#GPU Market Growth

[pricedaniel238]

GPU for AI market: Innovations, Trends, and Future Opportunities and Forecast 2023-2032

The Graphics Processing Unit (GPU) market has become a central pillar of the rapidly expanding artificial intelligence (AI) ecosystem. As AI applications permeate industries ranging from healthcare and finance to autonomous vehicles and entertainment, the demand for advanced GPUs continues to skyrocket. GPUs, with their parallel processing capabilities, have proven essential for handling the…

[delightfullyatomiccollector-blog]

https://www.whatech.com/og/markets-research/industrial/918932-data-center-gpu-market-growth-in-the-us-opportunities-and-industry-analysis-from-2023-to-2028.html

Accelerating AI workloads and driving the demand for GPUs across US data centers to support cloud services, machine learning, and high-performance computing applications.

The US data center GPU market is growing at a very high rate. Its growth is attributed to the accelerated adoption of AI, ML, and HPC in several sectors.

[semiconductorsandelectronics]

Data Center GPU Market Size & Growth

[259 Pages Report] The data center GPU market size was valued at USD 14.3 billion in 2023 and is estimated to reach USD 63.0 billion by 2028, growing at a CAGR of 34.6% during the forecast period.

[thatstormygeek]

What we're witnessing is the American tech industry's greatest act of hubris — a monument to the barely-conscious stewards of so-called "innovation," incapable of breaking the kayfabe of "competition" where everybody makes the same products, charges about the same amount, and mostly "innovates" in the same direction.

Fat, happy and lazy, and most of all, oblivious, America's most powerful tech companies sat back and built bigger, messier models powered by sprawling data centers and billions of dollars of NVIDIA GPUs, a bacchanalia of spending that strains our energy grid and depletes our water reserves without, it appears, much consideration of whether an alternative was possible. I refuse to believe that none of these companies could've done this — which means they either chose not to, or were so utterly myopic, so excited to burn so much money and so many parts of the Earth in pursuit of further growth, that they didn't think to try. This isn't about China — it's so much fucking easier if we let it be about China — it's about how the American tech industry is incurious, lazy, entitled, directionless and irresponsible. OpenAi and Anthropic are the antithesis of Silicon Valley. They are incumbents, public companies wearing startup suits, unwilling to take on real challenges, more focused on optics and marketing than they are on solving problems, even the problems that they themselves created with their large language models. By making this "about China" we ignore the root of the problem — that the American tech industry is no longer interested in making good software that helps people.

To be clear, if the alternative is that all of these companies simply didn't come up with this idea, that in and of itself is a damning indictment of the valley. Was nobody thinking about this stuff? If they were, why didn't Sam Altman, or Dario Amodei, or Satya Nadella, or anyone else put serious resources into efficiency? Was it because there was no reason to? Was it because there was, if we're honest, no real competition between any of these companies? Did anybody try anything other than throwing as much compute and training data at the model as possible? It's all so cynical and antithetical to innovation itself. Surely if any of this shit mattered — if generative AI truly was valid and viable in the eyes of these companies — they would have actively worked to do something like DeepSeek.

[awesome-casuallyfamouscollector]

“Musk is also engaging in rampant ‘resource tunnelling’. That is to say, he’s doing his best to strip out the valuable parts of Tesla and redirect them to areas that he personally controls. The most recent example is his conflict of interest in AI. With him putting off Tesla acquiring GPUs so that his private AI company could have them. Another example is with the Twitter takeover. He pushed as many of the engineers at Twitter to quit as he could, then backfilled the gap by pulling over a bunch of Tesla software engineers on a temporary basis. Oh, and he broke his on rule and suddenly began advertising on Twitter/X.

P.S. Tesla starts to stagnate: arrogance, high price vehicles poorly suited for mass market is the main reason why growth rate is slowing...! Despite all the fuss made by the media, Tesla is still a niche product, intended only for the production of toy cars for the rich...

In 2025, the global electric car market will see the arrival of several electric car models that are much more suitable, more practical and more affordable for the average car user...but this market is already quite saturated with expensive electric cars and the increase in the number of buyers there will be negligible....

[rthidden]

The Golden Era of AI: Small Business Owners, It's Your Time!

Now is the moment for small business owners to embrace the world of AI, turning data overload into dazzling opportunities for growth!

