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IT/기술
Tribute to Jiro Yamada, Automotive Artist (1960-2025) [video]
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IT/기술 · "TRIBUTE" · 총 24건
필터 보기현재 지수
50.3
0 = 부정 우세
50 = 중립
100 = 긍정 우세
최근 7일 기준 81,636건을 분석한 결과, 뉴스 심리지수는 50.2(균형)입니다. 긍정 3,988건(4.9%)·중립 75,721건(92.8%)·부정 1,927건(2.4%)이며, 중립 비중이 뚜렷하게 높습니다. 성향 지수는 종합 14.7(중도 균형)입니다.
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From birthday songs to hospice tributes, Suno is finding real-world uses for AI-generated music. Whether that translates into a sustainable multibillion-dollar business is less clear.
This sponsored article is brought to you by Black & Veatch. The biggest challenge facing utilities today isn’t what it seems. It’s not demand, even as load growth accelerates. It’s not extreme weather, even as “major events” become routine. It’s not cybersecurity, even as connections expand across the grid. The real challenge is this: Distribution systems were designed for a different reality. Long gone are the days of predictable demand, one-way power flow and isolated disruptions. At Black & Veatch, we see that leading utilities are no longer debating whether to modernize. They’re deciding how quickly they can do it, and how to do it at scale. Across grid modernization programs globally, three truths consistently emerge. They define what it takes to prepare the distribution system for what’s next: 1. Outage response is not a resilience strategy Resilience is being redefined in real time. A strategy centered on mobilizing crews and restoring service as quickly as possible is reactive, and increasingly insufficient. Resilience has to shift upstream into integrated system design. That starts with hardening. Stronger poles, undergrounding and structural upgrades all have a role, particularly in high-risk corridors. We’re also seeing meaningful gains from how the network is configured and how quickly it can respond without waiting on manual intervention. This is where distribution automation programs can change outcomes. Strategically placed reclosers, automated switches and fault indicators help contain disruptions before they spread. When combined with feeder reconfiguration and updated protection strategies, distribution automation investments allow utilities to set more aggressive recovery targets and achieve measurable reductions in outage duration and customer impact. 2. Future-readiness depends on DERs at scale Forecasting is less and less reliable. Only 19 percent of utilities report strong confidence in their ability to predict future load growth, according to the Black & Veatch 2025 Electric Report. Distributed Energy Resources (DERs) like solar, storage, EVs and behind-the-meter generation are exciting solutions; but they fundamentally change how the system operates. Power is no longer just delivered. It’s injected, stored and redirected in ways the system was never designed to manage. At scale, these challenges show up quickly — particularly on feeders where distributed generation is approaching or exceeding hosting capacity. Protection coordination becomes more difficult when fault current comes from multiple directions. Voltage becomes less predictable as generation fluctuates throughout the day. And planning models must now account for highly variable, location-specific behavior. Distribution modernization is fundamentally changing how the system is designed and operated so it can absorb disruption, manage bi-directional flows and respond in real time. Adapting to bi-directional power flow requires more than incremental updates. Leading utilities are responding by building flexibility into the system, moving beyond static assumptions toward dynamic hosting capacity and interconnection studies, planning that incorporates DER, EV adoption and localized load growth, and infrastructure aligned with the communications and control needed to manage it. 3. The edge must be intelligent, visible and secure As system stress and complexity increase, utilities need far greater visibility and control over the network. Historically, utilities relied on customer calls, Supervisory Control and Data Acquisition (SCADA) at the substation level and field crews to understand what was happening on the system. That model doesn’t hold up. You can’t effectively manage a system you can’t see. Plus, the most critical events are increasingly happening beyond the substation — on feeders, laterals, and at the edge where DER and customer behavior are interacting with the grid. Grid-edge technologies have become essential. Sensors, Advanced Metering Infrastructure (AMI) and automated switching provide the raw data and control needed to move from reactive to proactive operations. In more advanced deployments, utilities are creating centralized control environments that allow operators to see and manage the distribution system in near real time. That capability is enabled by: Advanced communications networks to form the backbone of real-time grid visibility Distribution Management System (DMS) and Outage Management System (OMS) to enable faster, more coordinated system response Analytics, AI and machine learning to improve situational awareness, anticipate system conditions, and support operational decision-making The same connectivity enabling this real-time visibility and control also introduces new vulnerabilities, blurring the line between physical and cyber