AI Research
What happens when humans clash with AI– and each other?

A search-and-rescue team aided by artificial intelligence scans a disaster area for a missing person. A human spotter in the air suggests shifting to a new area, and the AI assistant concurs, while a team member on the ground disagrees.
What happens next?
That is the kind of question that Christopher Flathmann of Clemson University is working to answer with a new research project. Flathmann, an assistant professor in the School of Computing, is focusing on how human beings and AI can best work together, including how to resolve conflict.
“The broad goal is to say, if we’re going to integrate an AI system into the workforce–into any team– we don’t want it to be at the cost of humans working together,” Flathmann said. “In fact, we wanted to bolster humans working together.”
The three-year project is funded with $400,000 from the Air Force Office of Scientific Research’s Young Investigator Program.
The program reserves funding for early-career investigators who show exceptional ability and promise for conducting basic research, marking Flathmann as a rising star in higher education.
His research is particularly timely, as the military and growing number of companies integrate AI into the workforce, he said.
“AI technology at this point is not something that is not nice to have– it’s going to become a requirement to handle these complex environments,” Flathmann said. “We can’t just have singular teams do singular missions anymore. Teams of teams have to work together, and large groups have to work together.”
Part of the project focuses on building and designing AI technology that helps preserve how human beings interact with each other, while part focuses on creating a training program to prepare humans to work with AI.
As part of the project, Flathmann and his team plan to have a general population of adults go through military-style search-and-rescue simulations and see how they interact with AI teammates.
They expect the findings to apply not only to the military but to broader questions about how to integrate AI into the workforce.
The research will give Flathmann’s students a chance to work in one of the world’s fastest-growing areas of study. Among them is Kwame André, a recent Clemson computer science graduate who is now a Ph.D. student in Flathmann’s lab.
“The speed that AI is developing– it is going to be integrated immediately,” André said. “So, when it’s integrated is it just going to harm relationships with people, or do we get in there and help mediate those relationships and help keep them together?”
It’s a crucial question Flathmann and André are working to resolve in favor of humans working together– as they have for millennia– but now with a new kind of help.
AI Research
3 Dominant Artificial Intelligence (AI) Stocks That I’m Buying Now and Planning to Hold Forever

The chip market powering AI is expected to expand significantly over the next five years.
The artificial intelligence (AI) arms race is still the prevailing theme in the market. Even though billions have been spent this year on record-setting data center capital expenditures, that number is projected to continue rising for the foreseeable future.
This benefits one industry in particular: semiconductors. These products account for a significant portion of the cost of a data center build, benefiting three companies (among many others) that appear to be great buys now: Nvidia (NVDA -2.78%), Taiwan Semiconductor Manufacturing (TSM 3.49%), and ASML Holding (ASML 3.75%).
Investors should consider buying all three of these stocks and holding them for the long term, as they’re poised to benefit significantly from the ongoing AI spending spree, which is far from complete.
Image source: Getty Images.
1. Nvidia
Because these three companies are close to their customers, they have a good idea of what spending is coming down the pipeline. One of the biggest revelations Nvidia revealed during its latest earnings call is that it expects the big four AI hyperscalers to spend around $600 billion on data center capital expenditures this year.
However, by 2030, worldwide data center capital expenditures are expected to reach $3 trillion to $4 trillion. That’s a massive jump from today’s record-setting spend, and all three of these investments are slated to rocket higher should that projection come true.
Nvidia is the most obvious benefactor, as it’s the closest to the end customer. It also has the best margins of the three, so this revenue growth will directly translate into increased profits. Nvidia’s graphics processing units (GPUs) have been the computing muscle behind the AI arms race since their inception, and the company’s continuous innovation in this field has kept it at the forefront.
The chipmaker estimates that it receives about 35% of the total spent on a data center, which positions it well if this $3 trillion to $4 trillion market emerges by the end of the decade.
2. Taiwan Semiconductor
Second on the list is Taiwan Semiconductor. Thisi is a chip foundry that fabricates other companies’ chips on their behalf. Nvidia uses TSMC chips, but so do other prominent tech companies, including Advanced Micro Devices, Broadcom, and Apple. This positions TSMC to be a long-term winner regardless of whose technologies are being widely deployed in data centers.
Additionally, it’s launching new technologies that will improve power consumption by its chips. Later this year, TSMC is slated to launch 2nm chips, which are expected to provide a 25% to 30% power consumption improvement over its 3nm chipset. Beyond that, it is working on a 1.6nm and 1.4nm node that offers a similar level of power consumption improvement.
Energy consumption is a growing concern as AI infrastructure expands, and TSMC’s innovations should help it maintain its position as the leading chip manufacturer.
