The AI Framework

Craftsmanship has always been a cornerstone of excellence in human society. Creating something functional, beneficial, and high-quality out of basically nothing using raw materials and tools can seem like magic for passersby. This applies to any craftsmanship if the creator brings a unique set of skills that not everyone can provide.     As engineers, we take pride in our craftsmanship. Our culture is built on a foundation of respect—for the craft and each other. This respect fosters an environment for creativity and innovation. We collaborate, challenge, and celebrate each other's successes, knowing that each triumph is a step towards elevating our collective capabilities.      It's about more than just the final product; it's about the process, the attention to detail, and the standards we uphold from conception to delivery.     We encourage you to do the same, be proud of what you are able to create, and show the same to your peers! 

We are thrilled to introduce Robert Luciani - AI & Data Advisor at The AI Framework, as the Chairman of the upcoming Nordic Data Science And Machine Learning Summit - The most Advanced and Technical Program so far, focusing on Applied and Gen AI, AI infrastructure. Robotics, DSML Platforms, AIOps, MlOps, 🙌 Don't miss out on this incredible opportunity to learn from one of the industry's leading experts. Save the dates: the 23rd and 24th of October in Stockholm! 📅 Stay tuned for more updates and get ready to be inspired by Robert Luciani and other thought leaders at the NDSML Summit. See you there! 😉 https://hubs.li/Q02CB6d50 #NDSMLSummit #DataScience #AppliedDataScience #MachineLearning #ML #ArtificialIntelligence #AI #EnterpriseAI #DeepLearning #DataEngineering #MLEngineering #DataPipelines #BigData #Automisation #GenerativeAI #EthicalAI #TrustworthyAI #LLMs #DataOps #MLOps

𝘼𝙄 𝙞𝙨 𝙩𝙝𝙚 𝙝𝙞𝙜𝙝-𝙞𝙣𝙩𝙚𝙧𝙚𝙨𝙩 𝙧𝙖𝙩𝙚 𝙘𝙧𝙚𝙙𝙞𝙩 𝙘𝙖𝙧𝙙 𝙤𝙛 𝙨𝙤𝙛𝙩𝙬𝙖𝙧𝙚 𝙚𝙣𝙜𝙞𝙣𝙚𝙚𝙧𝙞𝙣𝙜 𝙘𝙧𝙚𝙖𝙩𝙞𝙣𝙜 𝙖 𝙝𝙞𝙜𝙝 𝙖𝙢𝙤𝙪𝙣𝙩 𝙤𝙛 𝙩𝙚𝙘𝙝𝙣𝙞𝙘𝙖𝙡 𝙙𝙚𝙗𝙩 𝙞𝙛 𝙣𝙤𝙩 𝙝𝙖𝙣𝙙𝙡𝙚𝙙 𝙘𝙤𝙧𝙧𝙚𝙘𝙩𝙡𝙮. 10 years have passed since that statement was made, and it is more relevant today than ever. https://lnkd.in/dXMGqHGS On average, tech debt is estimated to amount to 20 to 40 % of the total value of an organisation's technology estate before depreciation. And a majority are experiencing an increase in technical debt over the last few years. We have helped many organisations reduce their technical debt and avoid creating new ones. An anchored AI strategy is key to achieving those results with scalable, repeatable, and modular solutions, regardless if it means replacing older systems or adding an abstraction layer to enhance current usability. An anchored AI strategy provides a common understanding and approach based on a clear, mutually agreed-upon set of rules and principles allowing IT and the business to work together and align on decision-making. Apart from reduced technical debt, organisations with an anchored AI strategy gain several economic benefits compared to organisations without one. Here are a few examples: 𝗘𝗰𝗼𝗻𝗼𝗺𝘆 𝗼𝗳 𝘀𝗰𝗮𝗹𝗲  Best-in-class companies reap a 13% ROI on AI projects, more than twice the average ROI of 5.9%. Why? Companies that develop mature, reusable, and scalable AI capabilities will generate profits, not just media buzz. 𝗙𝗮𝘀𝘁𝗲𝗿 𝘀𝗽𝗲𝗲𝗱 𝘁𝗼 𝘃𝗮𝗹𝘂𝗲 Consistently prioritize AI projects that align with strategy and principles supported by reusable capabilities, templates, connectors, APIs, and cookbooks to see faster speed-to-market and speed-to-value. 𝗥𝗲𝗱𝘂𝗰𝗲 𝗰𝗼𝘀𝘁 Cost decreases from AI adaptation scaled with a 10% increase in 2023 compared to 2022. All while more than 85% of advanced adopters with an anchored AI strategy are reducing operating costs with AI.

