What do you do if the rapidly evolving AI industry is leaving you behind?

In my experience, there's a lot of fundamental disruption and a lot of hype around AI which is a little bit easier to navigate by: - following a good newsletter (like "buttondown ainews"). The newsletter itself is AI generated. - looking at top "Huggingface Spaces" for interactive AI demos. - Following people from Huggingface & other smart people who post latest breakthroughs actively on Linkedin.

There's no denying it at this point. AI isn't going anywhere. It's important for everyone to start at least learning and adopting tools now rather than later. The best part is, you don't need to be technical to start using AI! The easiest and most common place to start is no doubt ChatGPT, just start by asking simple questions to familiarize yourself with it, and with each use and update you'll learn more and more. And, if that seems overwhelming, start with a simple YouTube video. I promise it gets more fun the more you try these tools. Keep learning!

I hear weekly at workshops and keynotes that I present at of how people feel like they’re behind and starting from the beginning. Many feel that the ability to learn has passed them by, but no one is an expert at this point. Things are evolving so quickly that even those developing their own models find them obsolete in record time. As such, anyone can “catch up.” It is all about an open-mindset and willingness to change one’s workflow

In my opinion, staying afloat in the AI industry is exactly the same as signing up for a gym membership, where the only way to stay in shape is to keep showing up. You have to embrace the fact that in the world of AI, learning never stops. So I dedicate time every now and then to learning, whether through online courses on platforms like Udemy, webinars that I find interesting, or research papers that are related to what I'm currently studying or working on.

You don't need to and actually your can't learn everything there is to AI. What you can do is choose a niche which to specialize on (mine is combining traditional and AI Art methods to create images, animation and music) or be a jack-of-all-trades-type of infobank, keeping up and sharing valuable trends and information with others. Both are appreciated in the fast-paced field of AI. People need both relevant and current information on a large selection of topics and also trailblazers who are not afraid to try out the latest tools in smaller sections of AI.

If the rapidly evolving AI industry feels overwhelming, focus on continuous learning. Prioritize acquiring new skills through online courses, workshops, and reading latest research. Network with professionals in the field for insights and mentorship. Adapt by finding your niche within AI, and leverage transferable skills to remain relevant and competitive.

As various GenAIs are developing so fast, even the best users are only a few steps ahead of you. What you learn on courses and research papers is already "old news" – so common knowledge that many people know it. So spend majority of your learning time pushing the boundaries of the AI you're specializing in. Also follow people who do the same and are eager to share their experiments as soon as they've done them. 😀

In the fast-evolving world of AI, staying relevant means embracing a continuous learning ethos. Below are some potential steps: • Embrace Change: Recognize the constant evolution of AI. Ground yourself in the fundamentals while staying agile. • Define Your Focus: Choose your AI niche. Stay informed on the latest trends and breakthroughs in that area. • Hands-On Learning: Practical experience is key. Tackle real-world projects, dive into datasets, and contribute to open-source communities. • Network and Share: Connect with peers and mentors. Share your work and insights to establish your presence in the AI community. Adopting this approach will keep you at the forefront of AI innovation, ready to navigate its dynamic landscape.

1. Learning is a lifelong process. Continuous learning is key to remaining relevant and adaptable in the evolving AI landscape. Invest time and resources in acquiring new skills, exploring emerging technologies, and mastering advanced concepts. 2. Enroll in online courses, certification programs, or workshops offered by industry leaders. 3. Leverage hands-on projects, open-source contributions, and collaborative initiatives to apply theoretical knowledge in practical settings.

Life long learning is difficult, but it’s a must in AI. You can’t just complete a course and suddenly you are done learning. Things change continuously. My advice is to focus on the fun parts. What do you live most? Is it music, travel, or maybe sports? Find the overlap between AI and that passion of yours, and continually learn how AI can further the experience.

Look for these things in who to network with: 1) Humility in the face of ever expanding knowledge domains in AI; 2) Specific domain experience with one or a few things instead of "everything in AI" and "end to end service" 3) Ability to change their mind in the face of evidence; 4) focus on client needs and not state of the art Most importantly: Stay as far away as possible from people holding "absolute" opinions. This last bit applies in every field really.

