What are the best ways to build a network of AI professionals in your area?

Attending diverse events is crucial for expanding your professional network. These gatherings don't need to be exclusively focused on AI; consider events such as Women in Tech meetups, entrepreneurship gatherings, Python workshops or data conferences, which can still draw AI professionals. Tailor your event choices based on your technical expertise. For instance, if you are a business professional, you might find entrepreneurship and tech meetups more valuable, while ML engineers looking to network with other industry professionals could benefit from participating in hackathons. Explore different types and see what events you enjoy the most and the kind of people they attract.

If there aren't any, start them! Some areas have events but they are very top level. Your perspective and experience is useful. Combine your talents with a few other peers and run a class or boot camp that focuses on a skill. This will also establish a reputation as well.

The best way to network with professionals in AI is attending conferences on latest AI advancements. There are many opportunities to be able to network in cities and the best way is to attend events and connect with different people. While attending such conferences always be prepared on what you may be expecting and introduce yourself to others in a professional way. Reach out to people and convey your insights and ask for their insights as well.

Attending local events is a great way to meet other people in your professional network. There are straight up networking events like happy hours, and more learning + networking events like tech talks. If you're looking for local events to get into, check out aicamp.ai for a series of local AI events.

It’s important to visit local events like conferences, meet ups, seminars etc. to build a network of AI professionals. What’s important is to follow up after the event with people whom you met and do some work with couple of them to build a strong connection. It can be writing a paper together or doing a project in personal capacity etc. It also helps to decide on a frequency of attending these events to get into a rhythm and maintain consistency. Else during the periods of high workload we can end up not attending an event for couple of quarters.

During times of high workload I often switch from in person conferences to webinars and podcasts. That gives me more time to do my work and at the same time still remain connected to the AI community. I have also leveraged LinkedIn and found it useful to connect with AI professionals with similar interest areas to learn together, gain insights from each other’s experiences etc.

I advocate for actively participating in forums, social media groups, or professional platforms dedicated to AI. These online spaces are great for connecting with peers, sharing knowledge, and staying updated on industry trends. Additionally, attending webinars, virtual conferences, and online workshops can also provide opportunities to meet and engage with AI experts.

Joining online AI communities offers a unique way to network with professionals in the field. Platforms like Reddit, LinkedIn, and Medium are great for finding active, relevant groups and forums. Engage in these communities by participating in discussions, sharing insights, and learning from others. These platforms are also useful for staying informed about local AI events and opportunities. By being an active member, you not only expand your network but also deepen your knowledge and visibility in the AI community.

Virtual Events are beneficial while we are stuck with multiple deliverables. They give us a fair chance to stay updated on skills while virtually connected with people around the Globe.

I think attending conferences or similar thought leadership groups/committees is a great start. Also, contributing to the community through articles, papers, use case discussions is considered a great help.

The concept of "riches in the niches" is particularly relevant in this context. While AI itself may seem like a specialized field, it's often too broad to stand out. Even a focus on generative AI might not be specific enough. The key is to identify a distinct niche within AI that sets you apart. For example, my approach involves integrating generative AI into local government operations. I share insights through various channels such as LinkedIn posts, a YouTube channel, a course I've developed, and a network I've established. Each of these platforms is sharply focused on exploring and demonstrating how local governments can effectively utilize AI.

Engaging with the audience through comments and discussions can foster relationships with other professionals. Also, consistently producing quality content can establish you as a thought leader in the AI space, attracting a network of like-minded individuals who value your contributions.

What you read you forget. What you create you understand. Write that blog. Reveal your expertise. Believe me, it works. I started content creation 6 months ago and it has been an absolute blast. Today, I am on top of the latest news. I have grown my network and made friends along the way. Find your style and put your work out there. You will be all the better for it.

AI professionals should share knowledge like pheromones in a colony of ants. When one professional discovers something new, they should leave a trail for others to follow. The strength of this "trail" should depend on how valuable the information is. Just as ants optimize their routes based on these trails, AI professionals should collectively improve their field by following and building upon shared insights. This decentralized communication and collaboration should help them navigate the vast landscape of AI, making progress and boosting productivity together.

Contents creation is a great way to meet people. When we create interesting contents about artificial intelligence, we get to link up with really cool folks who are into that stuff. From my own experience, creating that kind of content helped me a lot to connect with professionals using AI and students learning about AI. That led me to learn new things, talk about similar interests, and help a bunch of people. So, it's a great way to grow a network. Also, I noticed that if I make lots of really good and helpful content, I am able to end up building a really good group of connections.

A powerful way to deepen your network is by taking on leadership or organisational roles in volunteer projects related to AI for social good. This approach goes beyond just participating; it involves spearheading initiatives, managing teams, or contributing to the strategic direction of projects. By taking on such roles, you demonstrate your commitment and leadership skills, which are highly valued. Furthermore, these experiences often bring you into contact with a range of stakeholders, from tech experts to community leaders, thereby diversifying and enriching your network. The relationships you build while collaborating on meaningful projects are often stronger and more enduring than those formed through casual networking.