risk, yet many utilities manage them separately. Only 22 percent have unified teams in place, even as threats continue to rise, including a 50 percent increase in substation attacks and growing exposure to malware and ransomware, according to the Black & Veatch 2025 Electric Report. Cybersecurity and resilient network design must be embedded into the architecture from the outset—not layered on after the fact. See what bolder vision looks like Distribution modernization is fundamentally changing how the system is designed and operated so it can absorb disruption, manage bi-directional flows and respond in real time. To learn about a successful program, check out Georgia Power’s recent grid modernization program. Black & Veatch partnered with the utility on large-scale infrastructure upgrades. The results? Outages are down 76 percent, restoration times have improved by more than 80 percent and communities across Georgia are powered by a grid built to meet the future head-on. When the state faced the most destructive storm in the company’s history, Hurricane Helene, Georgia Power deployed a rapid response team that utilized its “smart grid” and restored power to more than 1 million customers within days. A grid built to meet the future head-on—that’s the result of bolder vision.
Uber has implemented monthly usage caps of $1,500 per AI coding tool for its employees due to exceeding its AI budget. This move aims to responsibly manage the rising costs associated with AI adoption and experimentation across the company. The company previously reported that AI agents contributed to 10% of its code.
Nvidia CEO Jensen Huang is putting South Korea's physical AI potential in the spotlight, with robotics set to top the agenda during his planned visit to Seoul from Thursday. "I think that robotics is very important to Korea, and I hope to be able to contribute to robotics in Korea," Huang said during Nvidia's "Korea Partner Night," held for the first time on the sidelines of the Computex event in Taiwan on Tuesday. "We would always consider investments in Korea, (it has) such a great ecosystem,
Senator Bernie Sanders has introduced the American AI Sovereign Wealth Fund Act, proposing a one-time 50% tax on the stock of major AI firms. This aims to transfer control from Silicon Valley billionaires to the American public, arguing AI was built on 'stolen' data. The fund would grant public voting shares and eventually distribute dividends.
Wall Street stocks posted modest gains on Monday as investors watched developments in U.S.-Iran peace negotiations and cheered the unveiling of a new computer chip that promises to bring artificial intelligence to personal computing.Tech shares boosted the Nasdaq and the S&P 500 to their latest in a series of record closing highs.U.S. President Donald Trump said talks with Iran continue. Earlier, Iran's news agency announced Tehran is halting indirect negotiations with Washington after a new round of strikes threatened to derail diplomatic efforts to end the war, now in its fourth month.The intensification of hostilities sent crude prices jumping, along with worries over the extent to which a protracted war could result in heightened, intransitory inflation."We don't really know where things stand," said Thomas Martin, senior portfolio manager at GLOBALT in Atlanta. "The market seems to think that something's going to get done at some point, but we don't have very good information to go on, like what the Iranians really want and what Trump is willing to settle for."Stocks added to their gains after Trump said no Israeli troops would go into Beirut, citing a call with Israeli Prime Minister Benjamin Netanyahu.Nvidia jumped after the company unveiled a new chip that puts AI capabilities directly into personal computers.The chip is the result of a three-year partnership with Microsoft to "reinvent the PC" for the AI era, Nvidia CEO Jensen Huang said. Microsoft shares rose.The reaction among semiconductor stocks was mixed. Qualcomm tumbled and while Intel also fell. Micron shares rose sharply, breaching the $1,000 mark for the first time.The Philadelphia SE Semiconductor Index advanced.In economic news, U.S. factory activity expanded in May for the fifth consecutive month as goods-makers navigate tariff and geopolitical crosswinds.Investors will turn to Friday's jobs report ahead of Kevin Warsh's debut policy meeting as chairman of the U.S. Federal Reserve this month, amid fears of rising inflation linked to the Iran war that could upend the stock market rally.According to preliminary data, the S&P 500 gained 20.19 points, or 0.27%, to end at 7,600.03 points, while the Nasdaq Composite gained 114.75 points, or 0.43%, to 27,087.37. The Dow Jones Industrial Average rose 44.70 points, or 0.09%, to 51,076.85.Software stocks rebounded from heavy selling earlier this year on AI disruption fears. ServiceNow and IBM rose sharply. The software services index advanced."On the software side, companies that hadn't been doing very well, but now are doing well today," Martin added. "Some of that has been attributed to Nvidia comments that software is part of the solution, so the market's coming back to" software stocks.Cadence Design Systems jumped after launching an Nvidia-powered AI agent for chip design.Broadcom's earnings, due on Wednesday, will be closely parsed in the wake of solid results from Dell last week, which signaled strong AI server demand.
