IT/기술 · "SOLUTION" · 총 48건
필터 보기현재 지수
50.3
0 = 부정 우세
50 = 중립
100 = 긍정 우세
최근 7일 기준 83,454건을 분석한 결과, 뉴스 심리지수는 50.3(균형)입니다. 긍정 4,166건(5.0%)·중립 77,313건(92.6%)·부정 1,975건(2.4%)이며, 중립 비중이 뚜렷하게 높습니다. 성향 지수는 종합 14.7(중도 균형)입니다.
Uber AI Solutions pays up to $150 an hour, contractors said. The AI training work doesn't involve onboarding and hours can vary from week to week.
The Logitech G512 X 98 lets you swap between mechanical and analog switches in an attempt to achieve the best of both worlds. Unfortunately, its solution isn't as well thought-out as I'd hoped.
The company announced a deal with B2U Storage Solutions to repurpose the battery packs as Waymo pulls them off the road.
New graduates’ careers are unfolding in an era when AI is not optional. The most successful engineers treat artificial intelligence as leverage, not competition. Here are seven tips to help keep young professionals in demand no matter how quickly the field’s tools evolve. 1. Master the fundamentals first. AI tools can help you code, but you still need strong fundamentals in: Data structures and algorithms for problem-solving. Operating systems, databases, and networking for system-level understanding. Core programming languages such as C++, Java, and Python. AI can autocomplete syntax, but if you don’t understand how things work under the hood, you’re likely to struggle to debug or optimize. 2. Learn how to work with AI, not against it. The best engineers will not try to out-code AI. Instead, they will learn to: Write clear prompts to generate better code snippets. Review and debug AI-generated code for accuracy, performance, and security. Use AI for productivity boosts while still exercising judgment. Think of AI as a teammate. The real skill is knowing when to trust it and when not to. 3. Build projects that showcase end-to-end thinking. Employers increasingly look for engineers who can design and build systems, not just solve problems. Create projects that show you can: Define requirements clearly. Use AI tools responsibly within the workflow. Deliver a product that scales and is maintainable. 4. Sharpen your system design skills early. Even junior engineers are now asked questions about basic system design with AI. Expect to explain to prospective employers: How you would responsibly integrate AI into a system. How to design fallbacks when AI fails. How to ensure scalability and reliability. 5. Develop strong communication skills. Today’s engineers don’t just code in isolation. You will be expected to: Explain design choices to teammates and stakeholders. Document decisions clearly. Collaborate effectively in cross-functional teams. This is one area where AI cannot replace you. Clear communication is a career accelerant. 6. Stay curious and keep learning. The tech industry moves fast, and AI is accelerating that pace. Cultivate habits such as: Following industry news, blogs, and open-source projects. Experimenting with new AI tools, frameworks, and libraries. Engaging in communities such as GitHub, IEEE Collabratec, LinkedIn, and Medium. Employers value engineers who keep themselves sharp and relevant. 7. Think beyond coding. AI will increasingly handle routine coding tasks. The differentiators for you will be: Problem-framing: Can you take a vague idea and turn it into a solution? Architectural judgment: Can you design systems that scale and last? Ethical awareness: Can you spot risks in AI use and address them responsibly? For more career advice, subscribe to the IEEE Spectrum Career Alert Newsletter. The biweekly newsletter features the latest information on jobs, education, management, and the engineering workplace.
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.
So many AI-driven stock picks, so little profit.
