Here's how you can excel as a top performer in AI.

In the dynamic realm of artificial intelligence, excelling as a top performer demands a blend of technical expertise, adaptability, and a passion for innovation. To thrive in AI, one must continuously hone skills in machine learning algorithms, deep neural networks, and emerging technologies like reinforcement learning and natural language processing. Equally crucial is the ability to collaborate across disciplines, integrating insights from diverse fields into AI solutions that address real-world challenges. Embrace a mindset of lifelong learning!

Learn a little everyday - Subscribe to a few newsletters and read a little maybe 15 minutes every day. Atomic habits build Experiment to learn - For example, when I learn a new topic or tool find a way to use it within my projects immediately Network - Network and talk to these cool AI startups who have done amazing work. LinkedIn is a great way to get in touch with them and learn and also share your perspectives Teach to learn - Break down complex topics into simple understandable and fun way. Teach to learn. Volunteer to write your perspective, teach sessions at forums. Take a topic - Take one topic and delve into it for say 1 hour by using chain of thought prompting. Then summarize your learning into a cool article

It is imperative to understand that leveraging a tool is not the same as building a tool. You can be an excellent driver who knows the road and can get somewhere fast but that does not make you a builder of cars or a mechanic. When we wield AI tools there are some risks of use that are apparent to users, think of prompt injection or output testing as potholes in the road. What we must be cautious of however are the risks tied to the tool itself. Does the car have a weak axel? Do you know what data was used to train the model? All this to say, when you are upskilling be clear about the distinction between using a tool and understanding what is under the hood. We must stop allowing "AI Expert" to be thrown around and be clear on expertise.

Here are some important ways to be a top performer in AI: 1. Master the Fundamentals: Gain a strong understanding of machine learning, deep learning, and data science principles. 2. Continuous Learning: Stay updated with the latest AI technologies. 3. Practical Experience: Work on real-world projects to apply theoretical knowledge and build a portfolio showcasing your programming skills 4. Customer meeting: Drive discussions with customers understand their business problems and provide customised solutions 5. Collaboration and Communication: Work effectively and collaborate with cross-functional teams. 6. Problem-Solving Mindset: Approach challenges analytically, think critically, and devise innovative solutions to complex problems.

Excelling as a top performer in AI involves a blend of technical expertise and soft skills. Continuously updating your knowledge and skills is crucial in this rapidly evolving field. Collaborating effectively with your team and stakeholders ensures smooth project execution. Emphasizing problem-solving and creativity can lead to innovative solutions. Maintaining a growth mindset and being open to feedback helps in personal and professional development. By balancing technical proficiency with strong interpersonal skills, you can stand out as a top performer in AI.

Given the rapid pace at which new papers are published and tools/models are launched each week, it's challenging to stay current. My strategy has been to maintain a categorized list of topics, including models I'm aware of or wish to explore further, ensuring each entry has at least one link for reference. I allocate readiness time to delve into these topics as my list grows. After reviewing a paper or repo, I jot down key takeaways, purpose, pros, cons, similar models, benchmarking, if I tested it... This approach not only helps organize my learning but also serves as a valuable resource for future reference, inspiration, or testing. I've been following this method for three years now, and I can tell you it definitely works!

Read a great newsletter Learn something new every day Take a course on AI/ML each term (learning 30 mins everyday will go a long way) Teach everything you know

Make it a habit to stay informed about the latest industry trends and technologies. Regularly engage with research papers, participate in conferences, subscribe to newsletters and join online forums to gain insights from leading professionals. This proactive approach not only enhances your expertise but also shows your dedication to the field, which is highly regarded by both employers and peers.

In the fast-paced world of AI, staying updated is crucial for success: 1. Create a topic list: Maintain a categorized inventory of AI concepts and models. This organized approach helps prioritize learning and track progress. 2. Allocate learning time: Dedicate regular slots to explore new developments. Consistent engagement keeps your knowledge fresh and applicable. 3. Summarize key takeaways: After studying, note main points, pros, and cons. This practice reinforces learning and builds a valuable reference resource. 4. Engage with the community: Participate in forums and conferences to gain diverse insights and stay ahead of trends. By staying current, you'll remain competitive and innovative in the AI field!