1. Data is Your Secret Sauce

Data is the fuel that powers AI, and today, we're swimming in an ocean of it! With billions of messages shared on platforms like WhatsApp and countless videos on YouTube, this data is ripe for the picking. Here’s how you can leverage it:

Understand Customer Behavior: Use data analytics tools to extract insights about your customers’ preferences and behaviors.

Tailor Marketing Strategies: Customize your marketing campaigns based on data-driven insights, leading to higher engagement rates.

Make Informed Decisions: Data helps you make decisions backed by facts rather than guessing. The more informed you are, the stronger your business decisions will be.

2. Power in Your Pocket

Believe it or not, the computing power you can access today dwarfs that of a government supercomputer from 20 years ago! With powerful GPUs available for just $2,000, you can get your hands on technology that was once only available to the elite. Here’s how to use that power:

Affordable AI Development: Harness this technology to kickstart your AI projects without breaking the bank.

Experiment with Neural Networks: With the processing power at your disposal, you can launch simple AI projects that enhance customer service or automate tasks.

Stay Agile: Rapid access to computing power allows you to pivot quickly and respond to market changes effectively.

3. Democratizing AI: You Can Do It!

The beauty of today's AI landscape is that building AI isn't just for tech giants. It’s democratic! You can dive into AI without needing a huge budget:

Start Small: Begin with straightforward AI tools and platforms that don’t require coding knowledge.

Explore Online Resources: Use free resources and online courses to get a grounding in AI concepts—platforms like Coursera or Udacity have various options.

Community Engagement: Join local or online tech communities focusing on AI. Networking can provide invaluable insights and support as you embark on your AI journey.

4. Invest in the Future

AI isn’t a passing trend; it’s the future of business. Investing in AI can transform your operation from the ground up:

Boost Efficiency: Automate mundane tasks, allowing your team to focus on higher-value work.

Enhance Customer Experience: Implement chatbots or recommendation systems that cater specifically to your customers, making their interactions seamless.

Future-Proof Your Business: Being an early adopter of AI can set you apart in the marketplace, giving your business a competitive edge.

In this golden era of AI, small business owners have an unprecedented opportunity to harness the power of data and computing. Dive in, explore, and include AI in your business strategy now!

Are you excited to jump on the AI bandwagon? Share your thoughts or experiences in the comments below—we’d love to hear how you intend to implement AI in your business!

[matalanero]

long post ahead explaining my point of view ->

So, I wanted to contribute my way of seeing this discusion because I think most people (knowingly or not) are kind of mistaken on how long this will take to make mainstream. Firstly, AI hardware acceleration is something that exists and it's been in the works for some time now. As AI is being sold for the end user (probably will be part of the "gaming" marketing), more and more CPUs will be capable of processing this kind of features in any OS.

The problem isn't that almost no hardware can run it now, the problem is how long will it take to make potent-enough motherboards that microsoft could use (maybe not optimally, but could use) for this kind of purposes. The answer to that may vary, as developing an architecture of a new kind of chip (it could be an AI GPU of sorts or it could be an integrated processing chip apart from de CPU, in the latter you could not control the feature being in your PC unless you avoid buying specific hardware) takes many months or years.

The main issue here is microsoft adding yet another part of their OS where you are pushed to "opt out" if you meet the hardware requeriments (a little reminder here, on propietary OSes you don't know how that "opt out" button works and have to believe Microsoft's word on its functionality) wich, yeah, are very high and almost unobtainable RIGHT NOW, but will be acceptable in not that much time.

Microsoft is building its product as a money making aberration independently of the license you have to pay to use it. This is probably part of the trend of endless growth that many enterprises are obsessed with, and it will only get worse.

Software is malleable, maybe recalls are very expensive right now, but other similar smaller features can and will be implemented in many mainstream OSes as part of the AI crazy frenzy.

And, before ending this reminder, I will like to point to the fact that Microsoft is forcing many of its users to upgrade hardware only to be able to switch to W11, making it a possibility that they will make you buy Intel or AMD chips with AI hardware capabilities when W10 reaches EOL.

So, TLDR: The fact that PCs aren't capable right now to execute this kind of features or the fact that Microsoft lets you push a software button doesn't necessarily mean you are free from features out of your control. Hardware will get better and you cannot be sure it won't be part of your motherboard unless you know what you are buying, wich many people don't.