Samsung Electronics unveiled a mockup of its HBM5 memory and a new heat-management technology at Computex 2026, signaling its ambition to regain momentum in the artificial intelligence memory race as competition with SK hynix intensifies. At the annual technology exhibition in Taiwan on Tuesday, Samsung showcased the planned architecture of its seventh-generation high-bandwidth memory, or HBM5, featuring a new thermal solution called Heat Path Block designed to improve heat dissipation in increa
Shares of Anant Raj surged as much as 4.6% to Rs 563.25 in Tuesday's trade after the company announced a landmark partnership with the Government of Haryana to accelerate the state's digital infrastructure buildout.The real estate and infrastructure developer has signed a Memorandum of Understanding (MoU) with the Haryana Enterprises Promotion Centre (HEPC), marking a significant step in its ambitions to expand its data centre and cloud services business.The agreement was formalized on June 1, 2026, during the launch of the "Make in Haryana Policy & Other Sectoral Policies" event, presided over by Haryana Chief Minister Nayab Singh Saini.Rs 25,000 crore investment planUnder the MoU, Anant Raj intends to invest around Rs 25,000 crore in building data centres and cloud infrastructure across Haryana. The move highlights the company's increasing emphasis on digital infrastructure as demand continues to grow for artificial intelligence (AI), cloud computing, and data storage solutions.The partnership framework involves several key government departments and agencies, including:Haryana Enterprises Promotion Centre (HEPC)Department of Information Technology, Electronics & CommunicationHaryana State Electronics Development CorporationCitizen Resources Information DepartmentDepartment of Industries & CommerceThe agreement is designed to support Anant Raj's expansion of its Digital Infrastructure Business, encompassing both data centre operations and cloud services. The Haryana government, through HEPC, has committed to providing facilitation support and ease-of-doing-business assistance to help fast-track the project.The company said the arrangement aims to foster long-term cooperation between the state government and Anant Raj, positioning Haryana as a major hub for next-generation digital infrastructure investments.Anant Raj clarified that the MoU does not involve any shareholding arrangement, special rights, equity issuance, or related-party transaction. The agreement is focused solely on enabling investment and operational expansion in the state.Share price performance and technical indicatorsOver the past three years, the stock has delivered strong returns, rallying nearly 254%. The company currently commands a market capitalization of approximately Rs 19,406 crore.From a technical perspective, the 14-day Relative Strength Index (RSI) stands at 61. An RSI reading below 30 typically indicates oversold conditions, while a reading above 70 suggests the stock may be overbought.The stock also exhibits strong bullish momentum, trading above all eight of its key Simple Moving Averages (SMAs), signaling a positive technical trend.(Disclaimer: Recommendations, suggestions, views and opinions given by the experts are their own. These do not represent the views of The Economic Times)
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.
Mike Schroepfer's Gigascale Capital has raised a large fund to back founders building climate-friendly solutions for the world's energy and material shortages.
I tried to explain OpenAI’s solution more clearly than OpenAI did.
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Hong Kong's legal professionals are uniquely positioned to bridge the gap between the different legal systems used in the city and Central Asia, according to the president of the Law Society of Hong Kong. Roden Tong will be part of Chief Executive John Lee's delegation to Kazakhstan and Uzbekistan. While Hong Kong practises common law under "One Country, Two Systems", most Central Asian jurisdictions follow civil law traditions. Speaking to RTHK ahead of the trip, Tong said Hong Kong's legal sector could play a "pivotal role" in facilitating investment between the two markets — pointing to a little-known common law enclave in the heart of Central Asia. He was referring to the Astana International Financial Centre (AIFC) in Kazakhstan that opened in 2018. "They adopt common law within the AIFC," Tong said. "That is quite very similar to Hong Kong." The AIFC features an independent court system whose judges are predominantly from the United Kingdom, creating a legal environment Tong described as "very equivalent to Hong Kong". The president revealed the Law Society has been building ties with the region since 2016, and signed a memorandum of understanding with the AIFC in 2022. "Hopefully during this delegation, on this occasion, we can further explore more business opportunities for the entire business sector," he said. Tong drew parallels with Dubai, where its international financial centre also operates under a common law system — a model Hong Kong legal professionals have already navigated successfully. For Central Asian companies looking to invest in Hong Kong and access the mainland Chinese market, Tong said the city's legal infrastructure offers several distinct advantages. Hong Kong's dual-language capability — English, Cantonese and Mandarin — provides certainty and predictability for international businesses, he said, particularly in dispute resolution, arbitration and mediation. Tong also pointed to the Mainland and Hong Kong Closer Economic Partnership Arrangement (Cepa), where overseas companies partnering with Hong Kong firms can adopt common law in the Greater Bay Area — complete with tax incentives. The recent establishment of the International Organisation for Mediation (IOMed) headquarters in Hong Kong adds another layer of appeal as well, Tong said. The Law Society recently met with Secretary for Financial Services and the Treasury Christopher Hui and IOMed Secretary-General Teresa Cheng to discuss creating a specialised mediation panel for commodities trading. "This is something that, if at the end of the day, there's any disputes or even in the contractual formulation... Hong Kong legal professionals can actually play this pivotal role," Tong said. Edited by Raymond Yeung
Google's CEO Sundar Pichai highlighted the escalating costs of AI, with companies depleting annual budgets by May due to heavy token usage. To combat this, Google unveiled Gemini 3.5 Flash, a cost-effective model promising significant savings. This new AI aims to boost efficiency in coding and agentic tasks, potentially saving enterprises over a billion dollars annually.
