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Understanding locally hosted AIs

Artificial intelligence, once a futuristic dream, has firmly rooted itself in our present-day technological landscape. However, the burgeoning field of locally hosted AI models is a distinct departure from the cloud-based AI that has dominated the scene.

This shift from cloud-based to local hosting is more than a technological nuance; it’s a fundamental change in how AI interacts with our data and devices. We will explore the significance of this transition, its impact on privacy, speed, autonomy, and customization, and how it is reshaping industries, from web development to small business operations

Understanding locally hosted AI

Unlike its cloud-based counterparts, where computations and data processing happen in remote data centers, locally hosted AI operates directly on your device. This approach has a bit of a “home-cooked” flavor—it’s personal, customizable, and sits in your own digital backyard.

The contrast with cloud-based AI models is striking. Cloud AI, the norm until recently, relies on sending data to distant servers where the processing happens.

On the other hand, with locally hosted AI, the interaction is direct, with computations happening right where the data resides. But why does this matter? 

Locally hosted AI opens up a world of possibilities that cloud-based models can’t always match. For starters, it offers enhanced privacy and security. Your data doesn’t need to leave your device, reducing the risk of breaches and unauthorized access.

Then there’s the aspect of speed and reduced latency—since the data doesn’t travel far, responses are quicker, making it ideal for real-time applications.

Moreover, locally hosted AI models promise a new level of autonomy and customization. You’re not at the mercy of cloud providers’ policies or network outages. 

You can tweak, adjust, and experiment with AI models to your heart’s content, tailoring them to specific needs or the management of projects. This autonomy is not just empowering; it’s a game-changer for innovators, developers, and businesses seeking to harness AI in unique ways.

Illustration suggesting security and speed for local AIs

The benefits of running AI models locally

When we talk about locally hosted AI, the benefits are as diverse as they are significant. Let’s break them down:

Enhanced privacy and data security

One of the most compelling advantages of running AI models locally is the increased level of privacy and data security. With data processing and storage happening on your device, the risk of data breaches and external hacks is drastically reduced. 

In a world where data is gold, keeping your information safe and secure is more important than ever. Locally hosted AI keeps your data under lock and key—in your control, not floating in the cloud. And the best part? This benefit isn’t reserved just for corporations with millions to spend on five-figure GPUs. 

Improved performance and speed

Speed is of the essence in our fast-paced world, and locally-hosted AI delivers on this front. By eliminating the need to send data back and forth to a remote server, locally hosted AI models can process information much faster.

This is the primary benefit that will drive further adoption. Over 100 million Americans are anticipated to engage with generative AI by 2024, with this number projected to swell to 116.9 million by 2025

But with that increased usage will undoubtedly come many concerns. We’ll examine some that could be on the horizon. First, let’s look at another benefit of having your own locally hosted AI model.

Autonomy, control, and accessible entrepreneurship

Running your AI models locally puts you in the driver’s seat. You have the freedom to customize and tweak the AI models to fit your specific needs without being constrained by the limitations or rules of a cloud provider. 

This level of control and autonomy is not just liberating; it’s a catalyst for innovation and personalized solutions. Small businesses don’t have to worry about investing copious amounts of money into 

It’s also not too hard to imagine a near future where locally hosted AI models become an engine of entrepreneurship. 

Provided that you have the right model, use case, and business plan, AI could help enterprising individuals who might otherwise lack the necessary manpower and funds with various aspects of running a business, both minor and major. 

From small functions like using a free company naming tool or image generation for branding to complex market analysis, financial planning, and legal compliance, it’s quite possible that locally hosted AI models will make entrepreneurship much more accessible going forward.

Locally hosted AI in web development

Here, we examine how locally-hosted AI is revolutionizing web development. In particular, let’s look at WordPress, which powers a staggering 43% of all websites as of 2024.

The integration of AI into this area opens up exciting possibilities. Imagine using a locally hosted AI model to craft a unique WordPress layout or generate front-end code. This isn’t just about making web development easier; it’s about unleashing creativity and efficiency in ways we’ve never seen before. 

With AI, the process of building a website could become more intuitive, more adaptive, and more streamlined. 

The utility extends beyond setting up a website—as Graham Grieve, the founder of Scottish SEO Agency A1 Glasgow, succinctly put it: 

“These models can be trained on internal data and prompted to come up with elaborate marketing strategies, tailored specifically to local markets and individual business needs, making them a game-changer in digital marketing, particularly in terms of allowing small businesses to compete with larger, more established companies.”

