CIONET is launching 'CIONET Trailblazer' as a series of interviews with leading digital executives among its members and partners. The objective is to get a glimpse of their vision and thought process on topical subjects within the world of ICT. Leading off the series is Davio Larnout, CEO of Radix, commenting on the current state of the AI industry, which he believes is at a pivotal moment.

How do you appreciate current breakthroughs like OpenAI and ChatGPT for AI? Have we reached a real tipping point for AI to go mainstream?

1. MLOps: MLOps, or Machine Learning Operations, is a set of practices that enables businesses to build, deploy, and manage machine learning models at scale. It involves using automation, collaboration, and monitoring tools to streamline the machine learning workflow. We believe that MLOps is important because it allows businesses to operationalize AI, making it more reliable, scalable, and accessible. This can lead to significant improvements in efficiency, accuracy, and cost savings.
2. Foundational Models such as LLMs: Foundational models such as Language Models (LLMs) are pre-trained AI models that can be fine-tuned to perform specific tasks. These models, such as GPT-3 from OpenAI, are already superpowering various applications and enabling breakthroughs in NLP and other fields. We believe that foundational models are important because they provide a solid base for building new AI applications and reducing development time and costs.
3. AGI: AGI, or Artificial General Intelligence, is the ultimate goal of AI research, aiming to create machines that can think and learn like humans, perform any intellectual task that a human can do, and adapt to new situations. Although we are still far from achieving AGI, we believe that it is important to focus on it because it represents the light cone of all future value. The journey towards AGI will require us to develop many AI solutions across our organization, superpowering our people and transforming every industry.
4. AutoML: AutoML or Auto Machine Learning is a set of tools and techniques that automate the process of building, testing, and deploying machine learning models. This technology trend is important because it allows organizations to leverage the power of AI even if they don't have a dedicated team of data scientists and machine learning experts. By automating the process of building and deploying machine learning models, AutoML enables organizations to accelerate their AI adoption journey and reduce the time and resources required to develop AI solutions. This can be especially important for small and medium-sized enterprises that may not have the same resources and expertise as larger organizations.

1. Setting clear goals and expectations: We establish clear goals and expectations for our team and communicate them effectively. This provides our team with a clear understanding of what is expected of them and what they need to accomplish to achieve success.
2. Encouraging creativity and innovation: We encourage creativity and innovation among our team members. This involves creating an environment allowing experimentation, taking calculated risks, and challenging the status quo. We believe that this mindset fosters a culture of continuous learning and improvement.
3. Tolerance for failure and intolerance for incompetence: We have a tolerance for failure, knowing that this is often a necessary step in the learning process. However, we also have an intolerance for incompetence.
4. Willingness to experiment with rigorous discipline: We are willing to experiment with new ideas but also maintain rigorous discipline in our approach. This means measuring and analyzing results, identifying areas for improvement, and making data-driven decisions.
5. Psychological safety with brutal candor: We create a culture of psychological safety where team members feel comfortable sharing their thoughts and ideas. At the same time, we encourage brutal candor, where team members provide honest and frank feedback to one another.
6. Collaboration balanced with individual accountability: We value collaboration, but we also hold each team member accountable for their individual contributions. This ensures that everyone does their part to achieve the company's goals.
7. Flatness with strong leadership: We maintain a flat organizational structure, which allows for open communication and collaboration. At the same time, we have strong leadership in place to guide the team and ensure that everyone is aligned with the company's vision.
8. Providing opportunities for growth and development: We invest in our team members by providing opportunities for growth and development, such as training and education, mentoring, exposure to new projects and challenges, and more. This helps our team members feel valued and engaged, and it helps us attract and retain top talent.
9. Recognizing and rewarding achievement: We recognize and reward our team members for their achievements and contributions. This can take many forms, including bonuses, promotions, public recognition, thank-you notes, etc. Recognizing and rewarding our team members is key to maintaining a positive and motivated team culture.
10. Creating a positive and inclusive culture: We strive to create a positive and inclusive culture where everyone feels valued and respected. This involves promoting diversity and inclusivity, fostering open communication and collaboration, and prioritizing work-life balance. We believe that a positive and inclusive culture is key to maintaining a motivated and engaged team.