Discussion understood to concern delayed SaaS transformation project
Dell's shares surged 33% on Friday as the PC maker's blockbuster results showed that its growing focus on AI servers was helping it capitalize on the data center boom, making the company one of the biggest beneficiaries of the new technology.The company, whose AI servers are crucial components in the global AI infrastructure build-out, is set to add $68 billion to its market value of about $206 billion, if gains hold.A household name in the PC market, Dell has in recent years scaled up its AI hardware business. Dell's AI server revenue of $16.1 billion surpassed its PC unit's $14.6 billion in sales in the quarter.The company's infrastructure solutions segment, home to both traditional and AI-optimized servers as well as other storage, software and networking solutions, has consistently eclipsed PC business revenue in the past four quarters."We've been following Dell a long time and never seen anything like this. Not only do they get an "A" for execution, but you can make an argument that Dell is even the best way to play AI out there," Melius Research analysts said.Dell's outlook for "AI and traditional servers are still very conservative," as the firm has stronger prospects for selling CPU racks to AI cloud providers like CoreWeave and Nscale, the brokerage said.The blowout quarter lifted shares of server makers Super Micro Computer and Hewlett Packard Enterprise 16% and 12%, respectively, while Dell's PC rival HP also rose 8%.Hewlett Packard Enterprise, which reports results on Monday, has also been prioritizing higher-margin product orders. But it has a smaller server business compared with Dell.Dell Chief Operating Officer Jeff Clarke acknowledged the ongoing "supply constrained" environment, particularly concerning memory chips, but said that its customers were actively securing supply for extended periods.The company has banked on balanced price hikes as well as its scale and strong supplier relationships to wade through the memory crisis. Strong returns from its AI server business are also helping cushion the blow to margins from the soaring memory prices.HP, which focuses mostly on PCs and printers, reported 13.2% growth in its personal systemsdivision, while sales in Dell's PC business unit grew 17%, driven by a Windows 11 refresh cycle and growing focus on AI PCs.At least 13 brokerages raised their price targets on Dell stock following the results, giving it a median price target of $255, according to data compiled by LSEG. That is up from $170 before the report.Dell is on track to record its biggest one-day percentage gain if gains hold. It has a 12-month forward price-to-earnings ratio of 20.21, compared with HP's 8.39 and HPE's 14.70.
