follow site https://psijax.edu/medicine/my-pham-tenamyd/50/ enter medical essay competition levitra apple valley once you have arranged an interview with an authority on your speech topic, what is your next task? an example of an argumentative thesis enter jurnal tesis ui write good introduction research paper follow site https://pharmacy.chsu.edu/pages/blue-sky-resume-service/45/ follow site cheap definition essay editing services ca graduate essay length essay on proverbs in english prednisone online credit card now canadian pharmacy. com does prednisone make you thirsty popular business plan ghostwriters sites for masters amount of viagra to take follow url free online algebra help i am paper examples dog prednisone thirst watch does viagra help blood circulation resume writing service india interprofessional collaboration in nursing essay cialis pricing daily go to link how to write a medical case study report We live in a world of key-value pairs. Every person, object and shred of content is paired with innumerable attributes that makes up for a database whose size obviously beats human comprehension. The race has, understandably so, moved into being able to harness this information and serve it up to the users when the user asks for it. Therein lies the next battle.
The key phrase of the last paragraph was “when the user asks for it”. Systems at this time, while appearing to understand the user are largely placing the burden of knowing what to ask for, back on the user. From Google Search to Siri, we live in a world of amazing technological growth and yet, we have not gotten nearly close in making the journey from the science of pairing and annotation to the art of understanding the context of the user’s mind. Big Data remains an abstract concept to end-users primarily due to our inability in making this journey. This is where the key to tomorrow’s success is to be found.
Let us take a simple example – a sentence as simple as “The chocolate brown truck went fast on the road”. When you tell this sentence to an astute ten year old kid, he/she will, in a few attempts say UPS. Naturally so, because the human mind has associated a fast moving chocolate brown truck to UPS. However, when you enter the same sentence in a search engine, UPS is not one of the top search results (and I am using top very liberally). How is it possible that a ten year old kid has built the knowledge and capability that outsmarts the brainpower of numerous data scientists and organizations? The answer lies in the ability to understand the context. In this case, the mapping is not between chocolate brown truck and UPS but that it is fast moving as well.
I am not saying that this is a dud. Associating a verb and adverb (fast moving) with a key value pair (chocolate brown truck and UPS) is not easy and is wrought with so many inconsistencies when you extend it, it is going to be incredibly hard to avoid misses that will drown out successes in this effort. To this, when you add the ever-growing axis of the Internet of Things, it becomes a puzzle whose boundaries are incredibly hard to fathom. But then, when has the awesomeness of a good problem ever stopped the human mind?
We live in a reactive world of computing. We always burden the user with this question of “Ask me anything and I will find an answer”. We cannot scale up to the users’ expectations by repeating that question through various mediums (search engine, personal assistant etc.). Sooner than later, we have to get truly predictive about the users’ intent and then, we can build intelligent systems to get proactive about the best solution for the question that the user has not yet come up with, in his/her mind.
If we have to make that transformation, we have to leap forward from today’s world of content into tomorrow’s world of context. That is truly the trump card of tomorrow’s computing success!