Baby Steps

How does a machine learning/AI model learn?

By taking baby steps. Machine learning/AI is an extraordinary application of calculus at the heart of which is the infinitesimal increment. This allows the models to learn by taking gradual, incremental steps, similar to a child's learning process.

Any profound change often occurs through small, gradual, and unnoticeable steps. Relatives who didn't see you often were always shocked at how much you'd grown, but your parents, who saw you every day, barely noticed the difference. The bestselling book "Atomic Habits" champions the idea of making small, incremental changes to achieve significant personal development and transformation over time.

A foundational principle in economics is that “rational people think at the margin”. This means that they make decisions by considering the incremental or additional benefits and costs of a particular action, rather than evaluating the total benefits and costs. They analyze how a slight change in their current plan will affect their overall well-being and choose the option that maximizes their net benefit.

Startup founders often have ambitions to disrupt industries with their groundbreaking products. However, the adoption of even revolutionary products like ChatGPT is a gradual process. Initial validation comes from early adopters, followed by acceptance from the mainstream market. This gradual adoption curve is a natural phenomenon, reflecting the inherent conservatism of the market and the time it takes for new ideas to become established. Early adopters who are willing to take those initial small steps towards embracing new technologies position themselves at the forefront of innovation.

Product-Led Growth is attained through incremental adoption, continuous improvement via feedback, and gradual feature releases. User onboarding with manageable steps and metrics analysis are key to identifying areas for improvement. Sticky products initially hook the user, and then prioritize a seamless and enjoyable experience to drive continued and incremental use. For example, ARNAB MUKHERJEE from our team is progressively integrating our influencer marketing platform into the workflows of marketing agencies and supporting them through the process.

During my early career, I worked as a data scientist, primarily as an individual contributor. However, starting a company requires one to be a jack of multiple skill sets, if not a master of them. My co-founder Rajesh Jagasia encouraged me to start a venture together with a vision of connecting businesses and creators and helping businesses with marketing. Back then, I had little knowledge of sales, marketing, team management, task management, hiring, fundraising, content creation, social media, product development, accounting, and design. I thought to myself, "There is only one life, why specialize in only one field?" and decided to start learning all of them bit by bit, whatever the moment demanded, by taking baby steps.

vHub.ai has a successful history of hiring interns who quickly become integral team members.? Shivam Keshari and Aniket Tiwari , for example,? mastered influencer marketing and now manage numerous influencer-brand collaborations.? Similarly, Shaina Bhardwaj and Ishita Joshi transitioned from intern roles into key positions within product development.? They were quick in taking baby steps and acquiring specific knowledge of their domains.

The work culture at vHub places a strong emphasis on continuous learning and development. This focus has fostered an environment where employees are encouraged to consistently expand their knowledge and skills. As a result of this commitment to growth, both individual employees and the organization as a whole have experienced substantial progress over the past year.

In conclusion, the journey towards innovation and success is paved with incremental steps, a willingness to experiment, and a commitment to continuous learning.