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Lady Ramsay's 22-year career saw her become the most senior officer in MI6 and take part in the 1985 extraction of KGB double agent Oleg Gordievsky from the Soviet Union.
Anthropic PBC raised $65 billion in a funding round that valued the artificial intelligence company at $965 billion including the new investment, eclipsing rival OpenAI’s value for the first time.The funding, announced Thursday, was led by Altimeter Capital, Dragoneer, Greenoaks and Sequoia Capital. Each of the lead investors put in more than $2 billion, according to people familiar with the matter. Sequoia declined to comment. The other three firms did not respond to a request for comment.Alphabet Inc.’s Google contributed several billion dollars to the round as part of a previously announced commitment to invest up to $40 billion in Anthropic over time, according to people familiar with the matter. Amazon.com Inc. invested $5 billion in the round, also as part of a prior commitment, Anthropic said in a blog post.Google declined to comment. Micron Technology Inc., Samsung Electronics Co. and SK Hynix Inc. also contributed an undisclosed amount, helping to push the round well above Anthropic’s initial $30 billion target.The large round came together in a matter of weeks, a sign of strong investor demand for the Claude maker. In late April, Anthropic had been weighing whether to pursue new financing at a more than $900 billion valuation after receiving several inbound proposals, Bloomberg News has reported. The artificial intelligence startup then kicked off advanced discussions earlier this month.Founded in 2021 by a group of former OpenAI employees, Anthropic has since emerged as a leader in the AI sector. Anthropic has developed a series of AI tools aimed at overhauling the way businesses handle tasks from coding to cybersecurity. Anthropic and OpenAI are both expected to go public as soon as this fall, Bloomberg News has reported. Anthropic is still expected to proceed with an IPO on that timeline after the latest funding, one person said.Anthropic declined to comment.Anthropic expects to post $10.9 billion in revenue for the second quarter, more than doubling from the prior three-month period as demand surges for its AI software, Bloomberg News has reported. The company is also on pace for its first profitable quarter.The company has told investors that its annualized run rate revenue will surpass $50 billion by the end of next month, people familiar with the matter said. Anthropic’s run rate, a metric that projects full-year revenue based on sales from a shorter period, was $4 billion in July of last year.OpenAI was most recently valued at $852 billion in a funding round completed in March. The company is expected to confidentially file draft paperwork to go public in the coming days or weeks.
A number of companies, including Snap, Coinbase, and Wix, have attributed recent staff reductions to AI.
Experimental build boots on Raspberry Pi 5, but for now the joy is mostly in getting there
More than €20 million was lost in investment frauds last year.
The scheme now extends from April 2026 to March 2031 and aims to modernize country’s PDS, which distributes subsidised food grains through ration shops
G. Viswanathan said that the scheme aimed to support high-achieving students from rural government schools who secure excellent marks in higher secondary examinations but lack the financial means to pursue further education
Tamil Nadu Legislative Assembly Speaker J.C.D. Prabhakar paid tributes to former Speaker Si.Pa. Adithanar in Chennai on the late leader’s death anniversary on May 24, 2026
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Pokrovsky's work contributed to the identification of “patient zero” in the Soviet Union’s first HIV outbreak and helped establish the methodology for a nationwide network of AIDS prevention and treatment centers.
