How do you promote learning in your AI project?

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Artificial intelligence (AI) is a fast-changing and dynamic field that requires constant learning and adaptation. Whether you are developing a new AI product, improving an existing one, or integrating AI into your business processes, you need to foster a learning culture in your AI project team. In this article, you will learn some practical tips on how to do that, based on AI project management and agile methods.

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Riccardo Zanardelli

Head of Data Science @Beretta | PhD Student in Statistics and Data Science | Engineer | Only personal views here
Mark B.

Producer & Visual Designer ? Tech Expert ? Carbon Neutral

1 Define clear and measurable goals

One of the first steps to promote learning in your AI project is to define clear and measurable goals that align with your vision, strategy, and customer needs. Goals help you focus your efforts, track your progress, and evaluate your results. They also provide a common direction and motivation for your team members, who can see how their work contributes to the overall success of the project. You can use the SMART framework (Specific, Measurable, Achievable, Relevant, and Time-bound) to set your goals and break them down into smaller and more manageable tasks.

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Mark B.

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AI is an industry that is moving at the speed of light. It's important to have a clear goal in mind of what you're trying to build. If a tool doesn't exist yet to get you there, it likely will soon. If it doesn't by the time you're ready to build, there will probably be a software stack that you can start with and then scale from there. The same rules apply. Be obsessed with the problem you're solving and the rest will fall into place.

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Akshit Kandi

GTM @ Salesforce Data and AI
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To promote learning in your AI project, prioritize a culture of continuous improvement and data-driven decision-making. Implement feedback loops for both the model and the team to iteratively refine the project. Encourage collaboration among data scientists, engineers, and business stakeholders to share insights and knowledge. Utilize tools and methodologies that allow for quick experimentation and validation, such as agile development frameworks. By creating an environment that values learning and adaptation, you'll be better equipped to navigate the complexities and uncertainties inherent in AI projects.

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Vlamir Ienne

CEO Grupo iv2 | LinkedIn Top Voice | AI Expert | Digital Creator | Palestrante MBA pela FGV em Tecnologia e Gest?o Negócios
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The AI is faster than our team can keep up with. But I always challenge my team: how can we do this smarter and faster with AI. It's important to get our team to focus on that. The idea is to leave our team open to new possibilities.

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2 Experiment and iterate

Another way to promote learning in your AI project is to experiment and iterate frequently. Experimentation allows you to test your assumptions, validate your hypotheses, and learn from your failures. Iteration allows you to refine your solutions, improve your quality, and incorporate feedback. You can use agile methods, such as Scrum or Kanban, to plan, execute, and review your experiments and iterations in short and regular cycles, called sprints or iterations. This way, you can deliver value faster, respond to changes better, and learn more effectively.

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Mark B.

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In today's world there are so many apps and products to choose from. It's important to stand out from the crowd, but the crowd is one of the best places to try out your new idea. Get it out there, even if it's not perfect. Solve a problem and you'll be amazed at how quickly people will forgive a bad iteration.

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3 Collaborate and communicate

A third way to promote learning in your AI project is to collaborate and communicate with your team members and stakeholders. Collaboration enables you to leverage the diverse skills, perspectives, and experiences of your team members, who can learn from each other and solve problems together. Communication enables you to share your ideas, insights, and findings with your stakeholders, who can provide you with feedback, support, and guidance. You can use tools, such as Slack, Trello, or GitHub, to facilitate your collaboration and communication, and adopt practices, such as daily stand-ups, retrospectives, or demos, to enhance your team cohesion and alignment.

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Mark B.

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It's important to collaborate, especially in a remote environment. However, be mindful of the purpose of collaboration. Is the meeting happening just because or is there something meaningful for everyone to contribute. Could AI help take notes? Could AI round everyone up? Could AI answer phone calls in the meantime? Tech is an expensive industry. In one of my last roles, we assumed that everyone in the meeting was making at least $50 an hour on the low end. If there are 10 people meeting for an hour that meeting is a minimum of $500 for the company - even remotely. It adds up in person when you count meal or snack expenses. Make your meetings worthwhile and utilize AI to summarize and automate when possible.

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4 Learn from data and feedback

A fourth way to promote learning in your AI project is to learn from data and feedback. Data is the lifeblood of any AI project, as it provides the raw material for your algorithms, models, and systems. Feedback is the fuel for your learning, as it provides the information for your evaluation, improvement, and innovation. You can use techniques, such as data analysis, data visualization, or data storytelling, to extract insights from your data and present them in a meaningful and engaging way. You can also use methods, such as user testing, surveys, or interviews, to collect feedback from your customers, users, or partners, and use it to enhance your user experience, satisfaction, and loyalty.

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Riccardo Zanardelli

Head of Data Science @Beretta | PhD Student in Statistics and Data Science | Engineer | Only personal views here
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User feedback is very helpful for improving the performance of nearly every AI model, as it allows to measure the errors in real-time predictions and integrate testing in the pipeline.

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Mark B.

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There are so many tools that provide useful data today. You can utilize AI to A/B test, analyze trends and get best practices from many sources at once. Use these to your advantage and consider training your own language models with proprietary data to exponentially rise above the competition.

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5 Invest in training and development

A fifth way to promote learning in your AI project is to invest in training and development for yourself and your team members. Training and development help you acquire new skills, knowledge, and competencies, as well as update and refresh your existing ones. They also help you keep up with the latest trends, technologies, and best practices in the AI field, which is constantly evolving and advancing. You can use resources, such as online courses, books, podcasts, or blogs, to learn from experts, mentors, or peers. You can also use platforms, such as Coursera, Udemy, or edX, to enroll in formal or informal learning programs, certificates, or degrees.

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Mark B.

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Embrace AI today. It becomes stronger and more powerful every day. Yes, there is good reason to regulate these tools, but don't wait until the dust settles. That will be too late. Learn the tools, encourage growth, take the classes available. A lot of them are free and will enable your team to become one of the best resources in the future while everyone rushes to catch up. Be on the bleeding edge of this exciting tech.

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6 Celebrate and reward learning

A sixth way to promote learning in your AI project is to celebrate and reward learning for yourself and your team members. Celebrating and rewarding learning help you recognize your achievements, appreciate your efforts, and motivate your actions. They also help you create a positive and supportive learning environment, where you and your team members can feel valued, respected, and empowered. You can use strategies, such as gamification, recognition, or incentives, to celebrate and reward learning in a fun and meaningful way. You can also use opportunities, such as events, conferences, or publications, to showcase your learning and share it with a wider audience.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How do you promote learning in your AI project?

1

2

3

4

5

6

7

1 Define clear and measurable goals

2 Experiment and iterate

3 Collaborate and communicate

4 Learn from data and feedback

5 Invest in training and development

6 Celebrate and reward learning

7 Here’s what else to consider

Artificial Intelligence

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How do you promote learning in your AI project?

1

2

3

4

5

6

7

1 Define clear and measurable goals

2 Experiment and iterate

3 Collaborate and communicate

4 Learn from data and feedback

5 Invest in training and development

6 Celebrate and reward learning

7 Here’s what else to consider

Artificial Intelligence

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