Stay afloat of new research papers and Github repos can be done pretty easily I personally follow the main researchers on Twitter and Linkedin, and of course I check basepub.org all days :)

Tackling problems is key to doing well in AI. Here’s how you can approach it: • Always think about solving problems first. • Look for real-world issues that AI can help fix. • Try out different models and techniques to find the best solution. • Work with people from different fields to solve tough problems. • Share what you learn and create with the AI community to help everyone. This way, you'll make the most out of AI and drive real innovation.

To solve a problem, the first thing we need is strong domain knowledge. AI brings people from different backgrounds together. Doctors, teachers, accountants, and bankers are some of the few professions that work on real-world problems requiring collaboration from AI experts. A top performer in AI needs to 1. understand their POV and frame the problem around that. 2. know that he might not know enough about the problem domain he is working on. 3. work as a team with their collaborators and ask for help whenever required.

To excel in AI, it's not just about technical knowledge but applying it to solve real-world problems. Work on various projects that push you to use AI creatively, which will sharpen your problem-solving skills and critical thinking abilities.

Solving problems is paramount to excel in AI since problems always pop up. I've found this framework to be helpful. With the AI domain knowledge I now possess, I look for real-world problems which can be solved by AI. I define the exact problem and then set objectives. I collect data about the problem. I then select the best model I know will help me based on the data available and nature of the problem. It really boils down to your knowledge of AI tools available and how/where to use them. I'll iterate till I find a solution I'm pleased with. For more complex problems, I collaborate with some of my friends who are also AI experts. I view AI as a second brain, 🧠 and with my two brains now, problem-solving has become easier

Identify real-world problems that is applicable to AI/ML. Build projects, publish your code and results on git-hub. Communicate effectively, and network.

In AI, clear Communication is crucial for learning and for making efficient projects too. It is important on both faces, with the developer team, and with stakeholders too. You can start by defining your goals and objectives clearly and unifying your own understanding so that you can explain it to everyone on their level of understanding. For the developers' team, you can maintain comprehensive documentation for easy understanding and preservation of code flow and development. And for stakeholders, engage them in decision-making to align with business objectives. Simplify technical jargon to make complex AI concepts understandable as they could be from a non-technical background.

Clear communication among stack holder and among team mate is essential for better outcome and no conflict as a business owner or team lead your intention and vision should be loud and clear

Comunicação clara é essencial, no entanto, muitas vezes acabamos escrevendo de forma descuidada e apressada. Felizmente, existem ferramentas de inteligência artificial que podem ajudar a resolver esse problema. Uma solução simples é instalar uma extensão no seu navegador para revisar e aprimorar sua escrita. Pessoalmente, utilizo a extensão gratuita Microsoft Editor e também recomendo a extensão Freemium Linguix. Experimente e veja como essas ferramentas podem aprimorar a qualidade da sua comunicação escrita. O que escrevi acima foi melhorado usando IA.

"4️⃣ Communicate Clearly: Effectively articulate complex ideas to diverse audiences, fostering understanding and collaboration. Develop your presentation and storytelling skills to convey AI concepts to non-technical stakeholders. Use data visualization tools to simplify complex information and make informed decisions"

Your excellence is determined by what you can prove. Simple to understand, but hard to master. Focusing on what matters is crucial. Successfully proving the concept is the true challenge.

I remember a mentor of mine who told me : week has 5 business days, so 5 lunches a week, or 5 opportunities to bond with people casually besides business. You should spend 3 lunches with new people and 2 lunches connecting back with acquaintances, that's how you grow your network. Of course, workout all day otherwise you won't fit in your suits very quickly! :)

In my experience, creating a smart communication network in cyberspace and social networks and among colleagues has a huge impact on promoting the scientific level of the individual, and it also creates a lot of job opportunities and collaborations.

Networking smartly is vital for me as an AI expert because it opens doors to new opportunities, collaborations, and knowledge. By connecting with other experts, I stay updated on the latest trends, tools, and research. These connections often lead to partnerships that can enhance my projects and career. For example, engaging in online communities allows me to exchange ideas and gain insights that I might not encounter otherwise. Networking also helps in finding mentors and mentees, fostering a supportive environment for growth and innovation. It’s all about building relationships that add value both ways. As someone who's just about to start an AI Automation Agency, I've already benefitted from networking immensely.