We’re looking at a future where artificial intelligence is accessible to everyone, with entry costs limited only to the hardware needed to run these less demanding models.

Checklist for locally-hosted AIs

How to run AI models locally

Ready to get your hands dirty with some AI? Here’s a basic guide to help you set up a locally hosted AI model. We’ve broken them down step-by-step so you can get started with your own AI.

  1. Assess Your Hardware: Ensure your device has the necessary computing power. This might include a robust processor, sufficient RAM, and, for more intensive tasks, a capable graphics processing unit (GPU).
  2. Choose the Right Software: Select the AI model that fits your needs. Open-source models offer a good starting point.
  3. Installation: Install the necessary libraries and dependencies. This often involves using package managers like Pip or Conda.
  4. Download the AI Model: Choose a model appropriate for your hardware and software setup. You can find specific websites that offer a plethora of models to start with. There are even modified versions adapted for specific tasks like ideation, coding, strategizing, and more. 
  5. Set Up the Environment: Configure your environment to suit the model. For more complex setups, this could include virtual environments or containerization.
  6. Run a Test: Execute a simple test to ensure everything is working as expected. Test the model with prompts, measure its output (tokens per second) and determine whether it’s usable throughout your business’s workflows. 

Consider Llama.cpp, an accessible tool for running AI models locally. Start by cloning the repository, compiling the model, and setting it up as per the instructions. Even if you’re not a seasoned developer, the community and documentation around such tools can guide you through the process.

Practical applications in business

Locally-hosted AI is set to transform business operations, especially for e-commerce and small enterprises, by streamlining various processes.

One practical application is in customer service automation. For instance, AI can handle routine inquiries, allowing human staff to focus on complex issues. This not only improves efficiency but also enhances customer experience with faster response times.

In e-commerce, AI can optimize inventory management, using predictive analysis to forecast demand and prevent overstocking or stockouts. This level of precision ensures businesses are agile and responsive to market changes.

Small businesses can also benefit from AI-driven logistics solutions. AI algorithms that predict and manage logistical hurdles can mitigate common challenges, such as packages stuck in customs, reducing delays and improving the supply chain’s reliability.

For marketing, locally hosted AI can personalize customer interactions. By analyzing customer data, AI can tailor marketing strategies to individual preferences, increasing engagement and sales.

Security concerns and ethical considerations

Unfortunately, malicious actors also reap the benefits of the greater degree of control and privacy that locally hosted models provide. The use of AI in malware has already caught the attention of cybersecurity specialists because the problem is already here.

AI-powered phishing attacks leveraged for ransomware are already misusing the technology’s capabilities to craft more convincing, adaptable messages — and several types of malware, like HYAS Labs’ Black Mamba keylogger or IBM’s evasive DeepLocker malware.

While these are two examples of malware made to showcase and highlight the potential dangers that the misuse of this powerful technology can bring about, the genie is out of the bottle, so to speak—and it won’t be long before we see actual incidents involving AI-powered malware.

This emerging arms race isn’t just a battle between AI’s offensive and defensive capabilities. Imagine an AI model trained to enhance the security of patient health data or virtual debit card transactions falling into the wrong hands. Such a model, locally hosted, could mimic legitimate activities, adapting and learning to ultimately deliver nigh-undetectable intrusions.

Another risk involves data privacy. Locally-hosted AI systems require access to vast amounts of transaction data to function effectively. If these systems are not adequately secured, they could become a goldmine for hackers, providing them with sensitive information.

Ethically, the autonomy of locally hosted AI poses significant dilemmas. The unchecked use of AI can lead to biases in decision-making, privacy invasions, and even unintentional harm.

For instance, AI algorithms could inadvertently reinforce societal prejudices or make incorrect decisions based on flawed data. Furthermore, humans have a moral responsibility to ensure that these AI systems are transparent and accountable. 

Without proper oversight, AI could be misused for surveillance or manipulating user behavior, raising concerns about individual autonomy and consent

Local AI applications continue to grow

We’ve journeyed through the evolving landscape of locally hosted AI, a game-changer in the tech world known for its heightened privacy, independence, and tailored experiences. This area of tech is rapidly expanding and covers everything from boosting business operations to ethical dilemmas and revolutionizing web design.

With more and more people turning to AI, there’s an open invitation to delve into its rich possibilities, all within the comfort of our digital realms.

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Gary Stevens avatar

Gary Stevens

Gary Stevens is a web developer and technology writer. He's a part-time blockchain geek and a volunteer working for the Ethereum foundation as well as an active Github contributor. More articles written by Gary.

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