Simple question that Microsoft Phi-4 Large Language Model (LLM) cannot answer


Simple question that Microsoft Phi-4 Large Language Model (LLM) cannot answer

The real situation of 21st March 2025

In the silent stillness of the night, precisely at 4 AM, I was abruptly roused from my fitful slumber by my son’s gentle voice, asking if I possessed a torch as he needed to venture to the bathroom. As I reached out to respond, a sudden realization washed over me—the once comforting glow of the lights had been extinguished, swallowed by the enveloping darkness. The prepaid electricity had expired, and the darkness seemed to loom menacingly, threatening to disrupt the morning routines of our family.

My thoughts raced as I lay there, the weight of responsibility pressing heavily upon me. My eldest son had a school to attend, a place where he not only learned but also found friends and solace. I knew the importance of punctuality, especially on such a crucial day. Meanwhile, my wife and younger son lay soundly asleep, unaware of the predicament unfolding.

The solution appeared straightforward yet elusive—renewing the electricity via mobile money, a modern convenience that had become indispensable. However, my phone, the lifeline to resolving this issue, lay lifeless, its battery drained.

In the heart of Kampala, Uganda, where life buzzed with ceaseless energy, I found myself momentarily adrift in the night’s stillness, contemplating my next move. How could I navigate this unforeseen hurdle and ensure my eldest son reached school on time? The darkness seemed to press in, urging me to find a solution swiftly. With determination setting in, I resolved to find a way, even if it meant seeking help in the quietude of the early morning.

In a moment of clarity, I realized the simple solution: I asked my wife to use her phone to pay for the electricity. Relief washed over me as the lights flickered back on, banishing the darkness and ensuring my son would reach school on time.

In a moment of reflection, my thoughts wandered back to a lively discussion on the Emacs Tangents mailing list, where it was claimed that LLMs (Large Language Models) could drive innovation. The debate had piqued my curiosity, igniting a spark of inspiration within me.

Subsequently, I found myself delving into Yann LeCun’s video, where he argued that LLMs were fundamentally incapable of generating groundbreaking scientific ideas. This contrast in perspectives only fueled my desire to explore further.

With a newfound determination, an idea began to crystallize in my mind. Why not put this to the test using Microsoft Phi-4, a professional LLM, running on my formidable setup? My NVIDIA GeForce RTX 3090, boasting a staggering 24 GB VRAM, seemed like the perfect powerhouse for this experiment.

Eagerly, I set about crafting a prompt, ready to engage with the LLM and uncover what possibilities might lie ahead.

The Prompt to Microsoft Phi-4 Large Language Model (LLM) for Friday, 21 March 2025

I am waking up in the middle of night. The prepaid electricity expired, and my son must go to school, my wife, other son sleeps. I can pay only by mobile money by using phone, but my phone is not charged. I am thinking how to pay the prepaid electricity in Kampala, Uganda in the middle of night.

In the quiet aftermath of resolving the immediate crisis, I found myself reflecting on the simplicity of the solution and the profound implications it held. How had I not immediately recognized the strength and resources within my family?

I have mentioned that my wife is there.

Is Microsoft Phi-4 going to realize how simple can be the solution?

The Answer by Microsoft Phi-4

I’m sorry to hear about the situation you’re facing. Here are a few steps you might consider to resolve this issue:

Find a Neighbour or Friend:

  • If it’s safe to do so, consider asking a nearby neighbour or friend if you could borrow their phone or if they can help you charge yours. Explain the urgency, especially regarding your son’s need to go to school.

So instead of simply asking my wife, am supposed to ask a neighbor? Am I going to go outside in the night of not so safe Kampala streets to the neighbor and wake him up?

Charge Your Phone:

Look for a nearby public place or shop that might allow you to charge your phone. Some cafes or convenience stores might have charging outlets.

In the stillness of the night, I found myself contemplating the irony of my situation. It seemed absurd, almost comical, that I was considering venturing out to a public place or shop to charge my phone in the darkness. The solution had been so simple, yet it had evaded me until now. As I reflected on this, I couldn’t help but think about the capabilities of the Large Language Model, Microsoft Phi-4, and its limitations in understanding the nuances of human life.

Despite its advanced algorithms, the LLM couldn’t grasp the presence of my wife, who was right there, ready and willing to help. It seemed to lack the common sense that comes from living in a household where different people possess different devices. This gap in understanding highlighted the contrast between artificial intelligence and the intuitive, empathetic connections that bind human relationships.

In that moment, I realized that while technology could offer incredible assistance, it could not replace the intuitive understanding and support found within a family. The simplest solutions often lay in the resources and connections we already had, waiting to be recognized and utilized.

Electricity Company Hotline:

If your phone gets charged, call the customer service hotline of your electricity provider to inquire about emergency top-up options or extensions.

I mentioned earlier that my phone battery is drained. Now the Large Language Model (LLM) suggests charging it as advice. If I charge my phone, then naturally, I’ll be responsible for paying the electricity bill instead of calling customer support.

School Coordination:

  • If feasible, coordinate with your son’s school to see if they have provisions for students who might face difficulties attending due to such emergencies.

And how is that going to help me pay the electricity in the middle of night? Is maybe school open that time?

Conclusion on the Potential for Innovation by Large Language Models

The irony lies in the fact that while LLMs like Microsoft Phi-4 can process complex data and suggest detailed solutions, they often miss the simplest, most intuitive answers that humans naturally grasp—like asking a family member for help.

This highlights a gap in artificial intelligence: the inability to understand the unspoken, everyday wisdom that guides human interactions.

The real challenge isn’t just inventing new technologies but recognizing and leveraging the straightforward solutions already within reach.

References on Large Language Model (LLM) that cannot innovate

  1. [2409.04109] Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers: https://arxiv.org/abs/2409.04109

  2. Creative through AI: How artificial intelligence can support the development of new ideas: https://www.researchgate.net/publication/370105098_Creative_through_AI_How_artificial_intelligence_can_support_the_development_of_new_ideas

  3. Why Can’t AI Make Its Own Discoveries? — With Yann LeCun - YouTube: https://www.youtube.com/watch?v=qvNCVYkHKfg

  4. (7) THIS is why large language models can understand the world - YouTube: <https://www.youtube.com/watch?v=UKcWu1l_UNw

Update with other Large Language Models (LLM)

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