The idea ofartificial intelligence(AI) is not new, but recent advances in related technologies have turned it into a tool used by all of us daily.The growing importance and proliferation of AI is, at the same time, exciting and potentially alarming, because the foundations of many AI platforms and resources are essentially black boxes controlled by a small number of powerful corporations
Large organizations, like Red Hat, they believe thateveryone should have the ability to contribute to AI. Innovation in AI should not be restricted to companies that can afford large amounts of processing power and the data scientists needed to train themlarge language models(LLMs)
Instead, decades of experience in open source for software development and collaboration with communities allow everyone to contribute and benefit from AI, while helping to shape a future that meets our needs. There is no doubt that the open source approach is the only way to reach the full potential of AI, making it safer, accessible and democratized
What is open source
Although the term "open source" originally refers to a software development methodology, he expanded to encompass a more general form of work that is open, decentralized and deeply collaborative. The open source movement now goes far beyond the world of software, andthe open source waywas embraced by collaborative efforts worldwide, including sectors such as science, education, government, manufacturing, health and more
Open source culture has somefundamental principles and valuesthat makes it effective and meaningful, for example
- Collaborative participation
- Shared responsibility
- Open exchanges
- Meritocracy and inclusion
- Community-driven development
- Open collaboration
- Self-organization
- Respect and reciprocity
When open source principles form the basis of collaborative efforts, the story shows that incredible things are possible. Some important examples range from the development and proliferation of theLinuxas the world's most powerful and ubiquitous operating system until the emergence and growth ofKubernetesand the containers, in addition to the development and expansion of the Internet itself
Six advantages of open source in the age of AI
There are numerous benefits to the development of technologies through open source code, but six advantages stand out among the others.
1. Increase in the speed of innovation
When technology is developed collaboratively and openly, innovation and discovery can happen much more quickly, unlike closed organizations and proprietary solutions.
When work is shared openly and others have the ability to create based on it, teams save a huge amount of time and effort because they do not need to start from scratch. New ideas can expand the projects that came before. This not only saves time and money, but it also strengthens the results as more people work together to solve problems, shareinsightsand review each other's work
A broader and more collaborative community is simply able to achieve more: promoting people and connecting expertise to solve complex problems and innovate more quickly and effectively than small and isolated groups.
2. Democratize access
Open source also democratizes access to new AI technologies. When you search, codes and tools are shared openly, this helps to eliminate some of the barriers that normally limit access to cutting-edge innovations
THEInstructLabis a great example of this premise. The initiative is an independent open source AI project that simplifies the process of contributing skills and knowledge to LLMs. The goal of the effort is to allow anyone to help shape theGenerative AI(gen AI), including those who do not have the skills and training in data science typically required. This allows more individuals and organizations to contribute to the training and refinement of LLMs reliably
3. Enhanced security and privacy
How open source projects reduce barriers to entry, a larger and more diverse group of collaborators is able to help identify and address potential security challenges present in AI models as they are being developed
Most of the data and methods used to train and fine-tune AI models are closed and maintained by proprietary logics. Rarely do outsiders of these organizations manage to gain any insight into how these algorithms work and whether they harbor any potentially dangerous data or inherent biases
If a model and the data used to train it are open, however, any interested person will be able to examine them, reducing security risks and minimizing platform biases.In addition, open philosophy contributors can create tools and processes to track and audit the future development of models and applications, allowing to monitor the development of different solutions.
This openness and transparency alsogenerate trust, once users have the ability to directly examine how their data is being used and processed, so that they can verify if their privacy and data sovereignty are being respected. Moreover, companies can also protect their private information, confidential or proprietary using open source projects like InstructLab to create their own fine-tuned models, over which they maintain strict control
4. Provides flexibility and freedom of choice
Although monolithic LLMs, owners and black box be what most people see and think about generative AI, we are starting to see a growing momentum towards smaller AI models, independent and developed for a specific purpose
Thosesmall language models(SLMs) are generally trained on much smaller datasets to give them their basic functionality, and they are even more adapted for specific use cases with domain-specific data and knowledge
These SLMs are significantly more efficient than their larger counterparts, and have shown to perform as well (if not better) when used for the intended purpose. They are faster and more efficient to train and deploy, and can be customized and adapted as needed
And it is largely for this reason that the InstructLab project was created. With him, you can take a smaller open source AI model and expand it with the additional data and training you want
For example, you can use InstructLab to create a highly tailored customer service chatbot developed for a specific purpose, enhancing best practices in the organization. This practice allows you to provide the best of your customer service experience to everyone, everywhere, in real time.
AND, more important, this allows you to avoid being locked into a vendor and provides flexibility in terms of where and how you implement your AI model and any applications built on it
5. Enables a vibrant ecosystem
In the open community, “no one innovates alone“, and this belief has been maintained since the first months of the community's foundation.
This idea will remain valid in the era of AI within Red Hat, leader in open solutions, that will provide various tools and open-source code frameworks in the form ofRed Hat AI,solution with which partners will generate more value for end customers.
A single supplier cannot provide everything an organization needs, you can even keep up with the current speed of technological evolution. The principles and practices of open source accelerate innovation and enable a vibrant ecosystem by promoting partnerships and collaboration opportunities between projects and industries
6. Reduce costs
In early 2025, estimate-it-isthat the average base salary of a data scientist in the United States is over $125.000, with more experienced data scientists potentially earning significantly more
Obviously, there is a huge and growing demand for data scientists with AI, but few companies have much hope of attracting and retaining the specialized talent they need
And the really large LLMs are exorbitantly expensive to build, train, maintain and implement, requiring entire warehouses full of highly optimized (and very expensive) computer equipment and a huge amount of storage
Open models, smaller and built for specific purposes and AI applications are significantly more efficient to build, train and implement. They not only require a fraction of the computing power of LLMs, projects like InstructLab enable people without specialized skills and experience to contribute actively and effectively to the training and fine-tuning of AI models
Clearly, the cost savings and flexibility that open source brings to AI development are beneficial for small and medium-sized enterprises that hope to achieve a competitive advantage with the applications that AI can bring
In summary
For the construction of a democratic and open AI, it is crucial to use the open source principles that enabled cloud computing, the internet, Linux and so many other open technologies, powerful and deeply innovative
This is the path that Red Hat is following to enable AI and other related tools. Everyone should benefit from the development of artificial intelligence, thus, everyone should be able to help determine and shape their trajectory, and contribute to its development. Collaborative innovation and open source are not essential as unavoidable for the future of the discipline