3. ASML
None of TSMC’s chip technology would be possible without ASML’s machines. ASML manufactures extreme ultraviolet (EUV) lithography machines used to lay the tiny electrical traces on a chip. TSMC’s 2nm or 3nm terminology correlates to the distance between electrical traces on a chip, with its current 3nm chipset having a 3-nanometer spacing between traces.
This takes an incredibly specialized machine, and ASML is the only company in the world that has these capabilities. This gives ASML a technological monopoly in this industry, and anytime you hear of a new chip factory being built, you should immediately assume that ASML will see increased business as a result.
ASML is a great alternative pick in the chip space, and with the stock down around 30% from its all-time high at present, it makes for an excellent long-term value investment.
Keithen Drury has positions in ASML, Broadcom, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool has positions in and recommends ASML, Advanced Micro Devices, Apple, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool recommends Broadcom. The Motley Fool has a disclosure policy.
AI Research
Meet the Artificial Intelligence (AI) Stock With $368 Billion in Revenue Coming Down the Pipeline

Key Points
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A handful of big tech companies are set to spend over $300 billion building AI infrastructure this year.
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Demand for compute is growing just as fast as companies can stand up new servers.
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This giant has more commitments and is growing faster than almost everyone in the market.
- 10 stocks we like better than Microsoft ›
A handful of big tech companies are set to spend over $300 billion building AI infrastructure this year.
Demand for compute is growing just as fast as companies can stand up new servers.
This giant has more commitments and is growing faster than almost everyone in the market.
The artificial intelligence boom is only getting bigger, with just a handful of big tech companies on track to spend over $300 billion on AI infrastructure this year alone. Alphabet (NASDAQ: GOOG)(NASDAQ: GOOGL) recently bumped its capital expenditure outlook for the full year from $75 billion to $85 billion. Amazon (NASDAQ: AMZN) is on track to spend over $100 billion in capital expenditures, mostly going toward new data centers and servers to fill them. And Microsoft (NASDAQ: MSFT) is planning a whopping $10 billion of spending per month for the current quarter.
By far the biggest beneficiary from all that spending has been Nvidia (NASDAQ: NVDA). The chipmaker has seen its data center chip sales soar over the last few years, including a 56% jump in its most recent quarter. And demand doesn’t seem to be slowing down anytime soon, with analysts expecting revenue to grow nearly as much next year as this year (on an absolute basis).
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But another AI giant just disclosed it has $368 billion of contracted revenue, and it’s doing everything it can to keep up with the massive demand it’s seeing.
Image source: Getty Images.
Huge long-term commitments give this stock a massive runway
All three major cloud computing platforms disclose their backlog, or remaining performance obligations, and all three are seeing healthy growth.
- Alphabet said its Google Cloud backlog climbed to $108 billion last quarter, a 37% increase from a year ago.
- Amazon said its Amazon Web Services backlog totaled $195 billion, a 25% increase from a year ago.
- Microsoft revealed a $368 billion backlog last quarter, a 37% increase from last year.
Indeed, Microsoft is the AI giant with $368 billion coming down the pipeline.
There’s an important caveat about Microsoft’s remaining performance obligations. It includes contracts for commercial software and services like Microsoft 365 and its Azure cloud computing platform. As such, it’s not a perfect apples-to-apples comparison with Amazon or Alphabet. Still, the growth is impressive, and the metric Microsoft shares suggests Azure may be growing its commitments significantly faster than its two biggest rivals.
Importantly, Microsoft’s backlog growth is stemming from a growing number of long-term commitments. Microsoft said just 35% of those commitments will be recognized as revenue in the next 12 months, with the total increasing 21% year over year. The amount recognized beyond 12 months grew 49%. By comparison, Alphabet saw the percentage of commitments set to be recognized as revenue within 24 months drop from 55% to 50% last quarter. Amazon saw the average length of its long-term commitments get a slight bump from 3.9 years to 4 years.
That shift can skew just how much faster Azure is growing compared to its rivals. If Microsoft is extending the length of its contracts, it’ll naturally have a bigger backlog. Still, the long-term commitments put Microsoft in a position to generate strong growth for Azure for years to come. Management shared that Azure is now a $75 billion business, after exhibiting 39% year-over-year revenue growth last quarter. It expects 37% growth next quarter. That makes it roughly 50% larger than Google Cloud, but growing faster. And its massive backlog means it can continue outpacing the competition in the future.
Demand continues to outpace supply
Microsoft management has been telling investors for well over a year that demand for its cloud computing services, particularly its Azure AI services, is higher than its supply. That remained the case in the fourth quarter. To be sure, that’s not a situation unique to Microsoft. Both Amazon and Alphabet have made similar comments on their earnings calls.
