detained nor mistreated South Korean activists who were released last week after being captured aboard aid vessels bound for the Gaza Strip. In a statement, the embassy asserted that the two Korean citizens were not held in detention. "Upon their arrival at the port of Ashdod, the two individuals were processed immediately and deported through an expedited procedure. This further calls into question the allegation
Some Christians are turning to the Bible for dietary guidance, following a healthy nutrition plan that eliminates processed food and prioritizes whole foods.
Three months after attacking Iran, US President Donald Trump faces a bigger question: Is he losing the war? With Iran’s grip on the Strait of Hormuz, its resistance to nuclear concessions and its government largely intact, doubts are growing that Trump can translate the US military’s tactical successes into an outcome he can frame convincingly as a geopolitical win. His repeated claims of complete victory ring hollow, some analysts say, as the two sides teeter between uncertain diplomacy and his on-again-off-again threats to resume strikes, which would be sure to draw Iranian retaliation across the region. Trump is now at risk of seeing the US and its Gulf Arab allies emerge from the conflict worse off, while Iran, though battered militarily and economically, could end up with greater leverage, having shown it can throttle one-fifth of the world’s oil and gas supplies. The crisis is not yet over, and some experts leave open the possibility Trump might still find a face-saving way out if negotiations break in his favour. But others predict a grim post-war outlook for Trump. “We’re three months in, and it’s looking like a war that was designed to be a short-term romp for Trump is turning into a long-term strategic failure,” said Aaron David Miller, a former Middle East negotiator for Republican and Democratic administrations. For Trump, that matters, especially given his famous sensitivity to being perceived as a loser, an insult he has often lobbed at opponents. In the Iran crisis, he finds himself commander-in-chief of the world’s mightiest military pitted against a second-tier power seemingly convinced it has the upper hand. And this predicament could make Trump, who has yet to define a clear endgame, more likely to resist any compromise that looks like a retreat from his maximalist positions or a repetition of the 2015 Obama-era nuclear deal with Iran that he scrapped in his first term, analysts say. White House spokeswoman Olivia Wales said the US has “met or surpassed all of our military objectives in ‘Operation Epic Fury’”. “President Trump holds all the cards and wisely keeps all options on the table,” she added. Pressure and frustration Trump campaigned for a second term promising no unnecessary military interventions but has brought the US into an entanglement that could do lasting damage to his foreign policy record and credibility abroad. The continuing standoff comes as he faces domestic pressure over high US gasoline prices and low approval ratings after he embarked on the unpopular war ahead of November’s midterm elections. His Republican Party is struggling to maintain control of Congress. As a result, more than six weeks into a ceasefire, some analysts believe Trump faces a stark choice: to accept a potentially flawed deal as an off-ramp or escalate militarily and risk an even longer crisis. Among his options if diplomacy collapses, they say, would be to launch a round of sharp but limited strikes, frame it as a final victory and move on. Another possibility, analysts say, is that Trump could attempt to shift focus to Cuba, as he has suggested, in hopes of changing the subject and trying to score a potentially easier win. If so, he might end up misjudging the challenges posed by Havana, much as some Trump aides privately acknowledge that he mistakenly thought the Iran operation would resemble the January 3 raid that captured Venezuela’s president and led to his replacement. Even so, Trump is not without his defenders. Alexander Gray, a former senior adviser in Trump’s first term and now chief executive officer of the American Global Strategies consultancy, rejected the notion that the president’s Iran campaign was on the ropes. He said that the heavy blow to Iranian military capabilities was in itself a “strategic success,” that the war had drawn Gulf states closer to the US and away from China, and that the fate of Irans nuclear program was still to be determined. There are signs, however, of Trump’s frustration with his inability to control the narrative. He has torn into his critics and accused the news media of treason. The conflict has lasted twice the maximum six-week time-frame that Trump laid out when he joined with Israel in starting the war on February 28. Since then, though his MAGA political base has stood by him on the war, cracks have appeared in his once almost unanimous backing from Republican lawmakers. At the outset, waves of airstrikes quickly degraded Iran’s ballistic missile stockpile, sank much of its navy and killed many top leaders. But Tehran responded by blocking the strait, which sent energy prices soaring, and attacking Israel and Gulf neighbours. Trump then ordered a blockade of Iran’s ports but that has also failed to bend Tehran to his will. Iran’s leaders have matched Trump’s triumphalist claims with their own propaganda depicting his campaign as a “crushing defeat”, though it is clear that Iranian officials have overstated their own military prowess. Shifting goals still unachieved Trump had said his objectives in going to war were to close off Iran’s path to a nuclear