Volunteering for a cause related to AI is an impactful way to build a network of professionals in your area. Contribute your skills and time to AI-focused community projects, events, or initiatives. Volunteering not only allows you to collaborate with like-minded individuals but also demonstrates your commitment to the local AI community. Engaging in shared goals fosters meaningful connections, presenting opportunities to network with professionals who share a passion for AI and a commitment to making a positive impact in your geographical area.

Volunteering is an excellent opportunity to meet like minded people. Contributing to open source is a good way in AI for building networks.

This approach aligns perfectly with my values and professional goals. By applying my skills and time to these causes, not only do I contribute to meaningful projects, but I also gain the opportunity to collaborate with like-minded AI professionals. This experience is invaluable for demonstrating real-world impact, learning from diverse perspectives, and making a tangible difference.

Volunteering with AI-focused social good organizations is both noble and strategic. It puts your skills to work where they're needed and exposes you to a different side of technology's potential impact. When you volunteer, you're not just contributing code or algorithms; you're part of a community striving for positive change. It’s about teamwork and empathy as much as it is about technology. Engage in projects with organizations like AI for Good or DataKind, where the goal is to solve real-world problems. The relationships you build and the experience you gain are unique and can resonate deeply with future employers or collaborators who share your commitment to making a difference.

The trick is not to limit yourself to what is accessible within your current company. Look into the public sites of large enterprises - especially those with externally active Employee Resource Groups (e.g. Deloitte, Microsoft, SAP, etc...). What I have found to be the most effective is to be outspoken. Share your interest and your goals with the people around you. You never know where your closest "multiplier", the person that will introduce you to your best resource, might be hiding.

One of the most wonderful things about the AI community is that the people are always very helpful and hence not being hesitant to reach out is the first step as mostly everyone will help you. I’ve reached out to people for help, and every time I have got what I wanted from this community . Making use of platforms like kaggle and linkedin would get you to the core people who work day in and out on the same stuff you might be having issues with. But please be respectful of their time too while you reach out.

Wir bei brand eins laden regelm??ig Expertinnen und Experten aus unterschiedlichen Bereichen der Entwicklung von künstlicher Intelligenz in die Redaktion ein. Wir diskutieren, um so unseren Wissensstand permanent zu challengen. Ein Fokus dabei sind kleine Anbieter, beziehungsweise Anbieter aus Deutschland. Uns interessiert zum Beispiel, welche besondere Herangehensweise sie mitbringen k?nnen, um mehr Vielfalt in die Entwicklung und Anwendung von Foundation Models zu bringen.

Some of the websites like TopMate has played a pivot role in getting a long term mentorship in space of data science and AI. Mentorship helps individuals in getting a macro view on how to tackle AI projects, how to handle workloads as well as provide more information on how to manage the infrastructure for an AI solution.

Mentors are needed at any stage of life one is in, because, there is always someone who is smarter and experienced in the path we are interested to tread. Mentors save a lot of time, effort and mistakes which we will do otherwise, when doing by ourselves. Mentors help to expand the network.

1. Attend local AI events. 2. Use LinkedIn for networking. 3. Collaborate on GitHub projects. 4. Join AI organizations and university events. 5. Engage in online AI forums. 6. Contribute to open-source AI projects. 7. Attend industry conferences. 8. Connect with AI professionals on Twitter. 9. Participate in hackathons and competitions. 10. Explore AI-related webinars and workshops.

Here are some techniques that have worked well for me: 1. Check that your profile is really clear and easy to understand (tip - remember to include a “friendly” headshot since most people would rather not meet an unapproachable professional) 2. Be generous with what you know - generate your own content or even just by interacting with the content that others create (sharing and re-sharing too where possible) 3. Engage at events or find opportunities to collaborate - and these can be effective either in person or virtual 4. Make your contributions predominantly positive - it is too easy to find faults I hope these help… My books - Making Data Work and Value Driven Data - discuss these and more, should a deeper dive be helpful to you…

Drawing from personal experience, building connections with local AI experts and organizing meetups enriched my knowledge and strengthened my local network. Collaborating within my workplace, sharing expertise, created a dynamic professional environment. Attending key events showcased my leadership and opened doors to new opportunities. Lastly, building relationships by assisting teams fostered a collaborative network within my organization.

Here are some additional tips that I have learned over the years: 1. Be visible - ensure a professional profile on LinkedIn 2. Share knowledge - yours and those of other interesting people you come across 3. Engage - interact with content and contribute to conversations 4. Network - attend events both physical and virtual 5. Follow - helps to stay close to people whose content you find enriching 6. Ask for help - be bold and reach out to people you think might be able to support you 7. Be helpful - be open to helping others and to exchanging ideas Hope these help…

Partner with local businesses that are interested in or are already using AI. Offer to hold informational sessions or workshops to share knowledge about AI applications relevant to their industry.