Posted on 03/14/2025 12:48:38 PM PDT by Red Badger
It’s 2026. You just bought a new laptop, and unlike your last one, this device is an “AI PC.” The distinction means you can now run all the latest AI applications directly on your device without draining your battery, keeping your data private and secure.
AI PCs If you stopped by a Sears circa 1960 to buy a television, the sales clerk’s first question for you would’ve been, “Color or black and white?” Only after hearing the answer could they help you find the television that was right for you.
Today’s computer buyers are facing their own fork in the consumer tech road as manufacturers begin rolling out “AI PCs” alongside their traditional models.
“AI PCs are laptops or desktop computers equipped with specific hardware that make them suitable for on-device AI tasks or features,” AI educator Paul Couvert tells Freethink. “Generally, they are more expensive than regular PCs when it comes to laptops, but they are becoming more and more affordable.”
To better understand this new category of computers, this week’s Future Explored is digging into the evolutions of PCs, what sets AI models apart from the rest, and why you may or may not want to buy one the next time you’re in the market for a new computer.
Where we’ve been
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It’s 2026. You just bought a new laptop, and unlike your last one, this device is an “AI PC.” The distinction means you can now run all the latest AI applications directly on your device without draining your battery, keeping your data private and secure.
AI PCs If you stopped by a Sears circa 1960 to buy a television, the sales clerk’s first question for you would’ve been, “Color or black and white?” Only after hearing the answer could they help you find the television that was right for you.
Today’s computer buyers are facing their own fork in the consumer tech road as manufacturers begin rolling out “AI PCs” alongside their traditional models.
“AI PCs are laptops or desktop computers equipped with specific hardware that make them suitable for on-device AI tasks or features,” AI educator Paul Couvert tells Freethink. “Generally, they are more expensive than regular PCs when it comes to laptops, but they are becoming more and more affordable.”
To better understand this new category of computers, this week’s Future Explored is digging into the evolutions of PCs, what sets AI models apart from the rest, and why you may or may not want to buy one the next time you’re in the market for a new computer.
Where we’ve been 1971 - Kenbak Corporation begins selling the first personal computer: the Kenbak-1. It’s designed as an educational device that can be used to learn the fundamentals of computing, but is not popular—only 50 or so devices are ever manufactured.
1974 - American software company Digital Research releases Control Program/Monitor (CP/M), the first mass-market operating system for PCs. The software makes it easier for a single application to run on a variety of computer models.
1977 - The Commodore PET 2001, the Apple II, and the Tandy/Radio Shack TRS-80 Model 1 hit the market. The three systems are later described as the “1977 Trinity” and credited with bringing PCs into the mainstream.
1981 - Osborne Computer Corporation releases the Osborne I. Despite weighing nearly 25 pounds, it is widely considered the first laptop computer as it can be folded shut and carried by hand.
1984 - Apple releases the Macintosh 128K, the first successful mass-market PC with a graphical user interface. Instead of typing commands using a keyboard, PC owners can now use a cursor to click on icons and other graphics. This makes learning to use computers easier and helps accelerate their adoption.
1990s - PC developers start to integrate CD-ROM drives into their systems. Because CD-ROMs can store far more information than floppy discs, they make it easier to distribute software and lead to digital encyclopedias and more immersive computer games. PCs equipped with the drives are often marketed as "multimedia computers."
1999 - Apple begins selling the iBook, a line of laptops featuring its new AirPort card. This allows the devices to wirelessly connect to the internet, bringing WiFi into the consumer tech mainstream.
1999 - Nvidia releases its GeForce 256, the first commercial graphics processing unit (GPU). These electronic circuits are specifically designed to take the burden of processing images off of the central processing unit (CPU). This enables more realistic computer graphics—a major boon in gaming.
2010 - Apple releases the iPad. Though not the first tablet PC, it is the first to find commercial success and inspires the creation of more devices with touchscreens and 2-in-1 designs.
2024 - Microsoft, Apple, and other major manufacturers begin selling PCs designed to efficiently run AI programs on GPUs, CPUs, and neural processing units (NPUs). Tech market analyst firm Gartner predicts that these “AI PCs” will account for 43% of all PCs shipped in 2025. Where we’re going (maybe) AI isn’t brand new—research into machines that can “think” has been going on since the 1940s—but the tech surged to the top of the public consciousness following OpenAI’s November 2022 release of ChatGPT, an AI capable of engaging in human-like conversations.
Within two months, more than 100 million people were using ChatGPT, and almost as quickly, seemingly every company, whether it was selling toys or TVs, was boasting about its products’ AI features.
The AI hype grew so quickly that by February 2023, the Federal Trade Commission was warning companies that they had better not be overpromising what their AI products could do or exaggerating their benefits over existing goods.
“[AI is] a marketing term,” Michael Atleson, an attorney in the FTC’s Division of Advertising Practices, wrote in a blog post. “Right now it’s a hot one, and at the FTC, one thing we know about hot marketing terms is that some advertisers won’t be able to stop themselves from overusing and abusing them.”