We are happy to welcome Andreas Soleiman to the team.  Andreas is not only a fun person to be around with interesting stories to tell, but also brings with him a wide range of knowledge and experience in creating business value through the use of the latest AI tools and techniques. That is evident from his impressive track record in both academia and industry. As an experienced engineer in various domains, Andreas has found his passion for ML engineering with a specialization in generative AI. He has a keen eye for identifying business challenges that can be addressed with AI and providing integrations that leverage cutting-edge solutions based on the latest AI advancements.

It’s crucial to understand that technology is just the tip of the iceberg when integrating AI into large organisations. The real challenge lies beneath the surface of 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 and 𝗮𝗱𝗼𝗽𝘁𝗶𝗼𝗻. While it’s easy to get caught up in advanced algorithms and cutting-edge technology, they constitute only a fraction of what makes AI initiatives successful. Successful organisations with good scaling practices have learned to prioritize differently. They have spent over half their analytics budgets on adoption. This includes updating ways of working, operating model, upskilling staff, and adjusting business processes to fully leverage AI capabilities. The remaining budget is dedicated to technology and algorithms. This ensures a balance between having the right tools and having the ability to effectively use them. It’s not just about having AI; it’s about integrating AI into the fabric of your organisation. The path of successful AI integration is not linear, nor is it solely technologically driven. By understanding this, you are already one step ahead in the game. The goal is not just to ‘have’ AI but to create a symbiotic relationship in your organization where AI can enhance value creation, innovation and cost reduction.

𝗛𝗶𝗴𝗵-𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗔𝗜 𝘁𝗲𝗮𝗺𝘀 There are more than one way to assemble high-performing AI teams as set-ups of roles varies between use cases. We have however learned through experience a number of factors influencing the success of AI teams, no matter the purpose or set-up. 𝗦𝗲𝗻𝘀𝗲 𝗼𝗳 𝗽𝘂𝗿𝗽𝗼𝘀𝗲 creates a shared understanding and commitment to the team’s mission and objectives. It’s crucial for every member to understand why the team exists, what it’s aiming to achieve, and how their individual roles contribute to the larger goal. 𝗢𝗽𝗲𝗻 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻 such as transparent sharing of ideas, feedback, and concerns are key in any high-performing team. This fosters a culture of innovation, allows for quick problem-solving, and helps avoid misunderstandings. 𝗧𝗿𝘂𝘀𝘁 𝗮𝗻𝗱 𝗺𝘂𝘁𝘂𝗮𝗹 𝗿𝗲𝘀𝗽𝗲𝗰𝘁 is the foundation of any successful team. Members should feel confident in each other’s abilities and intentions. Mutual respect ensures that all ideas and contributions are valued, fostering a positive and inclusive environment. 𝗦𝗵𝗮𝗿𝗲𝗱 𝗹𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 is the idea of leadership being fluid, with different members stepping up to lead based on their expertise and the task at hand. This approach leverages the diverse skills within the team and encourages ownership and accountability. 𝗘𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲 𝘄𝗼𝗿𝗸𝗶𝗻𝗴 𝗽𝗿𝗼𝗰𝗲𝗱𝘂𝗿𝗲𝘀 are the agreed-upon methods of working together, including decision-making processes, meeting protocols, and communication channels. Having clear procedures in place ensures efficiency and consistency. 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗼𝗻 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀 as a diverse team brings together a range of perspectives, which can lead to more innovative solutions. The team should value and build on these differences, rather than letting them become sources of conflict. 𝗙𝗹𝗲𝘅𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗮𝗻𝗱 𝗮𝗱𝗮𝗽𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 as AI projects often involve navigating uncharted territory, so the team must be ready to adapt to new information, changing requirements, and unexpected challenges. Flexibility also extends to roles within the team, which may evolve over time. 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 since the field of AI is rapidly evolving, so continuous learning is a must. This could involve regular training sessions, attending conferences, or simply staying up-to-date with the latest research. A culture of learning also encourages curiosity and exploration, which are key to innovation.