This sponsored article is brought to you by Wetour Robotics. A field technician on a wind turbine, harness clipped, both hands on a wrench, needs to send a command to the diagnostic device hanging at her belt. A logistics worker on a loading dock, gloves on, eyes on the pallet, needs to redirect a connected lift. A person using an assistive mobility device on a crowded street wants to nudge it forward without taking out a phone or speaking aloud. None of these moments call for a smarter robot. They call for a smarter way to be heard by the machines that already exist. The industry has been building from one side The past three years of Physical AI have been a story of remarkable progress on the robot side of the loop. Companies like Boston Dynamics, Figure, and Unitree have advanced actuators, locomotion, and dexterity to a level that would have seemed implausible a decade ago. Google DeepMind’s Gemini Robotics has redefined what vision-language-action models can do in unstructured settings. The trajectory of the hardware and the foundation models is real, and it is accelerating. But there is another side to this loop, and it has been treated as a solved problem for too long. The interface between humans and machines has defaulted, for 40 years, to three input modalities: screens, buttons, and voice. Each of those assumes the user can stop, look down, and translate intent into structured commands. That assumption breaks the moment the work moves into a real environment. On a turbine. On a dock. On a sidewalk. In any setting where hands are occupied, eyes are committed, or speaking is impractical, the conventional interface stack quietly fails. Spatial Intent Fusion is the simultaneous processing of three streams of human-centered information, namely spatial position, visual context, and gestural intent: Your body is the interface. The bottleneck on the human side of the loop is becoming as important as the one on the machine side. And solving it requires a different question. Not how do we make the robot more capable, but how do we let the human participate in the computing system as naturally as the robot already does. Wetour Robotics’ bet: put the human back into the computing loop Wetour Robotics is betting that the next architectural leap in Physical AI is not about making the robot more capable. It is about making the human a first-class node in the computing network, with the same kind of low-latency, high-fidelity participation that connected devices already enjoy. Wetour Robotics’ engineers frame the problem this way: a wristband that recognizes a gesture is not enough. A camera that recognizes a scene is not enough. The information a human carries about what they are about to do is distributed across multiple channels, including where their body is in space, what their eyes are attending to, and what their muscles are preparing to do, and any single channel observed in isolation is ambiguous. Reconstructing intent reliably means fusing those channels at the operating system level, with latency low enough that the loop feels closed rather than mediated. This approach has a name. Wetour Robotics calls it Spatial Intent Fusion: the simultaneous processing of three streams of human-centered information, namely spatial position, visual context, and gestural intent, fused into a single real-time command for any connected physical device. It is the technical implementation behind a simpler positioning statement the company uses externally: your body is the interface. Orchestra is a portable intelligent hub running the operating system that handles sensor fusion, intent inference, command translation, and safety arbitration. The reference compute platform is NVIDIA Jetson Orin Nano Super, which provides enough on-device inference capacity to keep the entire control loop at the edge, with no cloud dependency on the critical path. Wetour Robotics The architecture: three layers, four engines, one loop Orchestra is not a single device but a layered platform, designed from the start to be sensor-flexible and actuator-agnostic. The architecture decomposes into three perception layers and four coordination engines. Orchestra itself is the local compute and orchestration core: a portable intelligent hub running the operating system that handles sensor fusion, intent inference, command translation, and safety arbitration. The reference compute platform is NVIDIA Jetson Orin Nano Super, which provides enough on-device inference capacity to keep the entire control loop at the edge, with no cloud dependency on the critical path. Edge inference is non-negotiable for this application. Full-chain latency from biosignal acquisition to actuator command is held under 100 milliseconds, the envelope inside which closed-loop control feels natural rather than laggy. VisionLink handles visual and spatial perception. Cameras feed into vision models that identify objects, estimate distances, and track environmental context. VisionLink is designed not as a passive recognition layer but as a real-time command generator: its outputs feed directly into Orchestra OS to be fused with biosignal data. Conductor is the biosignal pipeline. It ingests raw surface electromyographic (sEMG) data from a wrist-worn