Taking all of this into consideration, it’s hard not to be a little skeptical of “AI PCs.” Are they really a significant advance in computing? Or just another example of the AI label being slapped onto a product to encourage sales?
What is an AI PC? To start to answer that question, we need to take a look at how the AI applications now making their way into our workplaces and homes operate.
AI tools like ChatGPT, Microsoft Copilot, and Apple Intelligence require a lot of processing power. If you access these AIs online, this processing takes place at a data center with enough servers to parse your request and respond within seconds.
However, there are benefits to having an AI do its processing locally, right on your computer.
A key one is that it keeps your data private and secure—no need to worry about a third-party seeing what you’re doing or being hacked. If you were paying a monthly subscription for an AI that runs in the cloud, running locally can save you money, and because your data doesn’t have to travel anywhere for processing, the approach can reduce latency and lead to faster results.
To take advantage of these benefits, though, you need a PC with enough processing power onboard to run the AI without slowing your system to a crawl. This is what tech companies say AI PCs can deliver.
“It’s a PC that can run AI on either an NPU, GPU, or CPU,” Josh Newman, general manager and vice president of product marketing and management at Intel’s Client Computing Group, tells Freethink. “That’s integrated into the PC so that all of the new software that is using AI models…will run smoothly and can deliver new experiences to customers.”
Intel’s Ultra Core processors include a CPU, GPU, and NPU. Let’s break that down.
If you’re at all familiar with the inner workings of PCs, you’ve likely heard about CPUs (central processing units) and GPUs (graphics processing units) before. The former acts like a computer’s “brain”—it interprets commands and carries out instructions. The latter was initially designed to process graphics for PCs, freeing up the CPU to work on other tasks and helping the whole system run more smoothly, but they’ve since proven useful for other applications, too, like mining cryptocurrency and training and running AIs.
This might, however, be your first time hearing about NPUs (neural processing units). These processing devices are specifically designed to handle AI tasks, which is why they’re sometimes called “AI chips” or “AI accelerators.”
“You want that to be really high fidelity… You want it to be seamless. That’s where the NPU comes in.”
Josh Newman
While GPUs have been a standard component of PCs for more than a decade (and CPUs have always been a part of them), NPUs are a newer feature, and while there isn’t a universally accepted definition of an “AI PC,” having an NPU is often considered a requirement and concretely sets these systems apart from regular ones.
“NPUs are specifically tuned for AI workloads to run them fast and at lowest possible power, so they’re great for AI applications that will always be running in the background,” says Newman.
“You think about video green screening, the background removal that’s constantly running for the hours you’re on Teams or Zoom calls,” he continues. “You want that to be really high fidelity, but you also want it to not take too much power or make the fans go up while you’re working. You want it to be seamless. That’s where the NPU comes in.”
Do I need an AI PC?
The answer to this question depends on what you plan to do with your computer.
If you’re someone like Couvert, who does a lot with AI, paying extra for a PC with an NPU could be worthwhile, especially if you’re buying a laptop—while many desktops can efficiently handle AI applications even without an NPU, running those same AIs through a laptop’s CPU or GPU could slow the system and drain its battery.
“I’m daily using both a Chromebook Plus and a Windows Copilot + laptop with a Snapdragon X Elite chip that allows me to run AI models locally,” Couvert tells Freethink. “The Copilot+ PC is very useful to me for interacting with AI models without being connected to an external server, which is a huge plus for privacy and cost efficiency. It also allows me to run my own AI agents basically for free, without having to rely on third-party APIs from OpenAI or other providers.”
If the only time you use AI is to blur your background in Zoom videos, and your current system seems to be handling that task just fine, switching to an AI PC right now might not be imperative. However, new AI tools are rolling out all the time, and some of them already require an NPU, so if you’re going to buy a new PC anyway and think you might want to take advantage of AI more often in the future, you may want to think about upgrading to one with an NPU.
“Given that AI PCs, specifically those using Snapdragon X chips, are becoming less expensive, if you need to change your laptop, it’s worth considering this option even today,” says Couvert.
Wait long enough, though, and you won’t have to decide between an AI PC and a regular one. Just like it did with GPUs, the tech industry seems to be planning to make NPUs a standard part of PCs moving forward, and eventually, finding one without an NPU will be as challenging as tracking down a brand new black-and-white TV.
“Pretty soon, all PCs will be AI PCs,” says Newman.
We’d love to hear from you! If you have a comment about this article or if you have a tip for a future Freethink story, please email us at tips@freethink.com.
Then we got VT100s and it was waaaay easier and fun...
= = =
I got my boss to get us one in our office.
Saved many 1/4 mile one-way trips to feed card decks into the mainframe.
Does it boot DOS? There’s your test for a YADM (yet another dos machine).
Something here is not adding up. AI needs so much power nuclear power plants will be needed to supply it verses it will soon be on your laptop.
However, there are benefits to having an AI do its processing locally, right on your computer.
= = =
Sounds good, so far . . .
But I thought AI searched and analyzed a lot of data to get their analysis.