[global-research-report]

The Future of White Box Servers: Market Outlook, Growth Trends, and Forecasts

The global white box server market size is estimated to reach USD 44.81 billion by 2030, according to a new study by Grand View Research, Inc., progressing at a CAGR of 16.2% during the forecast period. Increasing adoption of open source platforms such as Open Compute Project and Project Scorpio coupled with surging demand for micro-servers and containerization of data centers is expected to stoke the growth of the market. Spiraling demand for low-cost servers, higher uptime, and a high degree of customization and flexibility in hardware design are likely to propel the market over the forecast period.

A white box server can be considered as a customized server built either by assembling commercial off-the-shelf components or unbranded products supplied by Original Design Manufacturers (ODM) such as Supermicro; Quanta Computers; Inventec; and Hon Hai Precision Industry Company Inc. These servers are easier to design for custom business requirements and can offer improved functionality at a relatively cheaper cost, meeting an organization’s operational needs.

Evolving business needs of major cloud service and digital platform providers such as AWS, Google, Microsoft Azure, and Facebook are leading to increased adoption of white box servers. Low cost, varying levels of flexibility in server design, ease of deployment, and increasing need for server virtualization are poised to stir up the adoption of white box servers among enterprises.

Data Analytics and cloud adoption with increased server applications for processing workloads aided by cross-platform support in a distributed environment is also projected to augment the market. Open Infrastructure conducive to software-defined operations and housing servers, storage, and networking products will accentuate the market for storage and networking products during the forecast period.

Additionally, ODMs are focused on price reduction as well as innovating new energy-efficient products and improved storage solutions, which in turn will benefit the market during the forecast period. However, ODM’s limited service and support services, unreliable server lifespans, and lack of technical expertise to design and deploy white box servers can hinder market growth over the forecast period.

White Box Server Market Report Highlights

North America held the highest market share in 2023. The growth of the market can be attributed to the high saturation of data centers and surging demand for more data centers to support new big data, IoT, and cloud services

Asia Pacific is anticipated to witness the highest growth during the forecast period due to the burgeoning adoption of mobile and cloud services. Presence of key manufacturers offering low-cost products will bolster the growth of the regional market

The data center segment is estimated to dominate the white box server market throughout the forecast period owing to the rising need for computational power to support mobile, cloud, and data-intensive business applications

X86 servers held the largest market revenue share in 2023. Initiatives such as the open compute project encourage the adoption of open platforms that work with white box servers

Curious about the White Box Server Market? Get a FREE sample copy of the full report and gain valuable insights.

White Box Server Market Segmentation

Grand View Research has segmented the global white box server market on the basis of type, processor, operating system, application, and region:

White Box Server Type Outlook (Revenue, USD Million, 2018 - 2030)

Rackmount

GPU Servers

Workstations

Embedded

Blade Servers

White Box Server Processor Outlook (Revenue, USD Million, 2018 - 2030)

X86 servers

Non-X86 servers

White Box Server Operating System Outlook (Revenue, USD Million, 2018 - 2030)

Linux

Windows

UNIX

Others

White Box Server Application Outlook (Revenue, USD Million, 2018 - 2030)

Enterprise Customs

Data Center

White Box Server Regional Outlook (Revenue, USD Million, 2018 - 2030)

North America

US

Canada

Mexico

Europe

UK

Germany

France

Asia Pacific

China

India

Japan

Australia

South Korea

Latin America

Brazil

Middle East and Africa (MEA)

UAE

Saudi Arabia

South Africa

Key Players in the White Box Server Market

Super Micro Computer, Inc.

Quanta Computer lnc.

Equus Computer Systems

Inventec

SMART Global Holdings, Inc.

Advantech Co., Ltd.

Radisys Corporation

hyve solutions

Celestica Inc.

South Korea

Latin America

Brazil

Middle East and Africa (MEA)

UAE

Saudi Arabia

South Africa

Order a free sample PDF of the White Box Server Market Intelligence Study, published by Grand View Research.

[infernovm]

Server spending is at unprecedented levels as enterprises rush to adopt AI

The server market is experiencing record growth amid the voracious demand for production-ready AI infrastructure. The market has more than doubled in size since 2020, with revenues of $235.7 billion in 2024, according to a new IDC report. More than half of that revenue came from servers with embedded graphics processing units (GPUs), a segment that grew by nearly 193% year-over-year in Q4…

[controlledchaosetc]

Something to add.