Shares of Netweb Technologies surged over 15% on Friday to hit their fresh 52-week high of Rs 4,680 on the NSE amid high volumes. The stock extended its gaining streak for the third session in a row, rising 21% in this period.The rally comes on the back of a ratings upgrade by CRISIL Ratings Limited. The company's Long-term rating has been upgraded to 'Crisil A+ / Stable'; while short-term rating reaffirmed to Crisil A1. Netweb offers computing solutions with fully integrated design and manufacturing capabilities. Its HCS offering comprises HPC, Private cloud and (HCI), AI systems and enterprise workstations, High performance storage (HPS) and Data Centre ServersCrisil Ratings believes NTIL will continue to benefit from the extensive experience of its promoters and established relationships with clients.The rating agency has also listed a slew of factors that will likely aid its growth. Among them are sustained revenue growth to over Rs 4,000 crore, with diversification across the end users earning steady operating margin at 13-14%, leading to higher-than-expected net cash accruals. Efficient working capital management leading to moderate dependence on debt and sustenance of healthy financial risk profile and liquidity will be another trigger according to CRISIL.It has also highlighted caveats that include the likelihood of decline in revenue below Rs 2,000 crores or fall in operating margin to below 11%, could lead to lower-than-expected net cash accrual. Meanwhile large, debt-funded capex or substantial increase in the working capital requirement, thus weakening the financial risk profile and liquidity.CRISIL shares have been market laggards, falling over 8% in 2026 while extending its decline to 24% over the past 12 months.Netweb Technologies reported Q4FY26 revenue from operations at Rs 774 crore, growing 87% year-on-year. Its operating EBITDA for Q4FY26 stood at Rs 97 crore while the adjusted operating EBITDA for Q4FY26 was Rs 102 crore, up 72% YoY, with a margin of 13.2%.(Disclaimer: Recommendations, suggestions, views and opinions given by the experts are their own. These do not represent the views of Economic Times)
Korean supply chain management software provider Emro is stepping up its expansion in North America and Europe as growing geopolitical uncertainty, reshoring trends and supply chain disruptions drive demand for AI-powered procurement solutions. The company said Friday its AI-based supplier relationship management platform, Caidentia, drew strong interest at Gartner Supply Chain Symposium/Xpo 2026, one of the world's largest supply chain conferences, held in Orlando and Barcelona in May. Develope
I have been an application-specific IC (ASIC) designer for almost three decades. Over that time, I’ve moved through the full academic trajectory, from graduate student to full professor; later, I transitioned to industry after an unsuccessful stint at entrepreneurship. When I made the switch to the private sector in 2019, I began focusing on a critically important aspect of the electronic industry: silicon intellectual property. As much as 80 percent of the physical area in today’s most advanced chips is occupied by blocks that aren’t made for specific products or even designed by the consumer-facing companies that built them. Instead, chipmakers draw heavily on established silicon IP from companies like Arm, Cadence, Rambus, Synopsys, and the company I work for, Silicon Creations. Throughout my career, I’ve designed chips for very different purposes, including enabling the research program in my academic lab and expanding the IP portfolio of my company. When I joined Silicon Creations, I had no idea how differently the industry approaches IC design and encountered a steep learning curve. Initially, it seemed that much of my two decades of academic research and training did not directly translate to the role. I had to learn new skills and adopt a new mindset. Today, demand for ASICs is rapidly growing, driven by the need for specialized chips in the automotive sector, AI applications, and more. By one market estimate, the ASIC market is expected to grow from US $23.4 billion to $38.8 billion by 2033, and the semiconductor industry as a whole is projected to hit $1 trillion by 2030. The industry needs more chip designers—but if you’re coming from an academic background as I did, there are a few things you’ll need to know. Different goals lead to different strategies The differences between industry and academe begin with a divergence in purpose. In academia, my primary objective was to generate new knowledge: to propose a novel circuit technique, validate an unconventional architecture, or explore the limits of performance in a given domain. A successful chip is one that demonstrates a concept. In industry, it is not nearly enough to prove that something can work. The goal is to ensure that it works reliably, repeatedly, and at scale. Success is measured not by novelty but by whether the silicon meets specifications, yields as expected in production, and supports a competitive product delivered on schedule. This leads to a stark contrast in risk tolerance. Academic designs often deliberately push into unproven territory, where even partial success can yield valuable insight. In industry, however, we systematically minimize risk. The cost of failure makes first-time silicon success a central requirement—especially at advanced technology nodes, where the lithography masks used to transfer circuit designs onto silicon wafers alone can cost tens of millions of dollars. As a