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Investment in artificial intelligence (AI) is increasing. McKinsey Global Survey An AI study showed that 65 percent of organizations regularly use generative AI, almost double the percentage indicated by the same survey conducted just ten months earlier.
AI has many benefits for businesses, in terms of cost, speed and quality, but it must be implemented in accordance with Changing business prioritiesThese include: managing cloud migration; the need for better security against emerging technologies (including AI); the urgent requirement in some industries to address legacy IT; and Modernize applications; and the digitalization of workflows.
These shifting priorities are leading to an increasingly complex technology environment, and complexity is a problem for businesses: it delays decision-making and increases risk. If not managed properly, it hurts customer loyalty and employee engagement, and ultimately hurts bottom line profits.
Navigating the complexity
There is an urgent need for organizations to address complexity and do so with confidence, so they can become agile, innovative and open to new possibilities.
Central to this process is taking a collaborative approach to problem solving. Instead of pretending that we can solve every problem on our own, we should realize the benefits of working with partners and collaborating within and outside our organizations. This is especially true now that enterprise technology has become too complicated for anyone to handle on their own. Success and progress in today’s rapidly changing technological environment requires a community mindset.
A significant example of community-mindedness is the use of open source software. Millions of developers use open source techniques: the well-known open source software resource GitHub alone has 56 million collaborators.
The reason for this is quality. An open source approach allows organizations to benefit from the best ideas (far more extensive than those available in any one organization). Security, based on the community's extensive experience, is stronger. And system integration is easier because there is no need to develop code in isolation: there is always someone with insight into all systems.
Use open source techniques and you'll never have to risk innovating quickly alone, no matter where you're headed.
Open source for AI
Open source is one of the most important drivers of AI and is where most of the innovation happens. If we combine the power of the statistical algorithms used in AI with the vision, experience and energy of the community’s wisdom, we get something very powerful.
But despite its power, AI needs visionary leaders and strong management. It will never be enough to view the use of AI as an end in itself. AI must address real business problems defined by tangible and realistic goals.
It must also be technology agnostic, meaning it can run in any environment (on-premises, public cloud, private cloud, or hybrid cloud) and on any hardware platform. This is an area where the value of the open source community really becomes apparent: there will always be someone who knows the circumstances under which you are operating. In addition, open source facilitates interoperability of standards.
Accessibility is also important. As well as being easy for end users to use, AI should allow any organisation using it to have direct access to the model. This provides transparency so that people can see their data sources and better assess the accuracy; it also means they can make adjustments to get better results for their business. An example of accessibility is seen with InstructLaba pioneering platform from Red Hat and IBM that enables people to easily train AI models for their own use, while benefiting from the quality offered by an architecture created by IBM and supported by the entire community.
The focus of any AI project should always be on the requirements of the end-user organization, not the options offered by its vendors. Open source helps democratize AI by ensuring it is developed by diverse groups of people around the world, with specific input to address real-world needs, often with smaller, domain-specific models rather than a one-size-fits-all large language model (LLM).
Supporting open source AI
While open source represents a powerful avenue for AI, it is not without its challenges that require careful management. Community members may suggest ideas that have not been tested in the real world, and in some cases software may be developed without sufficient community support to be safe to use.
Therefore, using open source AI effectively requires specialized knowledge on how to manage it in a corporate environment. Red hat It has 30 years of experience in making open source software robust enough for use in the enterprise. This experience with open source AI means that organisations can have the best of both worlds: great ideas originating in a highly creative community, backed by the practical support of an experienced partner.
Red Hat is creating a variety of tools to enable organizations to develop their own digital applications. And AI is central to this. For example, Red Hat OpenShift Artificial Intelligencehelps businesses build, deploy, and monitor AI models and AI-powered applications. Red Hat Ansible Lightspeed uses AI to facilitate the automation of business workflows. And Red Hat Enterprise Linux Artificial Intelligence Provides a flexible and stable operating system that supports AI in a hybrid cloud.
Because Red Hat teams have experience working with large enterprises, they can facilitate community engagement while providing the robust support for open source projects that any large enterprise needs. Red Hat's approach to AI It encourages and facilitates collaboration and this is what distinguishes it from traditional vendors who focus on selling their own pre-existing products.
Collaboration at the heart of AI
Cross-industry collaboration underpins the development of high-quality AI services. By using open-source methods, any company can begin its journey toward effective AI knowing that it will benefit from the experience and expertise of thousands of individual developers and organizations.
You too can benefit from this community wisdom at Red Hat Summit: Connect events, where you can network with your peers and learn about cutting-edge, enterprise-ready technologies based on open source software. These are the places to go to learn more about AI and Red Hat AI products.
Read more about Summit: Connect here.