Building a balanced network of AI industry participants will ensure you have an insightful and reasoned perspective to share. Be sure to connect with a range of players including researchers, business leaders, product managers, founders, and end users. You can do this online via LinkedIn and other social platforms, in person at conferences, and by getting involved in events at universities and colleges.

Networking should be active and effective, steering clear of individuals who profess expertise in all AI areas or focus solely on themselves. True networking transcends mere conversation; it involves listening and engaging meaningfully with others. It's not just about accumulating contacts but about building connections with potential business partners, clients, or collaborators who can bring mutual value. Striking the right balance between showcasing your contributions and being open to what others have to offer is key. And never forget that one proper connection may be more important than hundreds of acquintances. One person could help you towards your biggest achievement ever or could be detrimental to everything you built up so far.

Collaboration and Opportunity Generation Building a network isn't just about collecting connections; it's about fostering collaboration and generating exciting opportunities. Actively seek out peers and mentors in the AI industry. Network online through discussions on platforms like LinkedIn or Reddit's r/MachineLearning community. Attend local meetups and conferences to connect with like-minded individuals. By sharing knowledge, collaborating on projects, and staying connected, you'll open doors to new possibilities.

Engage with professionals, experts, and enthusiasts in the AI community through networking events, forums, and online communities. Participate in discussions, share insights, and exchange ideas to expand your knowledge and network. Build meaningful relationships and leverage your connections for learning opportunities, collaborations, and career advancement.

There are plenty of prompting cheet sheets available here in LinkedIn posts and other sources. We generally get better results when we put the effort into setting the proper stage. I typically start with something like "Act as a highly trained [job title] that consults for [my industry or ideal client]. Help me develop an outline for a [blog post, article, ebook, etc] that addresses the concerns of [target audience]". I don't rely on chat GPT to write the content, just provide the structure around topic ideas. Think of chat GPT as the student intern research assistant you cannot afford to hire. They will get 80% of the way towards your finished project. Your expertise and voice are still most imortant.

As a full stack developer, it's relatively easy for me to see what AI is doing under the hood. It really isn't complicated: - The front end interface for chat GPT is rather plain and simple, easily approachable - on the back end, there's a massive store of data that's organized, categorized, and tagged for quick retrieval - the middle tier is where the smoke and mirrors are happening, what makes this feel so overwhelming. This layer consists of a natural language parser that attempts to decipher what you've prompted for. And after data comes back from the database layer, this middle tier again attempts to assemble a natural language response to what it found in the data. Approach your early learning and experimentation with curiosity.

Seek practical experience and hands-on projects to enhance your skills and credibility in the AI industry. Volunteer for projects, participate in hackathons, or contribute to open-source initiatives to gain valuable experience and showcase your abilities. Look for internships, freelance opportunities, or part-time roles to gain exposure to diverse projects and challenges.

There are so many products out there to try out without any software development skills. Even chatting with ChatGPT and analyzing the responses will give you a good idea of how a large language model works.

Adaptability in AI requires professionals to stay updated on new developments, tools, and methodologies. This involves continuously learning and adjusting technical skill sets to meet changing demands. Exploring emerging AI frameworks, programming languages, and specialized domains such as natural language processing and computer vision is crucial. Being open to interdisciplinary collaboration and leveraging insights from different fields is also important for driving innovation.

Embrace adaptability and flexibility to navigate the dynamic nature of the AI industry effectively. Be open to exploring new technologies, methodologies, and applications to broaden your skill set and remain relevant. Embrace change, experiment with different approaches, and learn from failures to adapt and thrive in evolving environments.

Embracing Change as a Superpower The dynamic nature of AI demands adaptability. Think of it as your superpower! Be open to learning new technologies and frameworks and even transitioning to different roles within AI as the industry evolves. Today's hot framework might be tomorrow's legacy system. Embrace this constant change as an opportunity to expand your skillset and stay relevant in a rapidly evolving field.