Disclaimer: I'm not an economics major, I don't own stocks, and I don't keep up with the market too much

However, lord the potential bubble that's forming. For the past year, there's been 7 stocks causing the continued rise of the SMP-500 called "The Magnificent 7". These are Tesla (although Tesla's been doing rather poorly which, lol, lmao even), Meta, Amazon, Apple, Alphabet (aka Google), and most importantly for this AI craze, Microsoft and Nvidia. It's ALL TECH STOCKS.

It's these 7 that drove the growth of the market almost entirely by themselves. Now, at the beginning of this year, it's primarily Nvidia and Microsoft (other stocks are still contributing, but growth wise, over 50% of it is these 2 stocks).

This almost entirely because of GenAI, with Microsoft owning OpenAI as stated before, and Nvidia manufacturing the GPU farms that can run these models.

Nvidia in particular is going ABSOLUTELY FUCKING NUTS. It's growth has SKYROCKETED because they are basically the ONLY company that can create the cards required to support ChatGPT and Midjourney and the like. So if you want to do GenAI, you gotta go through Nvidia, hence the massive growth spike.

Issue. As stated previously, GenAI's not profitable yet. Everyone's investing into 2 companies that are hoping to become money printers on the hope they can awkwardly shove it within their business models.

What happens if it isn't profitable quickly and the majority of companies that aren't doing well growth-wise that are pursuing GenAI stop?

Then gold rush stops and people stop buying shovels. Then the 2 companies that hold up the majority of growth in the stock market stop growing. Then people panic and pull out because its peaked and don't want to be left holding the bag.

We've seen it before with the dotcom bubble. We've seen it hit Nvidia specifically with crypto just a couple years ago (Don't conflate crypto and the current GenAI craze though, because while one was based on almost nothing, there is genuine merit at least business-wise in GenAI. Saying "this is just like crypto" means it's way easier to blow off in your head, and estimates the staying power about as long. Unfortunately I don't think we're getting that).

Idk when, or even if it'll happen, so again, take what I say with a grain of salt, but this expansion can't last. It'll stop, and based on current stock consolidation down to just a few, when it stops it's gonna be baddddddd.

If anyone wants to know why every tech company in the world right now is clamoring for AI like drowned rats scrabbling to board a ship, I decided to make a post to explain what's happening.

(Disclaimer to start: I'm a software engineer who's been employed full time since 2018. I am not a historian nor an overconfident Youtube essayist, so this post is my working knowledge of what I see around me and the logical bridges between pieces.)

Okay anyway. The explanation starts further back than what's going on now. I'm gonna start with the year 2000. The Dot Com Bubble just spectacularly burst. The model of "we get the users first, we learn how to profit off them later" went out in a no-money-having bang (remember this, it will be relevant later). A lot of money was lost. A lot of people ended up out of a job. A lot of startup companies went under. Investors left with a sour taste in their mouth and, in general, investment in the internet stayed pretty cooled for that decade. This was, in my opinion, very good for the internet as it was an era not suffocating under the grip of mega-corporation oligarchs and was, instead, filled with Club Penguin and I Can Haz Cheezburger websites.

Then around the 2010-2012 years, a few things happened. Interest rates got low, and then lower. Facebook got huge. The iPhone took off. And suddenly there was a huge new potential market of internet users and phone-havers, and the cheap money was available to start backing new tech startup companies trying to hop on this opportunity. Companies like Uber, Netflix, and Amazon either started in this time, or hit their ramp-up in these years by shifting focus to the internet and apps.

Now, every start-up tech company dreaming of being the next big thing has one thing in common: they need to start off by getting themselves massively in debt. Because before you can turn a profit you need to first spend money on employees and spend money on equipment and spend money on data centers and spend money on advertising and spend money on scale and and and

But also, everyone wants to be on the ship for The Next Big Thing that takes off to the moon.

So there is a mutual interest between new tech companies, and venture capitalists who are willing to invest $$$ into said new tech companies. Because if the venture capitalists can identify a prize pig and get in early, that money could come back to them 100-fold or 1,000-fold. In fact it hardly matters if they invest in 10 or 20 total bust projects along the way to find that unicorn.

