2. Understand AI Capabilities:
Familiarize yourself with the different areas where AI has proven successful. Some examples include automation of routine tasks, data analysis and prediction, natural language processing, image recognition, etc. Learning about these capabilities can help you identify how AI can be applied to your specific needs.
There are many resources available online to learn about AI's capabilities, both commercial and open-source. Here are a few that you may find useful:
Hugging Face: a prominent and respected company in the artificial intelligence space, particularly in Natural Language Processing (NLP). They have contributed significantly to the democratization of AI by developing and releasing popular open-source libraries and models. Whether you're looking to deploy an AI solution or simply learn more about NLP, Hugging Face is definitely a platform worth considering.
Other resources include -
1. Coursera: This platform offers a wide range of courses on AI from universities like Stanford and companies like Google. Courses include introductions to AI as well as more specialized topics. Some recommended ones are "AI For Everyone" and "Machine Learning" by Andrew Ng.
2. MIT OpenCourseWare: The Massachusetts Institute of Technology offers a number of free AI courses as part of their OpenCourseWare initiative.
3. Google AI Hub: Google's AI Hub offers a wide range of resources, including machine learning models, tutorials, and articles.
4. Kaggle: A platform for data scientists that offers a wide range of datasets and machine learning models. It's also a great community to learn from others' experiences.
5. arXiv: An open-access archive where researchers share their papers. The site includes a section on AI research.
6. Towards Data Science: A Medium publication covering a range of topics related to data science, including AI.
7. Online forums and communities: Websites like Reddit, Stack Overflow, and Quora have many discussions about AI, its capabilities, and the latest trends.
8. Vendor Websites/Blogs: Many AI solution providers, such as IBM, Microsoft (Azure AI), Google (Google Cloud AI), and Amazon (AWS AI), have resources on their websites. These include case studies, blogs, whitepapers, and webinars that can provide insight into the capabilities of AI and its commercial applications.
9. GitHub: This is a great resource for finding open-source AI projects. You can see the code, understand how these projects have been implemented, and often interact with the community that has developed or is using them.
10. AI Journals and Conferences: Keep an eye on prominent AI journals (like the Journal of Artificial Intelligence Research) and conferences (like NeurIPS, AAAI, ICLR) for the latest high-level research and developments in the field.
Remember, the field of AI is vast and rapidly evolving, so it's important to focus on resources that align with your specific interests and needs. Regularly revisit these resources to keep your knowledge up-to-date.