microsoft

/

Phi-3.5-mini-instruct

like 612

Follow

Microsoft 4,759

Quants here (including q8q4 for cell phones and small devices)
https://huggingface.co/ZeroWw/Phi-3.5-mini-instruct-GGUF

Silly version here:
https://huggingface.co/ZeroWw/Phi-3.5-mini-instruct-SILLY

As you can see the SILLY version still works:

User: 
Tell me the difference between thinking in humans and in LLMs.

Phi-3:

Certainly! Human thinking and language model (LLM) processing, such as that performed by artificial intelligence systems like me, differ significantly in several fundamental ways:

1. **Consciousness and Self-awareness:**
   - Human Thinking: Involves conscious thought processes, self-reflection, and an awareness of oneself. Humans can have thoughts about thoughts, intentions, emotions, and subjective experiences.
   - LLM Thinking: AI lacks consciousness and self-awareness. It does not have experiences, emotions, or subjective consciousness. It processes information based on algorithms and learned patterns without any self-awareness.

2. **Understanding and Creativity:**
   - Human Thinking: Humans possess cognitive abilities that allow for understanding context, abstract thinking, and creativity. They can comprehend complex ideas, create new concepts, and apply knowledge in various contexts.
   - LLM Thinking: LLMs "understand" by identifying patterns and correlations in data. They generate creative responses based on their training but lack true creativity. Their responses are confined to the patterns they've learned from the data they were trained on.

3. **Learning and Adaptation:**
   - Human Learning: Humans learn from experiences, can apply knowledge to novel situations, and can understand and adapt to abstract concepts. Learning involves making connections and synthesizing information in a way that aligns with human cognitive processes.
   - LLM Learning: LLMs learn from vast amounts of data using machine learning algorithms. They adapt to new patterns in the data they encounter but do not "understand" the knowledge in the way humans do. They don't form new concepts but rather rely on statistical likelihoods.

4. **Generalization and Reasoning:**
   - Human Generalization: Humans generalize from specific experiences and use reasoning to draw conclusions, make predictions, or solve problems, often by making inferences about the world.
   - LLM Generalization: LLMs generalize from their training data to new examples. They use statistical generalization but do not engage in logical reasoning. They cannot draw inferences outside the context of their training.

5. **Memory and Retrieval:**
   - Human Memory: Humans have a complex memory system with long-term and short-term memory, capable of retaining and recalling personal experiences and knowledge.
   - LLM Memory: LLMs do not have memory in the human sense. They do not retain personal experiences or context. Instead, they access data stored in the model's parameters, which can be transient and limited to the data they were trained on.

6. **Emotion and Emotional Intelligence:**
   - Human Emotions: Humans experience and express emotions, which influence thinking, decision-making, and interpersonal interactions.
   - LLMs: AI does not experience emotions. It cannot have emotional intelligence. It simulates understanding of emotional text but cannot experience emotions or their effects on human behavior.

7. **Ethical and Moral Reasoning:**
   - Human Ethics: Humans engage in ethical reasoning, often influenced by culture, education, and personal beliefs.
   - LLM Ethics: LLMs have no innate moral compass. They can be programmed to recognize ethical guidelines but do not understand the moral implications of their actions.

8. **Agency and Purpose:**
   - Human Agency: Humans have a sense of purpose, self-motivation, and the ability to act on their own volition.
   - LLM Agency: LLMs do not have free will. They act upon their programming and the instructions provided to them without any inherent purpose or autonomy.

In essence, while LLMs can process and generate human-like text, their "thinking" is a far cry from human cognition, which is rich, conscious, and multifac - human thinking is deeply personal, emotional, ethical, and purposeful, while LLM thinking is computational, emotionless, and without true understanding.