I often use GenAI to refine and rephrase my responses, making them more concise and clear. When I find a post that serves as a good prompt, I input it into GenAI to generate a response and label it accordingly. Since not everyone is familiar with AI, I do this to demonstrate that they are already using syntax that GPT can interpret and to show them the types of responses that are possible based on their queries. *final edit of this post was done by gpt-4o-2024-05-13 :)

I’m curious about the nuances of tagging content when using LLM/GenAI. I have an unofficial threshold for tagging: if I were in the reader's shoes, would it be helpful to know or would I want to know if a post was GenAI generated/enhanced? It's similar to identifying sources in a post—we typically assume the poster is the source, but if the information comes from elsewhere, like an LLM, it’s generally helpful to know that, especially if it's something poster can't personally verify. For instance, I don't typically call out when I have GenAI modify a draft, just like I don't mention the word processor or spellchecker used when editing content. I've been using GenAI almost daily since June 2022 and pretty good at spotting AI-generated material. There's way more GenAI content out there than most people realize.

Given the rapid advancements in AI and technology, a multi-year education program might become outdated by the time of completion. Additionally, the financial burden of further education is a significant consideration. With the plethora of online resources available, it's possible to learn relevant skills at little to no cost, aside from the time investment. ### Key Factors to Consider: 1. **Job Market Demand:** - **Research**: Look into the job market for informatics graduates. Determine if entry-level positions typically require just a bachelor's degree, or if a master's is preferred. - **Industry Requirements**: Understand if the industry values experience more than additional qualifications. 2. **Financial Considerations:** - **Debt**: A master's program involves more tuition fees and potential debt. Balance this against potential salary benefits. - **Earnings**: Starting work with a bachelor's degree allows you to earn and possibly save for a master's program in the future. 3. **Timeliness and Technology:** - **Advancements**: Informatics is a rapidly evolving field. Work experience can help you stay current with new trends and technologies. - **Career Path**: Real-world experience can provide clarity on your career direction and specialization. 4. **Real-World Experience:** - **Skill Application**: Applying your knowledge in professional settings strengthens your expertise. - **Networking**: Building professional connections can open up more opportunities. ### Practical Steps to Get a Job as a Fresh Graduate: 1. **Strong Resume and Portfolio:** - Highlight your projects, internships, relevant coursework, and technical skills. 2. **University Resources:** - Utilize career services, attend job fairs, and network through campus events. 3. **Networking:** - Connect with alumni and join professional organizations related to informatics. 4. **Online Presence:** - Create a professional LinkedIn profile and showcase your projects on platforms like GitHub. 5. **Tailored Applications:**

When tackling something entirely new, guided projects can be incredibly beneficial. They offer more than just syntax; they also provide valuable insights into different approaches. Based on your skills and understanding of the project you want to create, find guided projects your are comfortable with that has similar logic, functionality, and interface. Aim for one where you can follow about 80% of the logic. This will give you a solid foundation to build upon, allowing you to customize it to meet your specific needs and preferences. It's always beneficial to have a clear goal for how your project will be applied, based on your ideas. It helps guide your customization and ensure that the final product aligns with your vision and meets your intended purpose.

Nice share. Couple things I like about Ollama: - The Ollama API is compatible with Open AI API - There are a number of smaller less powerful LLMs that can run via Ollama without a high end computer. This opens the door for individuals that want a cost effective (free) way to experiment with local LLMs.