Using artificial intelligence (AI) systems without internet access might sound unrealistic, but it is actually quite feasible today. Neural networks can operate locally on a device, such as a computer or a smart phone, and be used for applications that require fast on-site data processing or a higher level of privacy, which is especially important in modern business and everyday life. These systems are designed to perform planning and forecasting, natural language processing, computer vision and more, with higher efficiency and security.
AI is changing the rules of the game
AI is truly a game-changer; but a system that performs AI tasks entirely on your device, rather than relying on online services, can make our lives easier and more convenient in many ways. Imagine a smart phone that not only dutifully responds to your voice commands, but also does so without sending data to a cloud – for example, enhances your photos on the fly using locally deployed processing algorithms.
Smart security cameras can analyze video streams in real time, detecting suspicious activity in an instant. This feature will definitely be appreciated in remote or hard-to-reach areas without a reliable internet connection. A device like this can immediately alert users or even turn on the alarm, providing an additional layer of security at your summer place, for example.
In automotive engineering, autonomous AI systems enable the autopilot to quickly respond to changes in the road environment. Imagine your car making its own decisions to avoid an obstacle or stop safely in an unforeseen situation. These capabilities are now possible with local data processing.
In medicine, portable AI-enabled devices can instantly process patient data and issue medical advice. For example, portable ECG monitors can analyze heart rate and detect abnormalities without sending data to a hospital. This is especially important in emergencies or in remote areas where access to medical facilities or to the internet may be limited. AI apps for medical workers can perform complex medical calculations, which usually take over an hour, in a matter of seconds.
Technologies that enable offline AI:
- Edge computing refers to the deployment of AI algorithms directly on local edge devices, reducing reliance on external servers.
- Model compression: Compression techniques such as pruning and quantization reduce the size of AI models to deploy them on edge devices that have low computing power and memory.
- Federated learning enables training machine learning models on decentralized data across devices without sharing raw data, thereby improving privacy and personalization.
Benefits of using offline AI for businesses
- Offline accessibility
Businesses can benefit greatly from the use of autonomous AI models, especially if they operate in remote or hard-to-reach areas where internet access is limited or unreliable. Such systems ensure stable and uninterrupted performance of critical operations without the need to connect to any external IT infrastructure.
- Data privacy and security
With offline AI, data is processed locally, reducing the risk of unauthorized access that can occur when data is transmitted over the internet. This is particularly relevant for industries that deal with sensitive information, such as finance or healthcare.
- Lower data traffic and cloud computing costs
Companies can cut costs by reducing the use of data connections and cloud resources if their data is processed and stored locally. This is a very attractive option for businesses that work with large amounts of information.
Benefits of using offline AI in private life
Offline AI can function as a mini version of the internet, depending on its purpose and on which segments of the internet and query responses it contains. In most cases, this type of AI can replace Google search.
Leading offline AI models
LLaMA 3 is one of the best local and open-sourced models. This model provides excellent opportunities for offline use and does not require immense computing capacities. Other models are often inferior to LLaMA 3 in terms of quality or required resources.
GPT4All offers a convenient interface for operating offline language models. It is essentially a shell for easily downloading and using open-sourced language models. Without this sort of shell, users would have to create prompts manually in code, which is not very convenient.
GPT4All supports the following models:
- Nous-Hermes2
- LLama 13B
- GPT4All-J 6B v1.0
- GPT4All LLaMa Lora 7B
They can be downloaded and launched on a laptop, which allows using AI for routine tasks such as summarizing texts or answering questions on specific topics.
Local model limitations
Offline AI models have their limitations. They can only handle ordinary tasks as they have less data embedded than online models. For example, an offline model can summarize a text or answer questions about a technology stack, but it won’t be able to provide as much depth and details as an online model.
Online models like the ones used by major cloud services are significantly larger in size. This is exactly why they have better knowledge and are capable of processing more complicated prompts. However, they require continuous internet access and may be less secure in terms of data privacy.
How does it work?
Imagine that you have an intelligent robot that can talk to you and answer questions. For this robot to work, you would usually need connection to a large book library via the internet. But what if you want to take this robot to a place with no internet – for example, onboard a plane?
Robot creators can develop a special version that can be downloaded directly to your phone or laptop. This is similar to downloading books from a large library to your device memory so that your robot could read them offline – except only most important books will be downloaded because memory is limited.
Now, the robot can answer many questions using the information from these books even when you are offline. The robot does not know everything like the internet but it can still help you with many questions.
Conclusion
Offline AI systems make a promising service that offers autonomy, security and convenience. Models like LLaMA 3 and GPT4All can easily integrate AI with routine tasks, providing a high level of privacy and responsiveness. Despite some data volume limitations, local models can be an excellent tool for solving many tasks without access to the internet.
By Nikita Tselobanov, CPO, VibeLab