Don't just add everyone you meet. Seek out connections with people working in your specific area of AI interest, or those with complementary skills. Connect with prominent researchers, industry figures, and active participants in online AI communities.

There’s certainly a crawl, walk, and run happening right now. Crawl The crawl is the ability to use a chat bot for marketing or customer service that enables the business to improve interactions with customers. This is basic and about 65% of organizations have this enabled or are in the process of enabling it (according to McKinsey, 2024). The Walk The walk is where an executive decides to create a smart pricing tool using AI or a recommendation engine to help improve their revenue or margins. This is usually done by partnering with an existing tool like Service Now Assist or Microsoft CoPilot. The Run is just starting to occur as hardware improves...I'll share more in my upcoming article.

"6️⃣ Innovate Constantly: Embrace innovation by exploring new ideas and pushing boundaries in AI technology. Experiment with cutting-edge tools and frameworks, such as PyTorch or GPT-3, to develop prototypes and proofs of concept. Stay curious and open to feedback, iterating on your solutions to achieve greater impact"

Being in this field, I think embracing multidisciplinary thinking is key to excelling as a top performer in AI. Exploring concepts from other domains, such as neuroscience, psychology, and even the arts, can open up new avenues for innovation and breakthroughs in AI. Collaborating with experts across diverse fields, including cognitive science, linguistics, and domain-specific areas, leads to novel solutions. This cross-pollination of ideas sparks creativity and pushes the boundaries of what's possible in AI. By actively seeking out and embracing these interdisciplinary connections, AI professionals can make groundbreaking contributions to the field and create AI systems that are more human-centric, empathetic, and beneficial to society.

Não inove por inovar, se não sabe claramente onde vai aplicar ou qual o real impacto de negócio, provavelmente não fará sentido seguir.

"Innovate Constantly" sounds like a useless platitude honestly. If you are here and working with AI, you are already innovating. You know it's an iterative process of experimentation and feedback. So while you are engaging with this sea change in technology, look to how this technology is impacting human behavior (which any disruptive technology does). Tech moves faster than cultural behavior, so observe the changes happening while you progress in your usage and understanding. The wake left behind can be an indicator to whats coming up next. Then ask better questions.

Early 2023, I decided to leverage generative AI (LLMs, etc.) to enhance my business consultancy, drawing on my extensive experience in the high-tech sector. Recognising the deep pool of highly qualified AI computer scientists & machine learning specialists, I asked myself: How can I excel in this vast field? My answer: leverage my nearly 40 years of experience in Product, Marketing, Sales & Management Consultancy to identify problems & spot opportunities. Further, my ability to code (as a hobby) & by actively learning about AI ethics, safe AI use, & applying my scientific background to stay current with new AI research, is what sets me apart. I aim to harness ALL these "superpowers" to excel in my chosen area within the vast AI landscape.

The most important part of AI people development for me is practice. Since AI is an experiential process, the data from publications does not always work out later in reality, opportunities to experience and practice are very important for development. Definitely more important than reading publications and theoretical knowledge.

If you are interested in AI, then you belong to a minority. The majority of people have not heard of it or are not interested in it. See yourself as a pioneer and thought leader. And defend society from toxic narratives like "it's not an AI that will replace you but a human who uses AI" that deepen social divisions and reinforce narcissistic personalities. You are still very early to be dealing with AI in 2024, but use this head start for the common good.

To be A Top Performer in AI let's understand with example When we ask God For strength He gives us the situation from which we gain experience and through which we become stronger. Talking about this in technical aspects to be the top performer we need to go with the situations (building foundations, collaboration, enhancing connections, Contribute more in diverse aspects, Create numerous solutions to any problem, Be the Risk Taker, Consistency etc) which will not only enhance the aptitude but also contribute more to become the top performer in AI.

It’s a matter of personal preference, but one thing to keep in mind is whether you’re comfortable supplying free content, in the form of group articles like this, to a giant company like LI (Microsoft) so they can train their own LLMs.