How can you network effectively with less experienced AI professionals?

Identifying your goals is an important step in personal and professional growth. When you know what you want to achieve, you can set goals and take action to make them happen. I set my goals as to bridge the AI knowledge between those who know about and it and those who don’t. I do this by - Providing free tutorials on AI tools for those who don’t know how to used it. - sharing valuable updates on group platforms on AI. Remember, if you are not inform them you are misinformed. - offering short courses for those interested

Identifying your goals emphasizes the importance of clarity in one's objectives and adapting communication styles to suit different goals. When aiming to mentor less experienced AI professionals, it's crucial to not only be supportive and patient but also to actively engage in listening. Understanding their aspirations and challenges can help tailor your guidance effectively. Additionally, sharing your own experiences and mistakes can provide them with valuable lessons and build trust. If you are aiming for partnership, it's important to provide opportunities for them to contribute meaningfully, while offering guidance and support. A good partnership starts and ends with mutual value.

Less experienced professionals won't be as keen nor as "into" AI as you are. So to best network with them, you must understand that they don't know as much as you do and are probably less interested in AI than you are. Once you know that, take a teaching stance, be comprehensive, explain and break down concepts. For example, can you explain AGI in one sentence? --> the ability of AI to do any intellectual task that humans can also do. This is how you work less-experienced people.

A master started as a novice at some point. All the experienced professionals should know and reflect on their journey with someone who is starting new. Define goals based on how you started and let your experience reflect on other’s growth.

One effective way of networking is to engage in open-minded conversations and assess the results. Depending on the other person's interests and level of expertise, you can tailor your communication to potentially lead to future collaboration, mentoring, hiring, or simply sharing personal experiences.

In my view, effective networking includes active engagement in mentorship circles on collaborative platforms such as Kaggle and LinkedIn, fostering a supportive environment. Participating enthusiastically in open-source projects, forums, and events, showcasing expertise while collaborating with peers, will be an entity platform. AI competitions serve as valuable arenas for practical networking and teamwork, especially for less experienced AI professionals. Also, it is good to be committed to cultivating genuine interactions to contribute meaningfully to the growth of emerging talents in the AI community.

Linkedin is a great Plattform but so far a workshop or Panel Discussions has the best opportunity inspire interest for AI topics in an organization. Despite that I found coachings or prototypes to be the most effective way to get people excited. Funnily enough AI consultancy is a lot about making others reflect and abstract their workflows to find the best solution for them. Doing that in person has a lot of upsides.

I call that the "ChatGPT-Moment" when suddenly the people understand the cool applications of AI. To get their tailor your communication towards the problems of your audience. It's easy to ramble about acronyms and technical details. It's harder to get them excited to use the tools and technology in a creative way.

Be Authentic! That applies to every aspect of the answer. Communicating your interests while sharing their aspirations and excitement for AI will do more for your relationship and keep you as a memorable connection.

The key to building rapport lies in authentic engagement and adaptability. Demonstrating genuine interest in others' work requires not just active listening but also adapting your communication style to suit their preferences, which could range from formal to informal. Instead of a one-size-fits-all approach, we should tailor our interactions based on the individual's background and professional culture. This includes being mindful of technical language, which can be a barrier in some contexts.

I am currently mentoring a 5 young AI explorers who are just getting to know AI. I meet with him regularly to discuss his progress and to offer feedback on his work. I also help him to identify new opportunities for learning and growth. I also constantly share updates and tutorials on AI tools via my social media channels.

Simplifying information is key. - Helps them grasp concepts better - Encourages a sense of accomplishment - Fosters collaboration as they feel more comfortable engaging in discussions and in seeking help - Makes them better equipped to apply the knowledge creatively to this dynamic field

This is absolutely true. Some few months ago, I recently attended a conference and I met a young AI enthusiasts who was working on a project that I found very interesting. I asked him about his work and we had a great conversation about the challenges and opportunities he was facing. I also offered to give him some feedback on his project and to connect him with other experts in the field.

Offer or seek mentorship to share knowledge and gain insights. Collaborate on projects, contribute to open-source initiatives, and be approachable in your interactions. Share your AI expertise through blogs, presentations, or publications. Participate in webinars and workshops to stay updated and engage on social media platforms. Attend local tech meetups for face-to-face networking. Follow up with personalized messages to build lasting connections. Networking helps you learn, share, and grow together in the AI community.