result, industry design flows are built around eliminating uncertainty through conservative margins, extensive validation, and careful reuse of proven solutions. “Academia explores the design space, asking what is possible, while industry exploits it, determining what is viable at scale.” This paradigm has existed since the 1970s, when application-specific chip design was established. However, the gulf between academia and industry has expanded since the mid-2010s, when FinFET technology, a 3D architecture using vertical “fins” of silicon, was widely adopted in industry. System designs are also becoming increasingly modular with the advent of chiplets. This fundamentally altered the economics and complexity of ASIC development, with design costs rising by almost an order of magnitude. Initiatives like Taiwan Semiconductor Manufacturing Co.’s University FinFET Program and new government-funded chip-design hubs now let some well-resourced universities design for more advanced architectures, but the technology is still out of reach for many academics. What the industry-academia split means in practice Consider a startup developing an ASIC. Its engineering team may have deep expertise in a particular algorithm, sensor interface, or system architecture, the features that define its competitive advantage. But it is unlikely to possess world-class expertise in every supporting function. Developing each of these blocks internally would require significant time, capital, and specialized talent. Doing so could delay market entry beyond the startup’s viability. Even large semiconductor companies face similar constraints. Advanced-node development demands intense focus. Allocating a team to redesign a standard interface block that has already been implemented elsewhere may be difficult to justify when differentiation lies at the system level, such as an inference chip’s ability to speed up neural network computations. The time it takes to move a new chip from conception to market and risk mitigation, not self-sufficiency, govern most decisions about in-house development versus outsourcing. The economics of advanced IC manufacturing reinforce this reality. When the development cost of a leading-edge chip reaches hundreds of millions of dollars, minimizing risk becomes a central design imperative. In this context, silicon IP emerged as a practical solution. Similar to how software developers rely on preexisting libraries rather than writing every function from scratch, ASIC designers license predesigned, preverified silicon blocks—such as processor cores, memory interfaces, and security engines—from highly specialized IP vendors. These blocks can then be integrated into larger, increasingly complex systems. Design scope, verification, and time horizons With the use of silicon IP, industry is able to widen the scope of its designs. Academic efforts tend to focus on block-level innovation: a new analog-to-digital converter architecture or an ultralow-noise amplifier, for instance. These designs typically abstract away many of the complexities of bringing a chip to market, such as packaging constraints, long-term reliability, and manufacturing yield. In industry, the focus shifts to system-level integration. Modern systems on chips, or SoCs, incorporate dozens or even hundreds of functional blocks. Managing signal integrity, timing, firmware interaction, and system-level validation becomes as critical as the design of any individual block. Verification philosophy also diverges sharply. In academia, the goal of verification is to demonstrate that the concept works under nominal conditions, which may not always reflect how it would perform in real applications. Even if only a fraction of fabricated chips from a multiproject wafer operates correctly, the design may still be considered a success if it validates the underlying idea. At my academic lab for instance, we used to receive 40 chips from a TSMC prototyping service and started testing them in batches of five. If the first five or 10 chips proved functional, we had already collected more than enough data for a publication. If some of them failed, we weren’t required to mention this when publishing the results. In industry, verification is exhaustive, critical, and often dominates the development schedule. Failures are measured in parts per million, and even rare anomalies are carefully analyzed and documented to identify root causes and prevent recurrence. When I started at Silicon Creations, I was surprised by the level of detail and scrutiny designs face. Differences in time horizons and economic constraints reinforce each of these contrasts. Academic projects operate on flexible timelines aligned with research and funding cycles. If I missed a deadline, I just had to wait for the next cycle. Industry projects are driven by fixed product schedules and market windows, frequently targeting costly leading-edge nodes to achieve competitive performance, power, and area efficiency. Missing a deadline can negate the value of an entire design and may have major financial consequences along the entire supply chain. In essence, academia explores the design space, asking what is possible, while industry exploits it, determining what is viable at scale. Both are indispensable, but they operate under fundamentally different definitions of success. As ASIC complexity continues to grow, understanding both perspectives will be essential for the next generation of engineers navigating the evolving semiconductor landscape. This article appears in the June 2026 print issue.