weapon, end its ability to threaten the region and US interests, and make it easier for Iranians to overthrow their rulers. There is no sign that his often-shifting goals have been achieved, and many analysts say it is unlikely that they will be. Jonathan Panikoff, a former deputy national intelligence officer for the Middle East, said that while Iran has taken devastating hits, its rulers consider it a success simply to have survived the US assault and learned how much control they can exert over Gulf shipping. “What they discovered is they can exercise that leverage and with few consequences for them,” said Panikoff, now at the Atlantic Council think tank, adding that Iran appeared confident it could tolerate more economic pain than Trump and outlast him. Trump’s main stated war aims Iran’s denuclearisation also remains unfulfilled, and Tehran has shown little willingness to significantly rein in its programme. A stockpile of highly enriched uranium is believed to remain buried following US and Israeli airstrikes last June and could be recovered and further processed to bomb grade. Iran says it wants the US to recognise its right to enrich uranium for what it says are peaceful purposes. Some analysts have suggested that the war could make Iran more, not less, likely to ramp up efforts to develop a nuclear weapon to shield itself like nuclear-armed North Korea. Another of Trump’s declared goals — forcing Iran to halt support for armed proxy groups — also remains unmet. Adding to Trump’s challenges, he is now dealing with new Iranian leaders considered even more hardline than their predecessors. Post-war, they are widely expected still to have enough remaining missiles and drones to pose a continued danger to their neighbours. He is also facing fallout with further erosion of relations with traditional European allies, which have mostly refused his calls for assistance in a war they were not consulted about. China and Russia, meanwhile, have drawn lessons about the US military’s shortcomings against asymmetric Iranian tactics and how some of its weapons supplies have become depleted, analysts said. Robert Kagan, a senior fellow at the Brookings Institution think tank, has argued that the outcome will be even more of a decisive setback to US standing than its humiliating withdrawals from much longer, bloodier conflicts in Vietnam and Afghanistan because those countries were “far from the main theatres of global competition”. “There will be no return to the status quo ante, no ultimate American triumph that will undo or overcome the harm done,” he wrote in a recent commentary entitled Checkmate in Iran on the Atlantic magazine’s website.
Customers want their data kept and processed strictly within the EU
This sponsored article is brought to you by Applied Materials. At pivotal moments in history, progress has required more than individual brilliance. The most consequential breakthroughs — such as those achieved under the Human Genome Project — required a new operating paradigm: Concentrate the world’s best talent around a single mission, establish a common platform, share critical infrastructure, and collapse feedback loops. When stakes are high and timelines are compressed, sequential and siloed innovation simply cannot keep pace. Today’s AI era is creating an engineering race with similar demands. Every company is pushing to deliver higher-performance AI systems, faster. But performance is no longer defined by compute alone. AI workloads are increasingly dominated by the movement of data: In many cases, moving bits consumes as much — or more — energy than compute itself. As a result, reducing energy per bit can extend system‑level performance alongside gains in peak compute. The path to energy‑efficient AI therefore runs through system‑level engineering, spanning three tightly interconnected domains: Logic, where performance per watt depends on efficient transistor switching, low‑loss power, and signal delivery through dense wiring stacks. Memory, where surging bandwidth and capacity demands expose the memory wall, with processor capability advancing faster than memory access. Advanced packaging, where 3D integration, chiplet architectures, and high‑density interconnects bring compute and memory closer together — enabling system designs monolithic scaling can no longer sustain. These domains can no longer be optimized independently. Gains in logic efficiency stall without sufficient memory bandwidth. Advances in memory bandwidth fall short if packaging cannot deliver proximity within thermal and mechanical constraints. Packaging, in turn, is constrained by the precision of both front‑end device fabrication and back‑end integration processes. In the angstrom era, the hardest problems arise at the boundaries — between compute and memory in the package, front‑end and back‑end integration, and the tightly coupled process steps needed for precise 3D fabrication. And it is precisely this boundary‑driven complexity where the traditional innovation model breaks down. The Traditional R&D Workflow Is Too Slow for Angstrom‑Era AI For decades, the semiconductor industry’s R&D model has resembled a relay race. Capabilities are developed in one part of the ecosystem, handed off downstream through integration and manufacturing, evaluated by chip and system designers, and only then fed back for the next iteration. That model worked when progress was dominated by relatively modular steps that could be scaled independently and simply dropped into the manufacturing flow. But the AI timeline has upended these rules. At angstrom‑scale dimensions, the physics enforces inescapable coupling across the entire