Justin Diaz:
The AI Conference was an eye-opening experience. I was hopeful about the amazing innovations that could be created with artificial intelligence in medicine, engineering, finance, technology, and art, and I am proud that NJIT is part of this innovation. However, I was alarmed to learn how people and corporations with incredible wealth could unjustly take advantage of those who played a role in this innovation and not give them the credit they deserve.
Speakers at the AI Conference acknowledged the loss of jobs at the hands of artificial intelligence and how to secure a job in this new economy. People can no longer be content being in the middle and doing the same tasks, since the new economy will reward people who come up with new ideas, are passionate about their work, and are not afraid to share their efforts.
Aneri Shethji:
I really enjoyed NJIT’s AI Exploration Day. I attended the 9 a.m. keynote presentation, a breakout session from 10:25–11:10, and the student AI symposium in the afternoon. As a future healthcare professional, I learned how I can leverage AI to my advantage in the research world.
During a breakout session on AI in biomedical research, I asked the panelists whether agentic AI could be used to determine possible new gene pathways in various diseases. The panelists pointed me in a new direction, and I am eager to discover how I can incorporate an AI algorithm into my future research interests. The field of medicine is one of warmth, compassion, and human connection, and AI can never take away those humanistic aspects. However, the field of research is vast and undiscovered, and this is an area where I think that AI will be incredibly advantageous.
Colin Daugherty:
I was surprised by the range of opinions and overall pragmatism at AI Exploration Day. Ethan Mollick’s opening keynote was exactly techno-optimist as I expected, but the “existential dread”-themed talk immediately after was refreshingly bleak and really contrasted the earlier perspective. I liked that most events seemed focused on real-world applications, not just hype. People are scared and confused, and it felt like we were all trying to figure out what the world is going to look like in the next few years.
I wish there was more of a focus on local AI; most people seem to be focusing on cloud models like Claude, Gemini and ChatGPT because they’re the most capable and heavily marketed products. Most people don’t seem to know that they can run small LLMs on their own devices.
There was a breakout session focused on AI’s effects on education that I wasn’t able to go to. I feel like there should have been more of an overall examination of how higher education might change in the future due to LLMs, like if four-year degrees might become obsolete or if only the most passionate will survive in education, but maybe universities are scared to broach that topic.
Justen Steinagle:
Ethan Mollick’s speech was incredibly tight, and he sounds as if he is imitating the LLM’s he spends all day with. I furiously jotted down notes, and I brought his four main principles here to all of you who slept in.
First Principle: Invite AI to everything. You want to cook something new tonight? Invite an AI to help you with suggestions.
Second Principle: Embrace abundance and you curate. If you need to reach a certain goal, ask AI for many iterations and curate from its selections.
Third Principle: Work interactively with AI. He encourages many reattempts. If your first prompt isn’t successful, try, try again.
Fourth Principle: This is the worst the models will ever be, as the AI companies are showing no signs of slowing down with releases and advancements. Hopefully, these principles will serve you as you wander the new AI-infused job market we are all trying to deal with.
