The Importance of Learning and Its Parallel in Artificial Intelligence
From Pixels to Patterns: Understanding Learning in Humans and AI
At Neuro Evolution, our mission is to unravel the complexities of artificial intelligence, making it accessible and comprehensible for all. Understanding AI’s mechanisms and potential is paramount for its ethical and advantageous deployment in society. Our goal is to foster a community where curiosity leads the way in exploring AI’s possibilities, ensuring a future where technology is harnessed responsibly and beneficially for humanity. Together, let’s embark on this enlightening journey of discovery, where every step is guided by a shared vision of progress and responsible innovation.
The Importance of Learning: Pixels on a Screen
Imagine learning as pixels on a screen. Each time we learn something new, it adds another pixel to our understanding of the world. The more we learn, the clearer and more detailed the picture becomes. This enhanced understanding allows us to form well-informed opinions and shape the future more effectively. Just as a high-resolution image provides clarity, a well-rounded education and continuous learning enable us to navigate the complexities of life with greater precision and insight.
Just as diverse data, in this case pixels, is crucial for enhancing the accuracy and robustness of computer vision models, diversity within organizations is equally vital. Agile teams composed of individuals from various backgrounds can tackle complex problems more effectively. This is because, much like overlapping pixels in an image to create a clearer and more detailed picture, diverse perspectives in a team overlap and integrate, leading to innovative solutions and improved outcomes. Embracing diversity ensures that a wider range of ideas and experiences are brought to the table, fostering a culture of creativity and resilience.
How We Learn: Neurons and Synapses
Learning is a fascinating process. When we learn something new, our neurons—the brain's fundamental units—come closer together. This physical proximity strengthens the synapses, or connections, between them, making it easier for signals to pass through. Visualizing this, we can see how new knowledge leads to a more interconnected and efficient neural network. The videos below beautifully illustrates
image credit: Yale baby school
Next time, don't be too hard on yourself when you are learning something new, whether it's AI, parenting, or CrossFit. Just remember that your synapses are forming connections. You will get better at it soon!
The Parallel in Artificial Intelligence
This biological process has a remarkable parallel in artificial intelligence. In AI, the "neurons" in neural networks connect with one another during the learning process. However, unlike our biological neurons, these AI connections are not physical. Instead, they are mathematical, governed by the "weight parameters" that represent the strength of the connections.
When an AI system learns, it adjusts these weight parameters. Higher weight parameters indicate stronger connections, akin to neurons being closer together. These strong connections signify that the AI has found meaningful relationships among the features or attributes in the data set, much like how our brain strengthens synapses when we understand new concepts.
image credit: 3Blue1Brown - What is a neural network?
Traditional AI: A Diligent Student
Traditional AI can be likened to a diligent student who learns from data. It memorizes facts, answers questions, and recognizes patterns. For example, traditional AI can identify objects in images, such as detecting cancer in histology images, enhancing diagnostic accuracy and aiding medical professionals.
Generative AI: Creativity Unleashed
Generative AI, on the other hand, has been trained on vast amounts of data and can generate new information. As mentioned in our last newsletter, large language models like GPT-4, Gemini, and Claude can generate text, write articles, code, and help users solve problems, thereby fostering creativity. Models like MidJourney and DALL-E generate and modify images based on text prompts. These models can also describe images, offering innovative applications across various fields.
Spotlight on PathChat
PathChat is an innovative example of generative AI. PathChat is a versatile and interactive AI copilot that can work with both visual and natural language inputs. It can have important uses in pathology education, research, and clinical decision making with human input. Built by adapting a foundational vision encoder for pathology and combining it with a pre-trained large language model, PathChat was fine-tuned on over 456,000 diverse visual language instructions. It produced more accurate and pathologist-preferable responses to pathology-related queries, showcasing the potential of AI in specialized fields.
image credit: Dr. Faisal Mahmood lab
The Excitement of Technological Advancement
Why is this extremely exciting? Throughout history, writing and drawing have been our primary methods for passing down knowledge. As technology advances, we can capture and communicate knowledge more effectively. Retiring professionals, such as physicians and researchers, can now pass on their vast experience to the next generation, enabling continuous progress.
Envisioning the Future
What does the future look like 50-100 years from now? While we cannot predict with certainty, we know that these technological advancements will have an exponential impact on our lives. As we move forward, let us hope that humanity continues to treat each other with respect and empathy, recognizing the unique value of both human and artificial intelligence.
Stay curious, stay informed, and let’s evolve together.