For years, we’ve been reliant on massive cloud-based AI models like ChatGPT. They’re powerful, sure, but they’re also dependent on huge data centres, raise privacy concerns, and can be subject to outages. Cloud-based models and systems are typically centralised and at the moment this makes sense given the processing required for their usage. But its very conceivable that you could in the not so distant future have a local LLM which rivals even some of the cloud based models in terms of capability. Improvements in hardware and tweaks and optimisations of the models could see them running on smaller devices. We’ve already seen this for some time in the Local LLM community – where edge models like 1B, 2B and 4B models have been made available for edge computing. I think that’s the exciting direction Ollama (and other frameworks) and the rise of Open LLMs are pointing us towards. A peer-to-peer world where you won’t be reliant on the Internet to have information available locally and information which you can query using natural language processes.
What is Ollama and what are Open LLMs?
Ollama is a fantastic, open-source project that’s making it incredibly easy to download, run, and experiment with powerful Open LLMs directly on your computer. Think of it as a user-friendly interface for deploying models like Llama (Meta), Gemma (Google), Deepseek, Mistral, and many others. It handles the complexities of setting up and managing these models, letting you focus on using them. Open LLMs are Large Language Models that are released with their vectors and weights publicly available. Unlike proprietary models like GPT-4, you can actually see and understand how these models work. This transparency is crucial for research, development, and building trust.
The implications of running LLMs locally are huge
Running models locally means your data stays on your device and remains private. No sending prompts to a remote server – a significant step towards greater privacy and security. Eliminating the network latency of cloud-based models dramatically improves speed and responsiveness. Imagine a chatbot that answers instantly, without a delay. Offline access means you’re not dependent on the Internet. With Open LLMs, you can fine-tune models on your own data, creating specialized AI tools tailored to your specific needs – so there is plenty of opportunity for experimentation and development.
Perhaps a new Dawn of Peer-to-Peer AI?
Ollama and similar technologies are laying the groundwork for a future where LLM and agents aren’t just on your phone, but potentially connected to a decentralized network and peer-to-peer network of agents on various devices around you. We’re observing trends so far for mobile support where developers are working on bringing Ollama and Open LLMs to mobile devices. It’s not quite there yet for all models, but the progress is rapid. Soon, you might be able to have a sophisticated AI assistant on your phone, without relying on a cloud connection. Projects are exploring ways to connect local LLMs in a decentralised network, creating a distributed AI ecosystems.
Ollama and Open LLMs are more than just a cool tech trend. They represent a fundamental shift in how we interact with AI – a shift towards local, private, and potentially decentralized experiences. Keep an eye on this space – the future of AI is being built right now, and it’s looking incredibly exciting.
Go check out Ollama.
Check out the model library.