If you have watched any sports match lately on TV, you may have noticed the increasing use of Technology to improve sports performance ranging from
- Assessment & recommendations based on distinctive data led insights about individual players and the team as a whole.
- Predictive analytics - which lists probabilities at micro intervals to distinctively predict the outcomes of match with greater bounds on confidence intervals.
- Customising training prior to the sports - to help prepare for peak performance. Right from monitors and devices to track fatigue, rest levels, adrenaline etc. - the use of technology to improve our experiences with the physical world are becoming even more real, powering outcomes that matter.
Essentially these states map to the following three nuances in all Machine learning systems
Access . Predict & Recommend . Improve
Some may discard the use of this technology as too intrusive, while others see it as an edge, in an increasingly dynamic world. This allows a very sophisticated combination of teams and their individual fitment in the sports.
The same nuances based by sophisticated machine learning techniques also apply to personalised entertainment, such as Netflix, where based on an individual's distinctive tastes, it allows both for content discovery and serendipity. As entire industries get shaped with the same, (remember, Moneyball ? ) and new industries and niches emerge, Machine learning is poised to massively disrupt different areas that had a traditional first mindset.
Pretty much like in sports, the possibilities of continuous improvement with a hyper personal Tech enabled coach are becoming both accessible & real. As computing gets cheap and the baseline of technology becomes more stronger, omni-channel algorithms behind these products, encourages a more balanced, diverse point of view, a more prepared and through well formed mind(or performance, at large). A thrust that Tech can enable, when seen in the context of Education in particular. This is where the traditional meets the Next generation set of tools for a new generation of learners.
We are now living in the information age, which means that Information is becoming commodity and is no longer preserved by a limited few.
In a world of Massively Open online courses (MOOC’s), the competitive edge is no longer the access, or content, but the ability to understand complex concepts and problem solve with the inputs that is given.
Seen those capstone applied projects ? As Industries demand a different workforce for the future, they will become a norm, and will inject all the way into the K12 learning, because of the pace at which we absorb in early and elementary education.
With the advent of micro snack-able content, reels, micro entertainment, the space is ripe to consume information in a deferred basis . In an increasingly complex world, we no longer need full degrees programs to learn specialised things. An example of this is the consultants that uses to be in demand for maintaining legacy ERP systems. With the disruption on SaaS based economies, they have both lost their temporary competitive edge and also the opportunity to be ahead of the pack to create blue oceans.
This is what Shunya is building. With its founding team brought up at the cusp of these disruptive changes it is well poised to not just understand & appreciate these changes but also actively shape it.
Specialisation in the new world order means being a strong generalist and whether we like it or not - all of this depends on a conditioned cognitive elasticity. Cognitive science uses advanced mathematics and neuroscience to give a diverse exposure in a field as career and life impacting as Education. In that, the way we have learnt to learn, stays with us for a very long time.
Simply put, imagine a system having a lot of data about your distinctive learning needs as a child. This, for good, is the world that Shunya is trying to create for the economies where GDP growth will be powered by true rewiring of the way talent is raised in the classrooms.
More data beats better algorithms quotes -- Peter Norvig, Google
So, what about Netflix ?
Much like Netflix, our insistence on hyper personalisation allows us to be different from traditional ERP and plain old vanilla LMS offerings. In that much like netflix, we don’t have one product but over a millions of different products, content exposure, uniquely tailored to each individual child and its learning modalities across Video, audio, text, content off the web etc.
We want education to be truly empowering for the children. Which means algorithmically understanding the way they respond to (Assessment & Recommendation) , predictive analytics (A/B testing the same) and Hyper personalising the exposure to micro concepts to get better & deeper learning outcomes with Technology. Much like Netflix does with it’s artwork and content personalisation.
So, we start humbly. Right at the schools. With the high fidelity data about a child’s distinctive learning needs. And we stay relentlessly committed to bringing a world, that possibly would never have been invented. Together.