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A recent pair of articles covering the topic of Artificial Intelligence (A.I.) has me confused. On one hand, there’s very positive news from recent PwC findings that suggest A.I. could drive $15.7 trillion in productivity gains by 2030. On the other, a recent piece from The New York Times makes a compelling case that, despite all the hype, A.I.’s dirty little secret is that “it still has a long, long way to go.”
Who’s right?
There’s no question A.I. is a developing technology. As The New York Times piece points out, we can find plenty of examples of robots falling over while opening doors, driverless cars needing human intervention, and machines that still cannot read reliably at the level of a sixth grader. And while there are many “microdiscoveries” being made along the way, progress toward real human cognition remains elusive. But there may be a better way forward. Here’s more from The New York Times:
To get computers to think like humans, we need a new A.I. paradigm, one that places “top down” and “bottom up” knowledge on equal footing. Bottom-up knowledge is the kind of raw information we get directly from our senses, like patterns of light falling on our retina. Top-down knowledge comprises cognitive models of the world and how it works.
The New York Times piece says is where A.I. will get stuck because both ways of funding A.I. – in small research labs and larger private ones – contain too many moving parts to make any sort of meaningful progress.
I beg to differ.
Getting to a better A.I. state of mind is all about the journey and aforementioned microdiscoveries. Just because the technology doesn’t work flawlessly now, doesn’t mean we should discredit progress-to-date or assume businesses won’t be impacted. The latest PwC findings back this train of thought. And while financial services and healthcare are the immediate big winners of A.I., it’s just the beginning. Here’s more from a recent PwC press release, per Gerard Verweij, Global Data & Analytics Leader, PwC:
“No sector or business is in any way immune from the impact of AI. The impact on productivity alone could be competitively transformational and even disruptive. Businesses that fail to apply AI, could quickly find themselves being undercut on turnaround times as well as costs and experience, and may lose a significant amount of their market share as a result. The big challenge is how to secure the right talent, technology and access to data to make the most of this opportunity.”
Indeed, leading tech companies like SAP are one step ahead, anticipating the need for companies to secure the right technology with new solutions like SAP Leonardo. So even though the impact of A.I. will be huge, the real dirty, little secret is that it’s just a small cog in the wheel when it comes to realizing the full value of the Intelligent Enterprise.
Follow me intelligently @TClark01.
Who’s right?
There’s no question A.I. is a developing technology. As The New York Times piece points out, we can find plenty of examples of robots falling over while opening doors, driverless cars needing human intervention, and machines that still cannot read reliably at the level of a sixth grader. And while there are many “microdiscoveries” being made along the way, progress toward real human cognition remains elusive. But there may be a better way forward. Here’s more from The New York Times:
To get computers to think like humans, we need a new A.I. paradigm, one that places “top down” and “bottom up” knowledge on equal footing. Bottom-up knowledge is the kind of raw information we get directly from our senses, like patterns of light falling on our retina. Top-down knowledge comprises cognitive models of the world and how it works.
The New York Times piece says is where A.I. will get stuck because both ways of funding A.I. – in small research labs and larger private ones – contain too many moving parts to make any sort of meaningful progress.
I beg to differ.
Getting to a better A.I. state of mind is all about the journey and aforementioned microdiscoveries. Just because the technology doesn’t work flawlessly now, doesn’t mean we should discredit progress-to-date or assume businesses won’t be impacted. The latest PwC findings back this train of thought. And while financial services and healthcare are the immediate big winners of A.I., it’s just the beginning. Here’s more from a recent PwC press release, per Gerard Verweij, Global Data & Analytics Leader, PwC:
“No sector or business is in any way immune from the impact of AI. The impact on productivity alone could be competitively transformational and even disruptive. Businesses that fail to apply AI, could quickly find themselves being undercut on turnaround times as well as costs and experience, and may lose a significant amount of their market share as a result. The big challenge is how to secure the right talent, technology and access to data to make the most of this opportunity.”
Indeed, leading tech companies like SAP are one step ahead, anticipating the need for companies to secure the right technology with new solutions like SAP Leonardo. So even though the impact of A.I. will be huge, the real dirty, little secret is that it’s just a small cog in the wheel when it comes to realizing the full value of the Intelligent Enterprise.
Follow me intelligently @TClark01.
