consciousness

AI & Consciousness, Product Market Fit & Product Growth

December 14th 2023, Esalen

There’s two modes of building products. One is when you are striving to find your center or fit with your self and the audience – commonly called product market fit (PMF). This requires coming up with hypotheses, testing, learning and iterating till you find flow. Sometimes it requires taking big bets to test wide and deep if you are really off center. The other mode is growth of product of self (Product Growth i.e. PG) – this is when you have found your center but you are growing in relationship with your audience. This is akin to play – you give and receive continually to stay in a state of flow but you are growing to expand to a higher state together. 

The two modes require slightly different energies. PMF requires bold action to cut through the noise and find the center. This to me is masculine in nature. PG, on the other hand, requires a more feminine energy to nurture and co-create. 

As humanity we have found PMF with nature or had at some point (hunter-gatherer). What we need next is something more nurturing, to co-create with nature and grow in unison. It requires patience because it looks slow like a pregnancy but it’s happening. Life creation appears slow and then happens all at once. 

Feminine energy is directing and masculine energy can fulfil and support its creation.

An ML model has an objective function, multiple data points and a gestation period which is training followed by a prediction with error rates. 

If we can develop consciousness as a product where we are mindful of what the objective function is and can be present during training with accurate data, and then play with prediction, as response and intention and give and receive feedback, what we can generate is a reality which is true to our objective function. Objective function can be our collectively chosen purpose and desires. If we don’t know our collective purpose, we start with desires and the purpose will emerge.

Neuroscience, Machine Learning and Product Management

December 12th, 2023, Esalen

From as far as back as I can remember, I have been curious about knowing and understanding what it means to be human. My very elementary-level presentation on the topic of philosophy and Turing test from 2005 when I was in undergrad is proof. As is my rabbithole into neural networks and bio-mimicry in 2007 in GITAM. I intuited that the language of understanding and explanation would come through computer technology and machine learning specifically. I evaluated pivoting to Neuroscience after joining the most apt place for machine learning study at CMU. I didn’t because it needed me to redo an undergraduate degree. I did end up studying machine learning and eventually building a career centered around it. The third aspect apart from the human brain & machine learning which had my full attention was product management. The principles of Silicon Valley’s hot and popular career path or more straightforwardly art & science of building products came very naturally to me. You make a hypothesis based on observations of reality, test the hypothesis and use innovative ways of testing that to validate or invalidate the hypothesis. To what end? A hypothesis is a way of learning and inching your way to product-market fit (PMF). PMF is where you find flow. It’s presence. Growth of a product is a natural next step and that requires play. Is the play before and after PMF the same? What works before may not work after. You have more freedom before which requires and allows you to take big bets for hypotheses, however, after PMF it requires discipline, precision, forethought to grow and build. PMF is nothing but the moment in time and space that the model fits. Prediction is perfect. PG is when the product is willing and influencing the market. The model leads and the data follows i.e. prediction precedes reality. These are fascinating concepts and schools of thought which I, and I suspect, other humans, approach life.