AI unmasked: How is nmodes different

Right now we're in a world that sees  transparency as the new form of integrity. Right now we're in a world that understands that reputation is everything. Loyalty is somewhat fleeting as consumers, armoured with this incessant flow of knowledge from the web, have the ability to make swift  judgements and decisions about individuals, companies and governments, often times to the detriment of the target.

The emergence of social media has forced companies to stop hiding from behind that veil of corporate spin and address the very things that the web has thrown at them. Nothing is secret any longer. Even secrets that were once held secure behind invulnerable fortresses now have a strong probability of materializing today.

Is transparency as a norm working? Or, are the results of transparency surfacing a new order that will create yet another tier of acceptance from the masses?

"Anonymity is Authenticity"

Following the death of Rahteah Parsons, who, after being assaulted by 4 boys, was tormented relentlessly by classmates and other kids on social networks; and also following the suicide of Hannah Smith, who experienced the same torment, it's clear the internet has evolved to an era that has given free reign to voice an opinion and use like-minded affiliations to express and further spread that opinion. In these cases, anonymous profiles proliferated the incessant stream of hateful attacks that eventually wore down both girls' defences.

And while I originally argue that anonymity was a cowardice state that allowed people to be and feel comfortable being the anti-self that runs away from accountability, my stance has seen another side of this coin.

Anonymity is Safe

It becomes clear that humans, while inherently social, are discriminating of the things we disclose and to those to whom we share. 

If transparency breeds contempt, then anonymity should build acceptance

The freedom to express opinion and judgement without feeling guarded, or without fearing others linking you to a statement is indeed liberating. And while this free reign may take the form of a soapbox soliloquy or criticisms (and perhaps bullying attacks) against opposing views, there is a large segment of users who want the ability to share a secret, or have a place to vent their frustrations or challenges -- without the fear of reprisal.

Despite revelations from Snowden and the NSA that nothing on the net is private, this does not stop the wave of user adoption for applications like SnapChat, Whisper or Secret.

Here are some recent stats for Snapchat from Mashable

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I've recently downloaded Whisper and my experience has been more than liberating. It has allowed me an outlet to record my hopes, desires and more importantly, my anger and not-for-public emotions. Being judged in real life or on social takes its toll. If my reputation precedes me, then I will be discriminating about what I say in places where my content and identity are linked.

Popular opinion just doesn't matter. It's irrelevant. But I want to track progress in my life: my emotions, my dark moments, my personal observations, my milestones -- all in my own digital diary.

Why shouldn't users have the option to keep part of their identities secret and separate?

It's up to the next generation

This new medium has created is an endless volatile loop of positive and negative reinforcement. While transparency has extreme benefits, there are just as many negative consequences that have come as a result of creating this honesty within social channels. Society continues to send the wrong message to Millennials and GenZers, warning them to be more discerning and to suppress who they really are as individuals... warning them of the potential consequences should they venture down the wrong path.

How we communicate today poses tremendous issues for this younger generation. Their experiences are grounded in the fear of being vulnerable... fear of being misjudged... fear of not being accepted... fear of being punished. When the next generation grows up, it'll be up to them to shape the landscape and determine how to balance the impacts of transparency and anonymity.

AI training is a critical part of conversational AI solutions, a part that makes AI software different from any kind of software previously created.
AI training is not coding.
Unlike all other existing software which is fully coded.

Let us consider a simple example:
We create chatbots for two companies, one company is selling shoes, another is selling cars. From the software standpoint it is one chatbot solution running as an online service accessed remotely or a program available locally. In both cases they are two identical instances of the same software (one instance for the shoes company, another for the cars company).
Yet, for the first company the chatbot is supposed to talk about flip-flops, summer shoes, high heels and so on. For the second company, however, the chatbot is not expected to know any of that. Instead, the chatbot should be able to support conversations about car brands, car models, should know how to tell Toyota Camry from Toyota Corolla, etc. This shoes and cars knowledge is not programmable. It is trainable. It is not coded, instead it is a part of language processing capability that AI solutions like chatbots have. And herein lies the major differentiation and advantage of the AI solutions compared to traditional software.

How to train AI?
There are several ways to do it. Sometimes AI system can train itself, improve its linguistic ability over time. It also can be trained by professional linguists. And in some cases, by the users. The latter is the desirable scenario because businesses know better than anybody else what they want their chatbot to talk about.
It is not easy, given the existing state of AI technology, and usually requires a high level of technical knowledge. You may have heard mentions of intents and entities in chatbot discussions. These are examples of linguistic elements AI training is currently based on.
Without proper understanding of what these linguistic elements are and how language acquisition process works in existing AI systems it is better to leave AI training to professional linguists.