But Microsoft is spending more than anyone building out its data centers. As mentioned, it committed to spending $30 billion on capex this quarter, and management refused to provide guidance on how much it might spend through the rest of fiscal 2026. But given the massive and rapidly growing backlog of demand for its AI services, investors should be happy to see Microsoft build as quickly as possible. It’s important to remember that Microsoft also holds a leading position as enterprises migrate more of their systems from on-premise to the cloud, specializing in hybrid cloud environments using Windows. As such, overbuilding shouldn’t be a huge concern.
Azure is the biggest growth driver for Microsoft right now, but it’s not the only one. As mentioned, that $368 billion backlog also includes commitments for Microsoft 365, Dynamics 365, and Microsoft’s other enterprise software and services. Those are getting a boost from AI as well, as Microsoft integrates its Copilot AI assistant into its software. That helps workers get more out of its products and increases productivity. As a result, Microsoft is able to charge more and gain bigger commitments from commercial customers.
Investors will have to pay a premium price to buy Microsoft stock. With a forward P/E ratio of 32, it trades for a much higher price than Alphabet, which sports a 23 multiple. It’s even approaching Amazon’s 34 times earnings multiple, despite the cloud computing leader historically trading for a much higher earnings multiple. But with a massive pipeline of long-term growth ahead for the company, it’s well worth paying up for.
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Adam Levy has positions in Alphabet, Amazon, and Microsoft. The Motley Fool has positions in and recommends Alphabet, Amazon, Microsoft, and Nvidia. The Motley Fool recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
AI Research
Artificial Intelligence For Video Surveillance Market

New Jersey, US State: “The global Artificial Intelligence For Video Surveillance market in the Information Technology and Telecom category is projected to reach USD 16.8 billion by 2031, growing at a CAGR of 11% from 2025 to 2031. With rising industrial adoption and continuous innovation in Information Technology and Telecom applications, the market is estimated to hit USD 6.5 billion in 2024, highlighting strong growth potential throughout the forecast period.”
Artificial Intelligence For Video Surveillance Market Size & Forecast 2033
The artificial intelligence for video surveillance market is expected to grow substantially by 2033, supported by rising demand for advanced security and monitoring solutions. AI-powered systems enhance surveillance by enabling real-time analytics, facial recognition, anomaly detection, and automated alerts. Increasing urbanization, smart city projects, and security concerns in public and private sectors are key drivers of adoption worldwide.
Technological innovations integrating AI with cloud storage, IoT devices, and edge computing are improving accuracy and scalability of surveillance systems. Vendors are focusing on developing customizable platforms for industries such as retail, transportation, and critical infrastructure. The emphasis on proactive threat detection and regulatory compliance is further boosting demand. By 2033, the AI for video surveillance market is forecast to reach robust global valuation, driven by continuous innovation and expanding applications across diverse sectors.
Key Players in the Artificial Intelligence For Video Surveillance Market
Hikvision
Dahua
Huawei
Cisco Meraki
Hanwha
ZTE
Honeywell Security
Simshine Intelligent Technology Co. Ltd.
For Further Detail, Download the Sample PDF with Complete TOC, Tables, Figures, Charts, And More @ https://www.marketresearchintellect.com/download-sample/?rid=1031128&utm_source=OpenprJune&utm_medium=023
Factors Supporting Growth of Artificial Intelligence For Video Surveillance Market in the Future:
1.Technological Advancements and Innovation:
The continuous evolution of technology is playing a vital role in driving the Artificial Intelligence For Video Surveillance market forward. Cutting-edge innovations are improving product functionality, enhancing performance, and reducing costs, making these solutions more accessible to a broader range of industries. Emerging technologies such as AI, IoT, advanced analytics, and automation are also enabling smarter and more efficient use cases, further expanding the scope of the market. These advancements are not only upgrading existing systems but are also creating entirely new application opportunities that will support long-term market expansion.
2. Expanding Applications Across End-Use Sectors:
The increasing integration of Artificial Intelligence For Video Surveillance solutions across diverse industries such as automotive, healthcare, consumer electronics, telecom, and industrial manufacturing is significantly boosting market demand. Each sector brings unique requirements, pushing companies to diversify their offerings and customize solutions. This cross-industry relevance ensures consistent demand growth, while rising digitalization and adoption of smart technologies amplify the market potential across both developed and developing regions.
3. Favorable Government Policies and Infrastructure Push:
Supportive initiatives by governments around the world, including funding programs, tax incentives, and policy frameworks, are providing a strong foundation for market development. Efforts to strengthen digital infrastructure, promote energy efficiency, and drive sustainable development are fueling demand for advanced Artificial Intelligence For Video Surveillance technologies. Moreover, public-private partnerships and national transformation agendas such as smart cities and Industry 4.0 are creating favorable conditions for rapid market expansion, especially in emerging economies
4. Increased Investment and Focus on Research & Development:
The Artificial Intelligence For Video Surveillance market is experiencing a surge in investment from both private and public entities, driven by the urgency to innovate and stay competitive. Companies are dedicating substantial resources to research and development to create next-generation products with higher efficiency, scalability, and environmental sustainability. Venture capital funding, mergers, acquisitions, and collaborations are also contributing to a dynamic ecosystem that fosters experimentation and accelerates commercialization of novel solutions, ensuring sustained market growth in the future.
