Few technologies are capturing our attention like AI. Its name, artificial intelligence, is itself intriguing. It promotes the possibility that technology can transcend its input/output origins and become a self-sustaining and self-actualizing technology.
To be sure, AI isn’t an entirely novel concept. It’s been around for decades, but the past several years have witnessed significant strides in its development and implementation. In many ways, artificial intelligence is already all around us. Many features that we use every day – auto-completing text phrases, self-generating music playlists, and our social media feeds – are all the product of the technology.
In February, The New York Times published a headline positing that AI is “Edging its way into our lives.” The reality is much less subtle. AI is estimated to be a $1.2 trillion industry by 2020, and it boasted an impressive 300% growth rate in 2017. Early last year, Google CEO Sundar Pichai remarked on the importance and prominence of AI, declaring that the technology is “one of the most important things that humanity is working on. It’s more profound than, I don’t know, electricity or fire.”
Of course, this isn’t for the benefit of computers. AI’s advantage is to users, or, in the broadest sense, all of humanity.
AI is capable of being more than just an accouterment. In many ways, it is the future of our technological landscape, and it can make a major impact on our lives. For instance, AI can detect depression just from someone’s voice, the healthcare industry is deploying the technology to detect dosage errors, and, as the MIT Technology Review explains, AI is being used by cybersecurity experts to thwart cyber-attacks. Consequently, The Wall Street Journal reports, “a tsunami of AI research and development that promises to leave no industry unchanged.”
Caption: Google’s AI AlphaGo Beating Human Experts at Their Own Games
Trouble for the Burgeoning Technology
Of course, all of this possibility doesn’t mean that AI is without its challenges. While some people are concerned about giving computers ancillary human characteristics, the more pronounced problems are with the glut of computational capabilities required to produce a competent AI infrastructure.
In most cases, AI relies on the deluge of data created by the internet to build logical connections between content. Currently, AI is inherently data heavy, functioning on a qualitative narrative that isn’t akin to human thought. Therefore, the technology is incredibly wasteful, expensive, invasive, inelegant, and inaccessible.
As a result, AI implementation is mostly relegated to large companies with immense resources, laying the foundation for what could be an AI-augmented elite that scantily funded small businesses and companies will not be able to rival.
Questioning the Norms
Although many of the most prominent AI-focused chip producers – including Bitmain, NVIDIA, and Qualcomm – are focused on building computationally competent computer chips, the future of AI might not be as complicated.
In fact, several companies are pursuing a next-generation approach to AI implementation. MindAI, DeepMind, SingularityNET, OpenAI, and DAPRA are all implementing aggressive strategies to AI research. These companies are joined by perennial tech juggernaut IBM and their much-touted Watson AI initiative to collectively encapsulate some of the most vigorous companies forming the future of AI.
Rather than relying on outlandishly intense computational process, the future of AI or third-wave AI is harnessing past research gains to build a more capable and efficient ecosystem. By applying things like a reasoning engine that uses natural language to more accurately depict human thought, companies are closing the gap between computers and human functions. In addition, companies are combing AI infrastructure with blockchain technology to create a more accessible, secure, and competent AI setup.
In many ways, the blockchain is making the difference.
For example, MindAI blockchain project enables researchers to use the blockchain’s transparent records to evaluate and discern the AI algorithm’s process for determining a specific conclusion. From a growth standpoint, this can help developers more quickly build AI platforms that address uniquely human problems in a precise way.
When paired with an open-source ethos and incentivized participation, this next-generation approach to AI development can harness technology to make it more usable and less absurd. Since AI is undoubtedly the future of computing, redefining best practices to make the algorithms as helpful as possible is a top priority.
Virtually every industry and most of our personal lives will continually be impacted by the impact of AI, so advancements in this sector are incredibly consequential. In other words, when AI better represents human thought, it can best solve human problems, and that’s the real benefit of artificial intelligence.