The Future of Artificial Intelligence & Machine Learning

We too often let our fear of misunderstanding guide us or inhibit our path to learning. A proclivity approach can yield a world we often think is beyond us. One of the paths I have taken in the recent past was to dive into the application of Artificial Intelligence. Learning from such, I have seen a wondrous collaboration already beginning to unfold. I have only started to see the powers and vibrant ways the technologies are weaving into our lives beyond that.

If you have happened upon this quote:

“Human Beings Are Works In Progress That Mistakenly Think They’re Finished“. — Dan Gilbert

I see so much of this as an occurrence of our function, that of being present in our somewhat comfortable lives. A conjecture to a larger audience in which fills the rooms of our minds, that what we have is acceptance of the human pursuit. This, beyond, our materialistic needs, but a lot if not a majority of people sit happily upon Mazlow’s pyramid, gazing down instead of up. What we learn is that self-actualization is not an achieved metric, more so a continuous act, a “pursuit”.

Data-Driven Machine Actualization

Plays a large role in the equations of all of these solutions, the need for input and variances is a concluding factor in how this develops. Though it is good to mind your output, it is also beneficial, for technology, hell, the world to share things, minding sensitive information.

Building these models requires collaboration, often that is a challenge as tech has looked down on a lot of people (muggles) in the past, but now must seek to get them engaged so they can use their help. The challenge with the offset rapport and forwarding these topics is just that, there is a lack of trust. There are a few games that come to mind where we disseminate the idea of this information, interestingly enough one, one in mind not only depicts the variables of training but the overarching thesis in how these components come together with people and machines… trust.

We understand that we are growing closer to an evident truth of parallel, the proximity of machine intelligence and the mind that many speculate could happen at any moment. Some may even refer to this evolution as bearing anxiety, for those of us studying and measuring the fields around the depths of machine learning, the impact of a leap could become a rapid evolution of societal shift. Computers in which create or control subordinate computers//humans is something we write into SciFi movies like Eagle Eye (film), or I, Robot (film), even the entrapment in concepts stemming back to Tron (film), we consider such principles. As a reserved evolutionary consistency we seek to sustain our top of hierarchy order, though such Muskian slips could lead us to believe the world will be organized through processors.

Machine Learning Correlations

Studies continue to relate our digital interactions and in which they reveal about our experience, whom we are, and how our character unfolds through the digital continuum. Personalities sociologically aligned through interactions, choices, shares, and expectations. The means in which we conduct ourselves is much of a data point, a maze of existence in which can be correlated back to whom. As aforementioned our availability or many a vulnerability in these contexts dictates in which these patterns evolve the machines around us.

Think, of the means in which we see early development, shared experiences between these demographics are prominent. The relation between whom gets what, when, or even how can change the experience in correlation to the adapted development in later years. Focusing on the shifts in the dynamic plasticity of the human mind, we can begin to relate that in which changes how we perceive the development of machines. The choices we make in digital are that in which these machines, unless trained separately have the means to learn from. Examples as such exist in Microsoft’s Tay.AI, an experiment that exists as a metaphor for our much-needed development to support a better ecosystem of self, but more so the production of a machinelike existence… dare we enter the Matrix, in many contexts, we must.

“A ship in port is safe, but that’s not what ships are built for”. — Grace Hopper

What we come to understand from following the white rabbit is less an interchange of information with evolved thought, but a compiled source of reference. I do not ordinarily see machines overtaking our existence in the way some may perceive, though it is a valid thought to consider. In the ways in which we meet these experiences, we must train perception within our creations to measure such.

Ethics in Artificial Intelligence

Expecting a machine to align, that in which we struggle to define in ourselves is certainly a task at hand. Past the ability to stop chasing our food, or moving with it, we began to bargain with ourselves how in which we understood each other, actions, instinct, relations, with the pack and beyond. Observationally we can quickly gather there are many contributions in which we are the nature we endure, though, within us, many argue certain balances are derived from conception. The very frays of our being, lined with internal instincts that separate our will from the next. Cognition alone, reserves a brilliance that many still wage over this day, thousands of years past stone and fire we shake our hands still as the tales of Cain and Abel, without remorse, we seek such identification through means beyond us, within, and with each other.