stack: materials choices shape integration schemes; integration defines design rules; design rules dictate power delivery; wiring sets thermal budgets; and thermals ultimately constrain packaging scaling. System architects simply cannot wait 10–15 years for each major semiconductor technology inflection to mature. Representing a roughly $5 billion investment, EPIC is the largest commitment to advanced semiconductor equipment R&D in U.S. history. A long‑term perspective is essential to align materials innovation with emerging device architectures — and to develop the tools and processes required to integrate both with manufacturable precision. At Applied Materials, together with our customers, we are charting a course across the next 3–4 generations, extending as far as 10 years down the roadmap. The angstrom era demands that we break down silos and bring together the industry’s best minds — from leading companies to leading academic institutions. If the problem is coupled, the solution must be coupled. If the timeline is compressed, the learning loop must be compressed. It’s not enough to just innovate — we must innovate how we innovate. EPIC: A Center and Platform for High‑Velocity Co‑Innovation This is the challenge that Applied Materials EPIC Center is designed to solve. Representing a roughly US $5 billion investment, EPIC is the largest commitment to advanced semiconductor equipment R&D in U.S. history. When it opens in 2026, it will deliver state‑of‑the‑art cleanroom capabilities built from the ground up to shorten the path from early‑stage research to full‑scale manufacturing. But the facilities are only one component of the model. EPIC is also a platform, an operating system for high-velocity co‑innovation that revolutionizes how ideas move from the lab to the fab. EPIC is a platform, an operating system for high-velocity co‑innovation that revolutionizes how ideas move from the lab to the fab.Applied Materials The EPIC model compresses the traditional workflow. Customer engineers work side‑by‑side with Applied technologists from day one — moving beyond isolated process optimization and downstream handoffs. Within a shared, secure environment, EPIC tightly integrates atomistic modeling, test vehicles, process development, validation, and metrology feedback. Constraints that once surfaced late in development are identified and addressed early. The result is a potentially 2x faster path that benefits the entire ecosystem under one roof: Chipmakers gain earlier access to Applied’s R&D portfolio, faster learning cycles, and accelerated transfer of next‑generation technologies into high‑volume manufacturing. Ecosystem partners gain earlier access to advanced manufacturing technology and collaboration opportunities that expand what is possible through materials innovation. Academic institutions gain opportunities to strengthen the lab‑to‑fab pipeline and help develop future semiconductor talent. Building on decades of co‑development, we are reinventing the innovation pipeline with our partners across logic, memory, and advanced packaging to deliver the next leap in energy‑efficient AI. Accelerating Advanced Logic Logic remains the engine of AI compute. In the angstrom era, however, system‑level gains are increasingly constrained by power and energy. Extending AI performance now depends on architectures that deliver more performance per watt — accelerating the move to 3D devices such as gate‑all‑around (GAA) transistors, which boost density within a compact footprint while preserving power efficiency. Architectures that deliver more performance per watt are accelerating the move to 3D devices such as gate‑all‑around (GAA) transistors, and further out, complementary FETs (CFETs), which push density scaling even more.Applied Materials These architectural shifts are unfolding at unprecedented scale, with the logic roadmap already extending beyond first‑generation GAA toward more advanced designs. One key example is GAA with backside power delivery, which relocates thick power lines to the backside of the wafer, reducing resistive losses and freeing front‑side routing for tighter logic cell integration. Another example brings adjacent GAA PMOS and NMOS transistors closer together while inserting a dielectric isolation wall between them to minimize electrical interference. Further out, complementary FETs (CFETs) push density scaling even more by stacking PMOS and NMOS devices directly atop one another. While these architectures deliver compelling gains in performance per watt and logic density without relying solely on tighter lithography, they significantly raise integration complexity. Manufacturing a single GAA device today can involve more than 2,000 tightly interdependent process steps. At the same time, wiring stacks continue to grow taller and denser to connect these advanced logic devices. Modern leading‑edge GPUs now in development pack more than 300 billion transistors into an area little larger than a postage stamp, interconnected by over 2,000 miles of wiring. Modern leading‑edge GPUs now in development pack more than 300 billion transistors into an area little larger than a postage stamp, interconnected by over 2,000 miles of wiring.Applied Materials At this level of complexity, the process steps used to create these precise 3D devices and wiring stacks cannot be optimized independently. Design and process must evolve in lockstep, and materials innovation and fabrication methods must advance alongside device architecture. EPIC’s co‑innovation model is designed to accelerate exactly this convergence — enabling logic compute to continue advancing the frontiers of AI at the