This direction feels especially relevant for enterprise use cases. On-device AI avoids cloud latency and subscription costs, but enterprises also gain privacy, compliance, and real-time responsiveness when models—and sensitive data—stay fully local. It’s compelling to see this shift: not just a fallback for poor connectivity, but a strategic architecture choice where endpoint control (encrypted storage, NPUs, hardware trust) is as critical as algorithmic capability. Great post!
>Then I created HugstonOne Enterprise Edition 1.0.7 and it fundamentally changed how I think about AI.
Who uses versioning numbers like that?
>It’s a paradigm shift.
But we have local LLMs already
>You’re locked into a platform (with no easy way to switch)
I've never think about LLMs providers like a cloud provider. I can jump providers whenever I want. I jumped from OpenAI to Anthropic to Open router. Given the parity of tooling and quality of SOTA models I fail to see where the vendor lock is.
Yes I know, but when I create and/or launch a software project I don't start with "1.0.7" if I'm being _semantic_. It's like a major version AND a patch already? It doesn't track.
"Who uses versioning numbers like that?"
Some coders obsessed with math, among others: Linux kernel: 2.4.0 (1999), Apache HTTP Server: 1.3.34 (2002) etc.
"I've never think about LLMs providers like a cloud provider. I can jump providers whenever I want. I jumped from OpenAI to Anthropic to Open router. Given the parity of tooling and quality of SOTA models I fail to see where the vendor lock is."
You didn't really read the article. You may jump but not your data, not the price and not the dependency. So yes they are a provider and a cloud, while with HugstonOne, the user becomes the provider.
And for the rest, I see you are very curious and have many questions. Maybe you can try the app, I am sure it will satisfy all your questions in an excellent manner.
But if I had to have AI, it would be on a local PC without an internet connection. Sadly this seems Windows only, which is a no-go for me, plus with Windows 11, can you really run it without an internet connection ?
But to me, I would be more worried about heat, I would think AI would push a Laptop to the limit.
So funny you mention it cause I was on vacations in Spain few weeks ago. They are the definition of "I will avoid AI at all costs". It seems we are living in 2 parallel universes. All the Spanish I met don´t know, don´t use and don´t care about AI.
I have been so busy but Linux version is coming soon, it is very time demanding.
And eventually I have to upgrade to a desktop PC for better performance.
Certainly I seem to have poor skill of writing an article, contrary to writing code.
Of course I use my app to revise, suggest and correct grammar, that´s why I created HugtsonOne, to help me optimize time.
So yes the article has some patches of LLM.
being able to write text in "human" is rapidly becoming an essential skill. too bad for non native speakers who go for the easy way of LLM munching, it shows and frankly, it grated. not totally their fault though.
my advice: own you mistakes and mal-à-propisms!
This direction feels especially relevant for enterprise use cases. On-device AI avoids cloud latency and subscription costs, but enterprises also gain privacy, compliance, and real-time responsiveness when models—and sensitive data—stay fully local. It’s compelling to see this shift: not just a fallback for poor connectivity, but a strategic architecture choice where endpoint control (encrypted storage, NPUs, hardware trust) is as critical as algorithmic capability. Great post!
You are absolutely right!
Thank you so much, I appreciate your reply.
>Then I created HugstonOne Enterprise Edition 1.0.7 and it fundamentally changed how I think about AI.
Who uses versioning numbers like that?
>It’s a paradigm shift.
But we have local LLMs already
>You’re locked into a platform (with no easy way to switch)
I've never think about LLMs providers like a cloud provider. I can jump providers whenever I want. I jumped from OpenAI to Anthropic to Open router. Given the parity of tooling and quality of SOTA models I fail to see where the vendor lock is.
semantic versioning (Major.Minor.Patch) is widely adopted and was standard practice in the 90s.
Yes I know, but when I create and/or launch a software project I don't start with "1.0.7" if I'm being _semantic_. It's like a major version AND a patch already? It doesn't track.
TFA reads like AI slop honestly.
"Who uses versioning numbers like that?" Some coders obsessed with math, among others: Linux kernel: 2.4.0 (1999), Apache HTTP Server: 1.3.34 (2002) etc.
"I've never think about LLMs providers like a cloud provider. I can jump providers whenever I want. I jumped from OpenAI to Anthropic to Open router. Given the parity of tooling and quality of SOTA models I fail to see where the vendor lock is."
You didn't really read the article. You may jump but not your data, not the price and not the dependency. So yes they are a provider and a cloud, while with HugstonOne, the user becomes the provider.
And for the rest, I see you are very curious and have many questions. Maybe you can try the app, I am sure it will satisfy all your questions in an excellent manner.
To be honest I will avoid AI at all costs :)
But if I had to have AI, it would be on a local PC without an internet connection. Sadly this seems Windows only, which is a no-go for me, plus with Windows 11, can you really run it without an internet connection ?
But to me, I would be more worried about heat, I would think AI would push a Laptop to the limit.
So funny you mention it cause I was on vacations in Spain few weeks ago. They are the definition of "I will avoid AI at all costs". It seems we are living in 2 parallel universes. All the Spanish I met don´t know, don´t use and don´t care about AI. I have been so busy but Linux version is coming soon, it is very time demanding. And eventually I have to upgrade to a desktop PC for better performance.
What happened to the paragraph after "What Makes HugstonOne Different"? I'm not sure if the formatting got lost somewhere or what...
Thank you, that´s a good observation that need to be fixed right away.
The specs of the laptop are nowhere to be seen both in the post and in the website. Any guesses?
You are right! Is a Lenovo Thinkpad T440s 4gb ram. It runs well in cpu (I7) with any model under 4b.
> This isn’t just another AI tool. It’s a paradigm shift.
ah so this entire article is written by a language model
Something feels off about the whole thing. I find the article to be extremely low information and extremely hyperbolic. It feels like keyword soup.
Certainly I seem to have poor skill of writing an article, contrary to writing code. Of course I use my app to revise, suggest and correct grammar, that´s why I created HugtsonOne, to help me optimize time. So yes the article has some patches of LLM.
It definitely has LLM vibes…
being able to write text in "human" is rapidly becoming an essential skill. too bad for non native speakers who go for the easy way of LLM munching, it shows and frankly, it grated. not totally their fault though. my advice: own you mistakes and mal-à-propisms!
You’re right: It’s not about "being perfect," but about taking responsibility for your words. That’s the skill that lasts AI or not.