What this means, deliberations aside is that we must make our choices evidently clear in these interactions, setting our tone in each step, minding our actions in each furling of existence and how those impacts arise in human and machine, an experience. Understanding in which, and where — let be a task of the thousands looking to solve the means in any which way, though the gravest task, is entertaining the idea that whom we are now, in these very moments, is/are the cave drawings for the collective technological future.

Futuristic Tendencies of Programmed Networks

Our existence of development should be that of cohesive interaction, where robots/machines/computers alike enable our societies to delve into tasks and existences allowing us to propel our evolution in contrast to a plateaued timeline of systematic depletion. We are already developing advancements to counter that of our presence, yet we can be so much further if we mind how each of these contributions is orchestrated and collectively become more involved.

Some examples of such can be relatively mind-shattering as our understanding of experience, ourselves, and nature are realigned through AI/ML/DL/NLP/QC and so on.

OpenFermion takes leaps in understanding the contributions of chemistry that humans can not solve alone, as it breaks way across computers we knew of only yesterday, but dreamed years ago. Correlations in which are mentioned in “Lo and Behold: Reveries of the Connected World”, taking steps behind human iteration in development of atomic structures.

FoveaNet builds upon machine understanding through computer vision, enabling computers to better interpret/draw/understand environments for the future of self-driving and autonomous machines in general.

In correlation of human and machine collaboration, voice and NLP are becoming an evident coexistent, with technologies deciphering motions, text, and speech as interaction, valuing the human input and managing its quality of intake alike are predominant value goals for such a task. Baidu’s DuerOS: Project Prometheus, is a steadfast motion towards correlating such, with recognition involved to intake even in noisy environments, it will further the gathering of data, in which aligning more emotive personality to the voice assistants of the future. Launching forward “state-of-the-art” and “state-of-the-practice” conversations.

In a future where machines gather voice (conversational), physical (observatory), and mental (cognitive), inputs to train continuously and increasingly — alone, with “human-like” intelligence, there is a growing need for advocacy of ethics to manage the data, evolution, and practices of these experiences//machines.

We can look to existing groups such as DeepMind with their many existing involvements in AI, to mention in recent AlphaGo, to collaboratively approach ethics, socio-economic impact, and application.

Though additionally, we must push ourselves to implicitly understand and measure components of existing technologies where we can and contribute to other groups privately interacting in spaces such as…

Along with research groups like:

To continue development and collaboration between machines and humans. Though much of these interactions are becoming increasingly technical, requiring, a lot of resources/computation, the practical applications are already becoming integrated into our experiences each day. Knowing where, when, how, and what these interactions are doing will become a prominent understanding in the much-stratified cloud in which they nest.

To balance the future, to gaze beyond which yet exists, we must take the practice upon ourselves to collaborate in the shifting futures at being. To be brave enough in which to ask why, to know what, and apply ethical interactions into our own existence, which will foster a better development for the practices of the machines in which we speculate to exist, just beyond tomorrow.

Sources Mentioned:

“Human Beings Are Works In Progress…”(-), Maslow’s hierarchy of needs (-), The Evolution of Trust (-), Pursuit of Happiness (-), AI Anxiety (-), “Eagle Eye” (-), “I, Robot” (-), “Tron” (-), Elon Musk Is Donating $10 Million To Keep Killer Robots From Taking Over The World (-), Psychological targeting as an effective approach to digital mass persuasion (-), Tay.AI (-), Artificial Intelligence (-), Machine Learning (-), Deep Learning (-), Natural Language Processing (-), Quantum Computing (-), “A ship in port is safe…” (-), OpenFermion (-), FoveaNet (-), DuerOS Project Prometheus (-), DeepMind (-), AlphaGO (-), DeepMind: Ethics & Society (-), How Clarifai builds accurate and unbiased AI technology (-), OpenAI Research (-)

Thanks for Reading, Keep Progressing!

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