Building for Believers: How Deep Neural Networks Help Explain Living Brains

Building for Believers: How Deep Neural Networks Help Explain Living Brains

In the world of community building, there is a key principle: the more committed a member is, the more they contribute to the community. This concept, known as "Building for Believers," emphasizes the importance of gradually increasing a member's commitment level over time. By starting with low barrier asks and incrementally increasing the level of commitment, community builders can generate greater rewards and engagement.

Meetup and Airbnb are prime examples of companies that have successfully implemented this principle. Instead of immediately asking new members to take on significant responsibilities, these platforms first ask them to complete smaller tasks. For instance, Meetup asks new members to read a blog post and attend an event before becoming a host. Similarly, Airbnb encourages new members to watch a video about how the platform works and then try booking a stay. By starting with these smaller asks, these companies increase the likelihood of members saying yes to larger commitments later on.

To effectively implement "Building for Believers," it is crucial to find Community-Member-Fit (CMF). CMF occurs when members consistently provide meaningful value to each other without being prompted. Rather than copying the current workings of established communities, it is more effective to copy how these communities started. Meetup and Airbnb began by focusing on the actions at the top of the commitment curve and targeting the biggest believers in the world: themselves. To find CMF, start with individuals who already have a high level of commitment and are actively trying, but unsuccessfully, to do what your community offers. These individuals should only need convincing to do it with your community.

Contrary to popular belief, starting a community does not require a massive number of people. In fact, all you need are 10 true believers. Rather than seeking out the most successful organizers or conference hosts, find the small organizers who still need assistance. These individuals possess the motivation but have not yet achieved success. By offering your help, you can bring them into your community and foster their commitment.

Now, let's shift our focus to deep neural networks and their ability to explain living brains. Deep neural networks are computational devices inspired by the neurological wiring of living brains. Researchers have discovered that these networks can replicate human abilities, such as recognizing objects in pictures or classifying speech and music.

One key insight from computational neuroscientist Daniel Yamins is that deep neural networks process features hierarchically, much like the brain. In the brain, the earlier stages of visual information processing handle low-level features, while complex representations of objects and faces emerge later in the cortex. Deep nets emulate this hierarchical processing and aim to reflect learned associations, similar to how the brain adjusts the strengths of connections between neurons.

Researchers have found that deep nets designed to recognize faces perform poorly when tasked with recognizing objects, and vice versa. This suggests that these networks represent faces and objects differently, similar to how the brain segregates the processing of faces from other objects. The deep net's internal organization spontaneously segregates the processing of faces and objects in later stages, mirroring the functional specialization seen in the human brain.

Deep neural networks also show promise in explaining the perception of smells. When researchers trained a network to classify simulated odors, they discovered that the network's connectivity closely resembled that of the fruit fly brain. This similarity suggests that both evolution and deep nets have converged on an optimal solution. Future studies will aim to evolve deep networks that can predict the connectivity in the olfactory system of unstudied animals, which can then be confirmed by neuroscientists.

While deep-net models provide valuable insights into brain functioning, they are not without limitations. These models often require large amounts of labeled data for training, whereas our brains can learn from just a single example. Additionally, deep nets utilize an algorithm called back propagation, which many neuroscientists believe cannot work in real neural tissue due to the lack of appropriate connections.

Cognitive neuroscientist Josh Tenenbaum notes that while deep-net models represent progress, they primarily excel at classification tasks. Our brains, on the other hand, do more than merely categorize what's out there. They use generative and recognition models to not only recognize objects but also infer the causal structures present in scenes.

In conclusion, "Building for Believers" and deep neural networks provide valuable insights into community building and understanding living brains. To effectively build a community, start with individuals who already have a high level of commitment and are actively seeking what your community offers. Gradually increase their commitment level over time to generate greater engagement. Similarly, deep neural networks offer a glimpse into how the brain processes information, particularly in relation to object recognition and sensory perception. While these models have their limitations, they contribute to our understanding of the complex workings of the brain.

Actionable Advice:

1. Start with a core group of highly committed individuals who are already seeking what your community offers. These "true believers" will help jumpstart your community and attract others.
2. Gradually increase the level of commitment required from members. Begin with low barrier asks and incrementally introduce more challenging tasks. This approach will generate greater engagement and rewards.
3. Seek out individuals who have the motivation but have not yet achieved success in their endeavors. By providing assistance and support, you can bring them into your community and foster their commitment.

By implementing these actionable advice, you can effectively build a thriving community and gain insights into the workings of living brains.