You have probably heard the quote “𝘍𝘰𝘭𝘭𝘰𝘸 𝘺𝘰𝘶𝘳 𝘱𝘢𝘴𝘴𝘪𝘰𝘯 𝘢𝘯𝘥 𝘺𝘰𝘶'𝘭𝘭 𝘯𝘦𝘷𝘦𝘳 𝘸𝘰𝘳𝘬 𝘢 𝘥𝘢𝘺 𝘪𝘯 𝘺𝘰𝘶𝘳 𝘭𝘪𝘧𝘦”. Passion can be found in many things, and if you are lucky enough, multiple passions can be combined and transcended. Thankfully for us at The AI Framework, we share a passion for tech and AI that continuously evolve and integrate into more and more areas. Robert Luciani, who has nearly two decades of experience in hands-on development of disruptive technologies in enterprise environments, also happens to be an excellent jazz-fusion composer. On stage at Data Innovation Summit last week Robert shared his knowledge on how to utilize Generative AI for composer project, more specifically for music-video production. Showcasing the power in transcendence of passions. ----- If you missed any panel discussion from the data octagon at Data Innovation Summit moderated by Robert, the two full days worth of content can be found in the links below on Hyperight AB Youtube-channel. Data Octagon Day 1: https://lnkd.in/d9NtNdJb Data Octagon Day 2: https://lnkd.in/daF3_pjf

𝗛𝗼𝘄 𝗱𝗼 𝘄𝗲 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗲 𝘁𝗼 𝘀𝗰𝗮𝗹𝗲 𝗼𝘂𝗿 𝗔𝗜 𝗶𝗻𝗶𝘁𝗶𝗮𝘁𝗶𝘃𝗲𝘀? A 𝗰𝗲𝗻𝘁𝗿𝗮𝗹𝗶𝘇𝗲𝗱 way of organizing is good to start with to build core competence. At one point however, the way of working will become dependent on centralized resources and won’t be able support much more than regulatory work and does not scale. A common and great second step is adopting the 𝗛𝘂𝗯 𝗮𝗻𝗱 𝗦𝗽𝗼𝗸𝗲 model that provides a higher level of maturity and lets business drive change and value creation. The hybrid blend of central and decentral ways of organizing that hub and spoke provide have the potential to scale by having a centralized team enabling embedded AI teams within different business units. We have in several cases supported our client in achieving that ability to scale. To succeed, there needs to be a joint operating model for distributed teams to enable scaling of current operations. The operating model should include long-term target states and how to transition to them. This can be accomplished by defining capabilities according to people, process, and technology as well as their perspective target state in a central, decentral, or shared perspective. The central team (hub) of AI experts maintain core AI capabilities, set standards, and ensure best practices. All while embedded AI teams (spokes) can leverage the capabilities to deliver specific AI solutions tailored to their unique needs. Some changes we have seen amongst our clients: 𝗜𝗺𝗽𝗿𝗼𝘃𝗲𝗱 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆: Efficient data transfer and communication. The central hub develops and maintain AI models and tools that are being reused across different projects, reducing duplication of effort. 𝗕𝗲𝘁𝘁𝗲𝗿 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝗢𝘃𝗲𝗿 𝗗𝗮𝘁𝗮 𝗙𝗹𝗼𝘄: The central hub ensuring that data is managed and used appropriately across all projects, enhancing data governance. 𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆: The hub setting and enforce security protocols, ensuring that AI models and data are used securely. 𝗖𝗼𝗵𝗲𝘀𝗶𝘃𝗲 𝗖𝘂𝗹𝘁𝘂𝗿𝗲: Despite the decentralization, the hub helps to ensure a cohesive culture and consistent practices across all AI projects. 𝗖𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴: The embedded teams learning from the hub and build their own AI capabilities over time.

Robert Luciani has visited Oslo and Copenhagen together with WorkShop The Consumer Experience Agency and held talks on AI and practical measures to start with a big impact. Robert shared insights on how AI can revolutionize business operations to create a competitive edge, and practical measures organizations can take to start their AI journey. Let’s break down the complexities, and provide actionable steps that you can take to start reaping the benefits of AI with maximum impact.

Errol Norlum recently delivered a talk at Stellar Capacity on the topic of AI-driven transformation. The talk covered topics such as successful ways to implement AI, fostering an AI-culture, and building an AI-ready organization. We synthesize knowledge gained by walking the walk, and believe in knowledge sharing and inspiring others to achieve great things. If you’re interested in learning more about successful real-world applications of AI, please get in touch. Let’s uncover the power of AI together!