Be ready to reorient your approach as new technologies emerge. If one AI framework becomes obsolete, learn another. Be flexible to play a variety of roles, from data analytics to software engineering. Embrace change as an opportunity for growth and constant refinement.

Adaptability is essential in the rapidly evolving AI field. Prepare to shift your focus as new technologies emerge. For instance, if your expertise lies in a specific AI framework that becomes less relevant, be ready to learn another. Being flexible also involves considering different roles within AI, from data analysis to software engineering. Embrace change as a chance to grow and refine your skill set.

Strategically planning your career path with a vision of the future is key to not falling behind. Set short- and long-term goals for skills development and career advancement. Keep an eye on in-demand AI applications to align your learning path. Anticipating trends and preparing yourself will give you a competitive edge to stay relevant and valuable.

Strategic Career Planning Taking charge of your career path is essential for long-term success. This means setting clear goals for skill development and aligning them with in-demand AI applications. Is healthcare AI piquing your interest? Then, focus your learning on medical imaging analysis. This proactive approach, or strategic career planning, demonstrates foresight and gives you a competitive edge in the job market.

We are at the tip of the iceberg in the AI perspective. While it may sound overwhelming just consuming large language models like ChatGPT. It is not going to be that simple in the future. More models and architectures are being developed. Papers are the best way to be ahead of the game.

Anticipate future trends, challenges, and opportunities in the AI industry to stay ahead of the curve. Develop a forward-thinking mindset and strategic vision to identify emerging niches, market demands, and areas for innovation. Proactively position yourself for future roles, industries, or applications by acquiring relevant skills and expertise.

Generate some LinkedIn posts using a GPT model. Input your own point of view and start posting on your profile. The Best learning is getting involved in the 'Comments' on Well Known AI advocates ( Andrew Ng or Ruben Hassid are just 2 I follow) Keep asking " If I can do this today....What could this tool be capable of tomorrow or next year" AI is here to stay....It will be a force for good if you make some effort to understand it

Only about 20% of the population has tried ChatGPT, so you're not alone in navigating this new frontier. Stay relevant by actively seeking out opportunities to learn new skills and keep up with the latest AI developments. Your existing expertise and problem-solving abilities can complement the capabilities of AI and create new opportunities. Connecting with others in the AI industry can help you learn, share knowledge, and find new ways to apply AI to your work. The key is to embrace the changes, focus on your strengths, and stay proactive in your learning and development. With the right mindset and approach, you will be the first one using the next-ChatGPT revolution in AI. Remember this: you're not just early. You're the first.

If you feel left behind in the AI landscape keep calm and GPT on! One of the most incredible features of new AI tools is the ability to have a personal tutor that can teach you, coach you, and direct you towards any goal you have including being up to date on AI. Join a community of practice and attend a few webinars to get the most current information.

Instead of getting overwhelmed, consider this fast paced evolution of AI as an exciting professional growth challenge. I would suggest beginning with consistent and active participation in the AI community to keep in the know. Join relevant social media platforms, forums, and groups to gain insights into the current releases, direction and emerging trends. This will lead you to a deeper understanding of how AI technologies are applied across different sectors... and who knows, could even lead to networking opportunities and potential collaborations!

Check with QA leaders, analytic team's leaders (or tools), monetization team, customer service team and product managers what are the specific issues or areas or components that there are problems with and check AI tools that specifically can add value in these arears. Be focus on target and adding values and then stay updated regarding the technologies.

There are very few job roles where AI, used well and responsibly, can't dramatically help improve productivity, reduce costs and foster creativity and innovation. If you're employed in an organisation that's strategically leveraging AI, take advantage of the training, learning and experimental opportunities in your organisation. If your organisation is taking a risk-averse approach to AI, effectively banning it, advocate to senior management that they are making a strategic mistake and instead they need to embrace AI, whilst putting in the necessary safeguards, so that employees can find ways to super power productivity growth, effectiveness and innovations. Take advantage of free and paid learning resources to keep yourself relevant.