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Key Segments Covered in Our Report: Artificial Intelligence For Video Surveillance Industry
Artificial Intelligence For Video Surveillance Market by Type
Software
Hardware
Artificial Intelligence For Video Surveillance Market by Application
Public & Government Infrastructure
Commercial
Residential
The Application segment showcases the industries and sectors that use Artificial Intelligence For Video Surveillance products for example Artificial Intelligence For Video Surveillance targeting healthcare and automotive industries etc. It also provides a perspective of the market rate of acceptance, usage of the products, and new applications that are paving the way for the future of the market.
Global Artificial Intelligence For Video Surveillance Market Regional Analysis
The Global Artificial Intelligence For Video Surveillance Market is examined in dimensions of regions, wherein each region has its own market growth, trends as well as dynamics. This section highlights on the detailed market performance, major shifts, and trends and underlying factors explaining growth in different places around the world.
North America: North America accounts for a large share of the Artificial Intelligence For Video Surveillance market which is a result of the developed technology, intense consumer market, and huge investments in the Artificial Intelligence For Video Surveillance industry. To add, the U.S. market also plays a crucial role as this economy is more concerned with innovation and was also one of the first to implement Artificial Intelligence For Video Surveillance products in its Artificial Intelligence For Video Surveillance sectors. The region is expected to see a gradual rise till 2031 and this is because of its reinforced infrastructure and existing regulation mechanisms.
Europe: Global has the fastest growing Artificial Intelligence For Video Surveillance market and is oriented around environmental protection, renewed efforts and environmental awareness. The market is dominated by countries like Germany, the UK, and France that have improved their technologies and have a strong industrial structure. Increased request for green solutions along with regulatory efforts are increasing demand in the market’s key areas such as Artificial Intelligence For Video Surveillance sectors.
Asia-Pacific: The growth potential in the Artificial Intelligence For Video Surveillance market is expected to be maximum for Asia-Pacific region. Increased maturation, urban migration as well as expanding middle class in China, India, and Japan and other developing economies are great constituents of market growth. Further, there is an increasing contribution to investments in the Artificial Intelligence For Video Surveillance sector which is increasing the demand for Artificial Intelligence For Video Surveillance regions-supplying throughout the area.
Rest of the World: Countries and areas like Latin America, Middle East & Africa have also been showing moderate Artificial Intelligence For Video Surveillance market growth. Although still developing, these markets are fueled by a fast increasing infrastructure, expending industrial activities and growing consumer demand for Artificial Intelligence For Video Surveillance goods. These regions pose great opportunities for the market players to tap into other sources of growth.
Frequently Asked Questions (FAQ) – Artificial Intelligence For Video Surveillance Market
Q1: What is the anticipated growth rate of the Global Artificial Intelligence For Video Surveillance Market?
A1: With a growth rate of CAGR of 11%, the Global Artificial Intelligence For Video Surveillance Market is anticipated to reach USD 16.8 billion by 2031. Industrial demand and innovation will lead it to reach USD 6.5 billion by 2024.
Q2: Which regions provide the highest growth opportunities for the Artificial Intelligence For Video Surveillance Market?
A2: Asia-Pacific is likely to provide the highest growth prospects based on speedy industrialization and infrastructure growth, followed by robust markets in Europe and North America.
Q3: Which are the primary drivers of market growth?
A3: The primary drivers are technology innovation, growing industrial applications, heightened government initiatives, and expanding use of Artificial Intelligence For Video Surveillance solutions in different industries.
Q4: What are the challenges faced by the Artificial Intelligence For Video Surveillance Market?
A4: The challenges are tight regulatory systems, high upfront capital expenditures, fragmentation of the market in the emerging markets, and geopolitical risks in some regions.
Q5: Which are the major players in the Global Artificial Intelligence For Video Surveillance Market?
A5: The market has a number of leading players with a focus on innovation, strategic alliances, and global expansion.
Q6: How does innovation influence the Artificial Intelligence For Video Surveillance Market?
A6: Market growth is driven by innovation, which enhances product efficiency, lowers costs, and facilitates new applications, making the overall market potential broader.
Q7: Which industries utilize Artificial Intelligence For Video Surveillance products mostly?
A7: Major industries include manufacturing, automotive, energy, electronics, and infrastructure, among others, where Artificial Intelligence For Video Surveillance solutions deliver operational efficiency and sustainability.
Q8: How is the market anticipated to change after 2031?
A8: Although projections beyond 2031 are uncertain, continued technological advancement and increasing industrial demand are expected to continue supporting long-run growth patterns.
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