device, classifies temporal patterns into discrete gestures or continuous control signals, and outputs actuator commands. The technically interesting property of sEMG for this use case is that the signal precedes visible motion. Motor unit action potentials appear at the skin surface roughly 50 to 80 milliseconds before a finger completes the corresponding gesture. Wetour Robotics calls this property pre-motion intent sensing, and it is what allows Orchestra to anticipate user intent rather than react to it. On top of the three perception layers, Orchestra OS runs four coordination engines. The Perception Engine ingests and normalizes raw sensor streams. The Intent Engine performs Spatial Intent Fusion across modalities, resolving what the user is trying to do given where they are, what they are looking at, and what their hand is signaling. The Orchestration Engine translates intent into device-specific command sequences for any connected actuator. The Safety Engine arbitrates conflicting commands, enforces operational envelopes, and gates execution against runtime safety conditions. Wetour Robotics The trade-offs we’re honest about No system that bridges the human body and the digital world is finished. Three engineering challenges remain open, and the company addresses each with a deliberate trade-off rather than a claim of having fully solved it. Baseline stability of sEMG under motion. In a stationary user, continuous gesture recognition from sEMG is reliable. Once the user is walking, climbing, or otherwise moving, motion artifacts and electrode drift degrade the signal in ways that are difficult to fully compensate for. Rather than overpromise on continuous control in dynamic settings, Orchestra defaults to a smaller set of robust discrete gestures in complex operating environments, and reserves continuous control modes for contexts where the signal-to-noise ratio supports them. Miniaturization of edge AI compute. Running the Orchestra control loop entirely at the edge requires real on-device inference, which has historically meant trading off between compute capacity, battery life, and form factor. Wetour Robotics’ approach has been a compact carrier board paired with a thermal design and a battery module sized for all-day wearability. The result is a hub that travels with the user rather than tethering them to a desk, and that performs the full perception-to-actuation loop without offloading to the cloud. Heterogeneity of third-party device protocols. The actuator side of the loop is a fragmented landscape. Different manufacturers expose different command interfaces, different communication stacks, and different safety conventions, and a Physical AI operating system has to integrate with all of them. Wetour Robotics uses an AI-agent layer to negotiate connection and protocol translation adaptively, so that Orchestra OS can ingest data from a wide range of devices, run them through neural network models that infer human intent, and emit the right command on the right protocol for the device on the other end. Why this matters, and why it helps the rest of the field The history of computing is a history of interface revolutions. Command lines gave way to graphical user interfaces, which gave way to touch, which gave way to voice. Each transition expanded who could participate in the system and what they could do with it. The next transition is not about a new screen or a new microphone. It is about treating the human body itself as a participant in the computing network, capable of contributing intent at the same speed and fidelity that any other connected node can. The history of computing is a history of interface revolutions. The next transition is not about a new screen or a new microphone — it is about treating the human body itself as a participant in the computing network. This path is not a competitor to the work being done on humanoid robots, foundation models for embodied AI, and dexterous manipulation. It is the missing complement to that work. The hardest open problem for humanoid systems is the data: every natural interaction between a human and the physical world is a potential training signal, and most of those interactions are currently invisible to any computing system. As more humans become first-class nodes in the loop, those interactions become observable, structured, and ultimately useful for training the next generation of embodied AI, including the humanoid robots being developed today. In other words: putting the human back into the computing loop is not just about better interfaces for individual users. It is about generating the kind of grounded, in-the-wild human-machine interaction data that the broader Physical AI ecosystem will need to keep advancing. The robot side and the human side of the loop are not two competing futures. They are two halves of the same one. That is what Wetour Robotics means when it says: Your body is the interface. Learn more at wetourrobotics.com.
In a press release, the AIADMK attributed to the victory of 53 candidates put up by the party and its allies in the recent election to Mr. Palaniswami’s State-wide campaign. However, it did not mention the number of district secretaries who attended the meeting, as against the total of 82