Saturday, March 30, 2024

What Are AI PCs? A Brief Explanation

Before I start with the explanation below I'd like to say that I believe that AI (artificial intelligence) as we are defining it today is not what most people envision as true 'artificial intelligence.' I look at it more as an augmented intelligence, one that uses your own interactions and those of users like you to generate best case answers, images, videos ect. We've been using the same software, same search algorithms, same voice commands, same pretty much everything for several years now. We never called it AI before because of the marketing strategy. Today we are just now seeing the marketing hype behind those same tools that have been learning our habits for years (I won't get started on the privacy issues here).

AI PCs - Intel's New Marketing Term

To put this simply the term AI PC is an Intel derived marketing term that requires specific Intel hardware and standards to apply. This doesn't mean that other PCs or devices can't run AI or that they aren't AI ready or AI chip equipped. So don't be confused here! 

Intel has stated that for a PC to receive the coveted "AI" label, it needs four things: a neural processing unit (NPU), a graphics processing unit (GPU), and the ability to handle Vector Neural Network Instructions (VNNI) and DP4a instructions (so that the GPU can handle video processing)  In other words what Intel is saying is that in order for them to call a new computer an AI PC it must be one with their latest CPU.


What is AI Ready and AI equipped

When it comes to slapping the AI ready label on things these are the few small things to know. AI apps and tools are currently used in two different ways. The difference between the two and how you are using them is really the difference in hardware requirements and what is needed. Basically any PC, smartphone, tablet or device can access and use cloud based AI.  On device generative tools require much better, more efficient hardware and that is were some of the confusion starts for most people.

One of the easiest ways to explain the hardware is to say the modern CPU as most people know it has become extremely outdated. New software changes take advantage of and use the GPU and a new NPU (secondary chip) to do the heavy work. These are both considered AI accelerators, deep learning processor, or neural processing units (NPUs). They have been specifically designed to accelerate artificial intelligence and machine learning applications and algorithms. (More on the differences here)

Tools like ChatGPT, Google image generator Gemini, or Microsoft CoPilot are all cloud based and do all their work in a cloud based system. This allows EVERY device to utilize AI because all the work is done by other, much more powerful systems, that then send the results to your PC or phone. This will soon change however as Intel has confirmed CoPilot and other applications will soon run locally on PCs and require better hardware to do so. 

PCs meeting those requirements are already shipping and other devices like the Apple iPhone, Google Pixel 8 and Samsung Galaxy phones are already using secondary more AI specific NPU chips for on-device AI.

In conclusion - don't be confused or fooled!
I'm writing this post I'm really hoping to take some confusion out of buying or upgrading your systems and hope that people aren't fooled into think they have to run out and search only for an AI PC to run their newly hyped apps. Yes newer hardware will eventually be required, and yes it only makes sense to adopt that hardware if you are already upgrading. No, that doesn't mean you will be left out if you don't!

Monday, January 22, 2024

Will AI Monetization Stifle Innovation?

Nearly a full month into 2024, and it's evident that this year is poised to be the "Year of AI," with virtually every aspect of our lives touched by AI in some form or another. However, as we witness the rapid development and subsequent market integration of AI, potential drawbacks are emerging. The two most significant hurdles seem to originate directly from tech giants.

AI Consolidation

Towards the end of 2023, major tech players such as Amazon, NVIDIA, Microsoft, and Google made significant moves to expand their AI portfolios, consolidating smaller companies under the umbrella of their massive enterprises. For instance, Amazon invested $4 billion in the startup Anthropic, while Google secured a $2 billion stake of its own. While these moves provide startups with the capital needed for growth, they often result in the acquiring companies exerting too much control over the projects, hindering their progress.

The desire to quickly monetize and grow a company, followed by potentially selling off the team's hard work, often leads to issues down the road. Companies like Amazon, Apple, and Google tend to absorb acquired ideas and software, which may either get shelved, completely reimagined, or fall by the wayside as companies explore other, potentially more cost-effective options.

