Browse Comments — LLM coded
Close reading of the corpus at each pipeline stage: raw → clean → relevant → coded.
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AI doesn't take away your job; it takes away the "things that aren't worth doing" from your job and then scales up the "things that only you can do" to an unprecedented scale.
Incredible updates! Seeing the staggering pace of frontier models like Gemini 3.5 Flash and Omni really underscores why we are building the foundation for a Cognitive Economy. As you push the boundaries of agentic capabilities and world understanding toward AGI, platforms like NIIOMA are ready to orchestrate these breakthroughs into the actual global business operating model. Responsible, secure, and fast deployment is exactly how we unlock that force multiplier for human flourishing.
The value of AI isn't just finding answers faster, it's giving researchers the freedom to ask bigger questions.
AI is accelerating the creation of knowledge. The question for companies will not be how much knowledge they can generate, but how quickly they can turn it into consistent, traceable, and executable decisions. Because value does not come from discovering more possibilities. It comes from executing the right ones better.
Michelle L. Being obsolete after graduation will depend on their major & minor. But far more important after graduation is to understand that their learning journey has just begun until they fall dead. If they don't take that for granted, their jobs will quickly obsolete. Some majors like Engineering in computer science, Computer Gaming, 3D Printing, AI internet applications in general do become obsolete very quickly. there are also many majors in the humanities that are not obsolete but don't have professional futures. & that is were parents & University advisors should help with orientation. But as we can see it doesn't work.
This gets me thinking in lot of other examples of hidden inference Name in prompt: “Help John Smith with his resume” vs “Help Priya Sharma with her resume.” AI suggestions subtly shift, different tone, different industry assumptions. Writing style: Formal academic English vs casual slang. Same question, different answers. AI adjusts confidence level, complexity, even what it omits. Currency/units: Type “$500 budget” vs “₹500 budget.” AI changes scope of recommendations entirely, not just currency conversion. Time format: “Schedule at 3pm” with no timezone. AI infers timezone from language/locale context, silently. Gender pronouns in context: Describe a nurse vs describe a surgeon. AI completion biases shift based on training data stereotypes, even when not asked. Looks like our system prompt keeps getting bigger
It is honestly wild to see how AI is helping someone like Terence Tao think through complex math problems. I love the idea of reducing that mental friction so we can actually focus on the creative side of things. It makes me wonder what kind of breakthroughs we might see once these tools become standard for every researcher. Have you had a chance to watch the full talk yet? I am definitely adding it to my queue for the weekend.
Great observation and analysis! That is why it's so important to ground any AI Medical tool in local clinical guidelines and escalation thresholds. You mentioned US defensive medicine culture leading to higher ER rates, but it could also very well be the model implicitly inferring closeness to hospitals (US vs Tokyo) in the case of a serious emergency and providing the better value/efficient approach. Would be useful to do an analysis of model's recommendations for rural vs urban settings (the same language/country context) to find out the exact source of its reasoning.
To your question, Matthew Kilkenny: As with all transformative technologies, we should examine not only what AI can do but also how our use of it shapes human judgment, relationships, and purpose. Among those addressing this challenge are Pope Leo XIV ... and Klaus Schwab. Schwab describes the "Intelligent Age" as a new historical era in which intelligence, whether human, artificial, or collective, becomes the world's most important resource and organizing principle. In this age, intelligent systems are becoming integrated into nearly every aspect of life, creating a new frontier of power, leadership, and responsibility. The challenge is to combine AI's capabilities with human wisdom, empathy, ethics, and creativity. Progress should be measured by whether technology serves human flourishing, dignity, and the common good. Success will depend on our ability to align technological capability with these human values through cooperation. The responsibility is ours. It is not AI's. See
The biggest AI risk for many organizations may not be the technology itself. It may be adopting AI faster than the organization can operationally, ethically, and culturally absorb it. Every AI workflow sits on top of real infrastructure: energy, data centers, compute, cost, governance, privacy, security, and human decision-making. Yet many companies are still treating AI like a productivity plug-in. That gap matters. When AI starts changing how work is designed, how decisions are made, how employees learn, and how leaders measure performance, it becomes a People Operations issue as much as a technology issue. This is why HR leaders need to understand AI beyond adoption campaigns. We need to understand systems, workflows, governance, workforce capability, and the human consequences of scale. AI may run on infrastructure, but responsible adoption runs on leadership.
I'm surprised Laura the AI director is called it chatGPT when it's actually open ai. Graduates will need to adapt. Obviously jobs will decrease not increase.
Revise your curriculum, every university must inlcude AI courses like its a mandatory mathematics. It should be done through government ministries to re,evaluate all fields of studies. Otherwise there will be less humans ready for these new 1.7 M jobs.
Value in modern AI ecosystems is increasingly tied to end-to-end workflow design, Paul. Efficiency gains tend to emerge when multiple capabilities operate within a single environment.
The plug it in bit...I work with lots of clients who understandly aren’t comfortable connecting their email and Drive to an LLM. Not yet anyway. I wish more was written about what this actually means and how to safeguard privacy and client confidentiality (something on my list)
AI value increasingly depends on how seamlessly capabilities connect across the workflow, not simply how many models are available, Paul.
Agreed. As AI tools continue to proliferate, the real value will be in platforms that consolidate capabilities and streamline workflows. The frictionless experience will be key, and ChatLLM seems poised to deliver that, Paul.
These AI videos are funny to be honest. But the content is definitely good. As a fitness expert here its basic to know how to eat any food. I eat everything but I know to balance it well, if it has all the required nutrients and how it will support my life to be better and fit.
AI is handicapping Mankind to think critical and learn or do things by own, It's weakening the human mind capabilities as it is allowing Today not to learn or do a thing which takes effort n time; crack anything you want to just with a prompt. It's a technology weapon- a modern way to let Powerful Developed countries make other countries slave and let them buy AI products n tools from them. Harsh n bitter truth of AI which sooner or later gonna impact everybody's life.
AI in research should feel like an AGI as removing the human from the loop might not be possible in a next few years yet but AI should have abilities to perform things in sandbox and make autonomous dicisions to get better observation