pace the roadmap demands. Powering the Memory Roadmap At the same time, the AI computing era is fundamentally reshaping how data is generated, moved, and processed — making memory technologies, especially DRAM, central to delivering the energy‑efficient performance AI systems require. As models grow larger and more data‑hungry, the DRAM roadmap is shifting toward architectures that deliver higher density, greater bandwidth, and faster access per watt. At the DRAM cell level, AI performance requirements are driving a transition from 6F² buried‑channel array transistors (BCAT) to more compact 4F², and beyond that, architectures that move past what 2D scaling alone can deliver. Applied Materials At the DRAM cell level, this shift is driving a transition from 6F² buried‑channel array transistors (BCAT) to more compact 4F² architectures, which orient the transistor vertically to boost density and reduce chip area. Looking beyond 4F², sustaining gains in performance per watt will require moving past what 2D scaling alone can deliver. The industry is therefore turning to 3D DRAM, stacking memory cells vertically to add capacity within a constrained footprint. As these structures grow taller and aspect ratios intensify, high-mobility materials engineering in three dimensions becomes increasingly critical to performance and reliability. Beyond the memory cell array, another powerful lever for DRAM scaling is shrinking the peripheral circuitry, which includes logic transistors and interconnect wiring. One emerging approach places select periphery functions beneath the DRAM array by bonding two wafers — one optimized for the DRAM cells and the other for CMOS logic — using multiple wiring layers. Beyond the memory cell array, another powerful lever for DRAM scaling is shrinking the peripheral circuitry, which includes logic transistors and interconnect wiring.Applied Materials In parallel, DRAM performance is being extended by leveraging logic‑proven enhancers in the memory periphery. These include mobility boosters such as embedded silicon germanium and stress films, along with wiring upgrades like improved low‑k dielectrics and advanced copper interconnects. Memory manufacturers are also transitioning periphery transistors from planar devices to FinFET architectures, following the logic roadmap to further improve I/O speed. These valuable inflections are central to EPIC’s mission — where they can be co-developed and rapidly validated for next‑generation memory systems. Driving System Scaling With Advanced Packaging As data movement becomes the dominant energy cost in AI systems, advanced packaging has emerged as a critical lever for improving system‑level efficiency—shortening interconnect distances, increasing bandwidth density, and reducing the power required to move data between logic and memory. The rise of 3D packages such as high‑bandwidth memory (HBM) underscores why advanced packaging is becoming central to the AI era.Applied Materials High‑bandwidth memory (HBM) marks a major inflection along this path. By stacking DRAM dies — scaling to 16 layers and beyond — and placing memory much closer to the processor, HBM enables rapid access to ever‑larger working datasets. This delivers step‑function gains in both bandwidth and energy efficiency. More broadly, the rise of 3D packages such as HBM underscores why advanced packaging is becoming central to the AI era. Packaging now addresses system‑level constraints that logic and memory device scaling alone can no longer overcome. It also enables a move away from monolithic systems‑on‑chip toward chiplet‑based architectures, as AI workloads increasingly demand flexible designs that combine logic, memory, and specialized accelerators optimized for specific tasks. A vital technology powering this roadmap is hybrid bonding. With interconnect pitches approaching those of on‑chip wiring, conventional bumps and microbumps run into fundamental limits in density, power, and signal integrity. Hybrid bonding removes these barriers by allowing dramatically higher interconnect and I/O density, supporting a broad range of chiplet architectures — from memory stacking to tighter compute‑memory integration. EPIC tackles high‑value advanced‑packaging challenges through early, parallel co‑innovation across materials, integration, and manufacturing.Applied Materials As bonded structures like HBM stacks grow larger and more complex, warpage control, die placement, stack alignment, and thermal management become first‑order challenges. EPIC tackles these and other high‑value advanced‑packaging challenges through early, parallel co‑innovation across materials, integration, and manufacturing. Bringing It All Together Across logic, memory, and advanced packaging, our industry faces an ambitious roadmap that promises significant gains in energy efficiency for AI systems. But realizing that potential demands breakthrough materials innovation at a time when feature sizes are shrinking, interfaces are multiplying, and process interdependencies are escalating. These challenges cannot be solved on 10–15‑year timelines under the traditional relay‑race model. We must break down silos, align earlier across the ecosystem, and parallelize learning to keep pace with AI’s demands. In the AI era, progress will be defined by the speed at which lightbulb moments turn into manufacturing and commercialization reality. The only viable path forward is a new innovation model — and EPIC is how we are driving it.
The quote with IBIT ticker will be traded in US dollars per lot, with settlements processed in Russian rubles
He collected 49.4% of the votes after all of the ballots were processed