While some acquisitions have led to great innovations, such as Apple incorporating features like Siri from the 30+ AI startups it acquired over the last decade, other instances, like Google shuttering numerous programs, showcase the potential pitfalls of consolidation.

AI as a Service and Pay-Walling

While consolidation poses challenges to development, the more significant concern lies in the tendency to place AI tools behind paywalls or offer them as subscription services. Companies naturally seek to monetize their AI tools swiftly and effectively. For instance, Microsoft already offers its AI tool Copilot as a subscription service, and Amazon reportedly plans to introduce a paid Alexa service, "Alexa Plus," featuring premium features.

Running these programs, developing infrastructure, and staying ahead in terms of development are costly endeavors for large companies. While pay-walling premium features is not a novel approach, consumers generally resist being forced to pay for tools they are already using. In the realm of new technology and the push for expanded integration and adoption, subscriptions may not be the most effective means to align consumers with corporate plans. If consumers push back against adoption, some otherwise promising companies might face setbacks.

Big Tech Control Playing Big Brother

One area I haven't really discussed is big tech and government level control. We are already seeing governments around the world  looking at regulations and attempts at controlling or slowing AI adoption. Historically speaking rapid progression of technology hasn't been the best thing. We've made some big mistakes over the years. Generally big tech has played big brother of sorts and held back quick rapid releases of new technology. Hint there are things they have now you still won't see for yrs because of costs Where this control and controlled slow releases may be warranted. The down side is if we attempt to slow adoption in one area we inevitably kill off competition and innovation in another!

If government regulation is overly strict it puts undue pressure on start-up companies and keeps them from the market. If they aren't strict enough then we see top tier companies effectively being the key-holders and keeping innovation out (or in). We end up putting in place too many barriers and true innovators suffer the consequences!

My Conclusion

From my background in the tech sector and the work I've done over the years I see the term AI as much more of a marketing term right now than anything else. People overlook that Siri, Alexa, Google Search ect are all essentially AI. For me personally I think the term as we currently use it Artificial Intelligence, really is a misnomer. I think Augmented Intelligence is far closer to what we currently have rather than the average person thinks of AI  (which is mostly a theatrical movie style computer driven intelligence).

I feel that if we see our current systems going to SaaS (subscriber or pay-to-use) we'll see consumer blow-back and companies will have to rethink their programs. I believe people are already starting to wake up to over utilization of the AI label and the market saturation of the term! My hope is companies keep an even keel on this and let the tech progress naturally. Hopefully smaller companies and individual developers are lost in the shuffle!

Wednesday, January 03, 2024

2024 IPOs Are Coming, Will We See a Boom or Bust

Just a few of the IPOs expected are; Reddit, Discord, Skims, Stripe, Shein, Panera, and Liquid Death (amongst about 50 more top names). IPOs over the last few years have had some mixed results and unfortunately some of these may see the same downturns.

First off, we are seeing a draw back from the tech sector. So many of these tech related companies might be a tough sell on Wall Street. Several major players have been selling off real estate and downsizing work forces. We have also seen many major startups failing all together.

Secondly, many of the companies expected to go public are already cash strapped and are only making the move because they need to capital. While this is normal, it also indicates that they may not be on a solid foundation. A major negative for Wall Street players looking for long term growth potential.

On the upside, most of these brands carry major 'sentimental' up-value. Meaning investors will grab a hold of them because they are who they are. The question we'll see answered, really quickly, is if that brand recognition will hold value and those IPOs pay off the way these companies hope!

 As an investor and Techie it will be interesting to watch what happens. Some of these tech companies directly impact my daily life as I'm a member of several of their sites. We are already seeing push-back  from Reddit developers seeking more money or a share of the value add their work has given the company. Once the money starts flowing we may see a major negative push! Fingers crossed for any early investors!