But also, becoming profitable takes time. And that might mean being in debt for a long long time before that rocket ship takes off to make everyone onboard a gazzilionaire.

But luckily, for tech startup bros and venture capitalists, being in debt in the 2010's was cheap, and it only got cheaper between 2010 and 2020. If people could secure loans for ~3% or 4% annual interest, well then a $100,000 loan only really costs $3,000 of interest a year to keep afloat. And if inflation is higher than that or at least similar, you're still beating the system.

So from 2010 through early 2022, times were good for tech companies. Startups could take off with massive growth, showing massive potential for something, and venture capitalists would throw infinite money at them in the hopes of pegging just one winner who will take off. And supporting the struggling investments or the long-haulers remained pretty cheap to keep funding.

You hear constantly about "Such and such app has 10-bazillion users gained over the last 10 years and has never once been profitable", yet the thing keeps chugging along because the investors backing it aren't stressed about the immediate future, and are still banking on that "eventually" when it learns how to really monetize its users and turn that profit.

The pandemic in 2020 took a magnifying-glass-in-the-sun effect to this, as EVERYTHING was forcibly turned online which pumped a ton of money and workers into tech investment. Simultaneously, money got really REALLY cheap, bottoming out with historic lows for interest rates.

Then the tide changed with the massive inflation that struck late 2021. Because this all-gas no-brakes state of things was also contributing to off-the-rails inflation (along with your standard-fare greedflation and price gouging, given the extremely convenient excuses of pandemic hardships and supply chain issues). The federal reserve whipped out interest rate hikes to try to curb this huge inflation, which is like a fire extinguisher dousing and suffocating your really-cool, actively-on-fire party where everyone else is burning but you're in the pool. And then they did this more, and then more. And the financial climate followed suit. And suddenly money was not cheap anymore, and new loans became expensive, because loans that used to compound at 2% a year are now compounding at 7 or 8% which, in the language of compounding, is a HUGE difference. A $100,000 loan at a 2% interest rate, if not repaid a single cent in 10 years, accrues to $121,899. A $100,000 loan at an 8% interest rate, if not repaid a single cent in 10 years, more than doubles to $215,892.

Now it is scary and risky to throw money at "could eventually be profitable" tech companies. Now investors are watching companies burn through their current funding and, when the companies come back asking for more, investors are tightening their coin purses instead. The bill is coming due. The free money is drying up and companies are under compounding pressure to produce a profit for their waiting investors who are now done waiting.

You get enshittification. You get quality going down and price going up. You get "now that you're a captive audience here, we're forcing ads or we're forcing subscriptions on you." Don't get me wrong, the plan was ALWAYS to monetize the users. It's just that it's come earlier than expected, with way more feet-to-the-fire than these companies were expecting. ESPECIALLY with Wall Street as the other factor in funding (public) companies, where Wall Street exhibits roughly the same temperament as a baby screaming crying upset that it's soiled its own diaper (maybe that's too mean a comparison to babies), and now companies are being put through the wringer for anything LESS than infinite growth that Wall Street demands of them.

Internal to the tech industry, you get MASSIVE wide-spread layoffs. You get an industry that used to be easy to land multiple job offers shriveling up and leaving recent graduates in a desperately awful situation where no company is hiring and the market is flooded with laid-off workers trying to get back on their feet.

Because those coin-purse-clutching investors DO love virtue-signaling efforts from companies that say "See! We're not being frivolous with your money! We only spend on the essentials." And this is true even for MASSIVE, PROFITABLE companies, because those companies' value is based on the Rich Person Feeling Graph (their stock) rather than the literal profit money. A company making a genuine gazillion dollars a year still tears through layoffs and freezes hiring and removes the free batteries from the printer room (totally not speaking from experience, surely) because the investors LOVE when you cut costs and take away employee perks. The "beer on tap, ping pong table in the common area" era of tech is drying up. And we're still unionless.

Never mind that last part.

And then in early 2023, AI (more specifically, Chat-GPT which is OpenAI's Large Language Model creation) tears its way into the tech scene with a meteor's amount of momentum. Here's Microsoft's prize pig, which it invested heavily in and is galivanting around the pig-show with, to the desperate jealousy and rapture of every other tech company and investor wishing it had that pig. And for the first time since the interest rate hikes, investors have dollar signs in their eyes, both venture capital and Wall Street alike. They're willing to restart the hose of money (even with the new risk) because this feels big enough for them to take the risk.