Is this data supposed to be on my computer? It is pretty vacant right now. Maybe some family photos, screen dumps of engineering constants and conversion tables, ...
I don’t think AI can get very smart from my limited set of data.
What am I missing?
In layman's terms, not much unless you do a lot of high powered processing. And even then, we're talking about only certain tasks that are programmed to utilize that kind of instruction set.
Perhaps in 5 or so years, "normal" software apps will be made to utilize those instruction sets as well. For example, the laptop I'm typing this on is running a SQL Server database engine -- requiring more horsepower than most people need from their PC's (except maybe hardcore gamers). But the database software isn't design to utilize the GPU style chips of an "AI PC". So my database engine wouldn't run any faster on one of those chips...for now. Neither would any of my homemade software.
But a few years from now, perhaps I could recompile my same old software (a lot of it is C#) in a new version of the IDE I use, but with a few property settings it'd compile the end user program to utilize the GPU style chips too, with no real changes needed from me as a programmer to change a lot of the code. Then my software apps (and other out of the box apps) would run tons faster on the GPU PC's.
But even then, it wouldn't matter unless your app was very heavy on processing use (instead of being a light-weight app that's waiting for information to download from the internet, like my TUBI app on my ROKU device does, which will never speed up unless I speed up my internet connection).
For me, it would mean that when I lead a financial small group and someone asks, "What would have happened with investment portfolio A for someone who retired right before the dot-com bubble burst?". None of that data has to be downloaded -- I have it on my laptop (no lag time because of internet speed). The only lag in time for me to produce a report to answer that question is purely processing power to churn through the market data for that time period --- speeding up the CPU processing would be nice and make it take maybe half a second instead of 2 or 3 seconds. But virtually nobody does that kind of thing for personal use.
The same for if I wanted to study the past few years of my solar inverter data (which records all of the solar power coming in, how much of it was to power my home, how much I had to pull from the grid, etc. every 5 minutes). Perhaps if I wanted to re-examine all of the power rate plan options my power utility offers to see which one would cost me the less money based on what I know I would have pulled from the grid at each time of day during each month with each of the different time of day rates and how each of those change during the seasons. Again, none of that is data I'd have to wait to download from the internet (the usual reason we have to wait when using PC's). But it's a task I might have to wait a few seconds or even a minute to run because it's churning through a lot of data. But virtually no one else does that kind of thing with their laptop/desktop. So this GPU technology is really for AI and blockchain and gaming stuff.
Thanks.
For your solar power inverter case, would you be required to formulate a normal rigorous statistical analysis in R? Or will you be able to present the problem in general terms and have AI figure out HOW to solve it?
I use a recording pulse-oximeter at night to see how well I’m sleeping on my CPAP machine. I have tons of data in csv format and have been wondering how to analyze it. The app that comes with the recording device has simple histograms and averages, but they are only on a per-day basis. I can’t do summary analysis for a week, month or year.
I used co-pilot for the first time today.
It has a “conversation” with you.
Get it going with a basic question.
It then responds to one word inquisitive queries.
I asked about data centers in TX. It will throw out an informative detail.
Then I just asked “Compass” or “Microsoft” or “Dallas”.
It stayed on topic with data centers in TX.
It was kinda cool.
Shut up Stella.😏
AI PC sounds more like a spying on you and phoning home PC..... /Constantly taking screenshots and storing them/....until proven otherwise. I use Grok and Perplexity AI on line. How is any PC with built in AI, going to be better than Groks stacks of latest NVidia chips. I hear 100,000 of them.
AI PC is also a bonzo selling point. Soon be sold on QVC. Your brand new 17.3” HP / AI PC. Women love laptops and I see the larger 17.3” ones are sold frequently on QVC. What can I say, but better than a dumbed down tablet
Oh, but those people ARE "special needs" persons.
They "specially needs" to be taken out back and thrashed severely for their stupidity.
“I don’t want AI at all. When I’ve asked AI if someone is a retard, it nags at me
saying that is not appropriate question. It truly is 1984 Big Brother.”
Hear hear...
That's what the smaller kids called me because they were jealous that I was special and the school sent a little bus just for me.
Mean man sent email saying I need to go home now. That's funny cause I've been home for years.
Paste tastes good but don't tell anybody.
LOL, RIGHT!?
There you go.
I built my own desktop for the first time. The first I did was test it out playing Doom.
"Plook me now, you savage rascal."
These fools didn't even mention my Texas Instruments TI-99/4a. The TRS80 was a stupid joke compared to the TI-99/4a and it had the best speech synthesizer up until the present day.
The Osborne was a nothing burger, but it made a good boat anchor.
I already have issues with my Smart TV acting too smart for its own good. The last thing I want is an AI-PC that thinks it has to police my usage or think for me.
I can see it now, the AI Nanny PC the best thing for the modern-day sheeple.
Loading “Tunnels of Doom” from my cassette drive…good times!
“All PCs will be AI PCs “pretty soon,”
.
I will be building a 100% Linux PC “pretty soon.”
Windows will only exist in a spellchecker on that box.
.
Nope, it was never the word but the usage of it.
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