Now all these companies, who were in varying stages of sweating as their bill came due, or wringing their hands as their stock prices tanked, see a single glorious gold-plated rocket up out of here, the likes of which haven't been seen since the free money days. It's their ticket to buy time, and buy investors, and say "see THIS is what will wring money forth, finally, we promise, just let us show you."

To be clear, AI is NOT profitable yet. It's a money-sink. Perhaps a money-black-hole. But everyone in the space is so wowed by it that there is a wide-spread and powerful conviction that it will become profitable and earn its keep. (Let's be real, half of that profit "potential" is the promise of automating away jobs of pesky employees who peskily cost money.) It's a tech-space industrial revolution that will automate away skilled jobs, and getting in on the ground floor is the absolute best thing you can do to get your pie slice's worth.

It's the thing that will win investors back. It's the thing that will get the investment money coming in again (or, get it second-hand if the company can be the PROVIDER of something needed for AI, which other companies with venture-back will pay handsomely for). It's the thing companies are terrified of missing out on, lest it leave them utterly irrelevant in a future where not having AI-integration is like not having a mobile phone app for your company or not having a website.

So I guess to reiterate on my earlier point:

Drowned rats. Swimming to the one ship in sight.

[influencermagazineuk]

Nvidia's shares took a significant hit, even after the firm launched its next-generation artificial intelligence (AI) chips at the San Jose, California-based GPU Technology Conference (GTC). Although historic, the reveal was not sufficient to withstand the general risk-averse nature of the market, and the company's shares fell by more than 3% after the announcement. This decline is in line with the prevailing trend of investors shying away from tech stocks in a period of economic uncertainty, compounded by fears over Trump's tariffs. Nvidia was not the only one to experience these headwinds, with other top members of the "Magnificent Seven" group experiencing declines in their stocks. Even though it had recently launched its new AI chips, Nvidia's shares have fallen 15% so far this year in 2025, propelled by both international market nervousness as well as the development of a lower-cost AI model from China-based DeepSeek. Fuel to the flames, Nvidia's latest quarterly earnings report indicated that sales growth slowed, adding to investor caution. However, Josh Gilbert, an eToro Australia market analyst, noted that certain investors may view this decline as a chance, given the valuation of the company is still appealing despite the reduced growth prospects. The GTC, which takes place every year, is a significant event for Nvidia, as it presents its most recent developments and attempts to assure key investors regarding the future of its products. NVIDIA Taiwan, CC BY 2.0 https://creativecommons.org/licenses/by/2.0, via Wikimedia Commons Nvidia released some of its key updates in the product line this year, which are essential to retaining its hold in the AI chip market. The biggest news this year was the release of the Blackwell Ultra chip, which will be used to replace the existing Blackwell supercomputing chip. Expected to begin shipments in the second half of 2025, the Blackwell Ultra promises to deliver superior performance, handling more tasks in the same timeframe as its predecessor. Nvidia’s CEO, Jensen Huang, explained that this chip was designed to meet the current demand for powerful, versatile AI platforms capable of handling everything from pretraining to post-training and AI inference. Besides Blackwell Ultra, Nvidia also announced Vera Rubin, a new-generation system that fuses CPU and GPU processing. The platform will arrive late in 2026 and extend the limits of AI computing power, processing 50 petaflops when handling inference tasks. This would be more than double the current Blackwell chips' capabilities, another step in Nvidia's effort to dominate the AI hardware market. Another significant news at the GTC was Nvidia's revelation of a number of significant partnerships that would push AI and robotics forward. Among them was one with Walt Disney and Google DeepMind on Isaac GR00T N1, a project meant to speed up robotics development. Nvidia also made announcements of collaborations with General Motors for future-generation automotive AI, as well as collaborations with T-Mobile US and Cisco Systems to create AI-based hardware for the 6G network. These partnership arrangements underscore Nvidia's ongoing focus on pushing the boundaries of AI in various industries. Nvidia's main clients are still the world's largest cloud providers, including Amazon, Microsoft, Alphabet, and Oracle, who have all invested heavily in the firm's products. These hyperscalers have purchased 3.6 million Blackwell AI chips in 2025 alone, combined, according to Huang. Overall, Bloomberg stated that firms such as Microsoft, Amazon, and Meta Platforms will spend a whopping $371 billion (€340 billion) on AI infrastructure in 2025, that number forecast to grow to $525 billion (€480 billion) by 2032. The enormous splurge mirrors the increasing need for AI features and the facilities to enable it. Moving forward, specialists believe the investments made on AI will progressively center around more processing capacity as well as improved inference skills and less on designing completely novel AI models. To a great extent, the breakthroughs within DeepSeek's generative AI model have served as an industry pull, stimulating interest. As Nvidia keeps developing its next-gen chips, being ahead of such competitors as DeepSeek will be essential to retain its leadership status in the worldwide AI market. During his address at the GTC, CEO Jensen Huang underscored a major breakthrough in AI development over the past few years, calling it "agentic AI." This advancement, according to Huang, represents a fundamental shift in AI’s capabilities, allowing it to reason and make decisions autonomously about how to answer or solve problems. As AI continues to advance, Nvidia is leading the way in these technological developments, with the goal of delivering the processing capabilities and infrastructure that will define the future of industries from robotics to autonomous vehicles. While Nvidia's shares may have fallen in the aftermath of its announcements, the company's long-term outlook remains strong based on its strategic alliances, advanced technology, and sustained leadership in the AI field. While there may be short-term issues, Nvidia is setting itself up to be a pivotal participant in the current AI revolution, with opportunities for dramatic expansion in the coming years. Read the full article

[delightfullyatomiccollector-blog]

Chiplet Market Advancements Highlighted by Size, Share, Statistics and Industry Growth Analysis Report To 2028

 The global chiplet market size was valued at USD 6.5 billion in 2023 and is estimated to reach USD 148.0 billion by 2028, growing a CAGR of 86.7% during the forecast period.

The growth of the chiplet market is driven by adoption of high-performance computing (HPC) servers in various sectors, proliferation of data centers worldwide, and adoption of advanced packaging technologies.

[lovelypol]

AI Chips = The Future! Market Skyrocketing to $230B by 2034 🚀

Artificial Intelligence (AI) Chip Market focuses on high-performance semiconductor chips tailored for AI computations, including machine learning, deep learning, and predictive analytics. AI chips — such as GPUs, TPUs, ASICs, and FPGAs — enhance processing efficiency, enabling autonomous systems, intelligent automation, and real-time analytics across industries.

To Request Sample Report : https://www.globalinsightservices.com/request-sample/?id=GIS25086 &utm_source=SnehaPatil&utm_medium=Article

Market Trends & Growth:

GPUs (45% market share) lead, driven by parallel processing capabilities for AI workloads.

ASICs (30%) gain traction for customized AI applications and energy efficiency.

FPGAs (25%) are increasingly used for flexible AI model acceleration.

Inference chips dominate, optimizing real-time AI decision-making at the edge and cloud.

Regional Insights:

North America dominates the AI chip market, with strong R&D and tech leadership.

Asia-Pacific follows, led by China’s semiconductor growth and India’s emerging AI ecosystem.

Europe invests in AI chips for automotive, robotics, and edge computing applications.

Future Outlook:

With advancements in 7nm and 5nm fabrication technologies, AI-driven cloud computing, and edge AI innovations, the AI chip market is set for exponential expansion. Key players like NVIDIA, Intel, AMD, and Qualcomm are shaping the future with next-gen AI architectures and strategic collaborations.

#aichips #artificialintelligence #machinelearning #deeplearning #neuralnetworks #gpus #cpus #fpgas #asics #npus #tpus #edgeai #cloudai #computervision #speechrecognition #predictiveanalytics #autonomoussystems #aiinhealthcare #aiinautomotive #aiinfinance #semiconductors #highperformancecomputing #waferfabrication #chipdesign #7nmtechnology #10nmtechnology #siliconchips #galliumnitride #siliconcarbide #inferenceengines #trainingchips #cloudcomputing #edgecomputing #aiprocessors #quantumcomputing #neuromorphiccomputing #iotai #aiacceleration #hardwareoptimization #smartdevices #bigdataanalytics #robotics #aiintelecom