“The clothing industry is said to be the world’s second most polluting business, runner-up in grubbiness to oil.”
Although some thinkers use the term “singularity” to refer to any dramatic paradigm shift in the way we think and perceive our reality, in most conversations The Singularity refers to the point at which AI surpasses human intelligence. What that point looks like, though, is subject to debate, as is the date when it will happen.
In a recent interview with Inverse, Stanford University business and energy and earth sciences graduate student Damien Scott provided his definition of singularity: the moment when humans can no longer predict the motives of AI. Many people envision singularity as some apocalyptic moment of truth with a clear point of epiphany. Scott doesn’t see it that way.
“We’ll start to see narrow artificial intelligence domains that keep getting better than the best human,” Scott told Inverse. Calculators already outperform us, and there’s evidence that within two to three years, AI will outperform the best radiologists in the world. In other words, the singularity is already happening across each specialty and industry touched by AI — which, soon enough, will be all of them. If you’re of the mind that the singularity means catastrophe for humans, this likens the process for humans to the experience of the frogs placed into the pot of water that slowly comes to a boil: that is to say, killing us so slowly that we don’t notice it’s already begun.
Continue reading “Human-Level AI Are Probably A Lot Closer Than You Think” »
Deep learning owes its rising popularity to its vast applications across an increasing number of fields. From healthcare to finance, automation to e-commerce, the RE•WORK Deep Learning Summit (27−28 April) will showcase the deep learning landscape and its impact on business and society.
Of notable interest is speaker Jeffrey De Fauw, Research Engineer at DeepMind. Prior to joining DeepMind, De Fauw developed a deep learning model to detect Diabetic Retinopathy (DR) in fundus images, which he will be presenting at the Summit. DR is a leading cause of blindness in the developed world and diagnosing it is a time-consuming process. De Fauw’s model was designed to reduce diagnostics time and to accurately identify patients at risk, to help them receive treatment as early as possible.
Joining De Fauw will be Brian Cheung, A PhD student from UC Berkeley, and currently working at Google Brain. At the event, he will explain how neural network models are able to extract relevant features from data with minimal feature engineering. Applied in the study of physiology, his research aims to use a retinal lattice model to examine retinal images.
Artificial intelligence has reached peak hype. News outlets report that companies have replaced workers with IBM Watson and that algorithms are beating doctors at diagnoses. New AI startups pop up everyday, claiming to solve all your personal and business problems with machine learning.
Ordinary objects like juicers and Wi-Fi routers suddenly advertise themselves as “powered by AI.” Not only can smart standing desks remember your height settings, they can also order you lunch.
Much of the AI hubbub is generated by reporters who’ve never trained a neural network and by startups or those hoping to be acqui-hired for engineering talent despite not having solved any real business problems. No wonder there are so many misconceptions about what AI can and cannot do.
Continue reading “Understanding the limits of deep learning” »
“Bloomberg, an entrepreneur and former mayor of New York City, and Pope, a lifelong environmental leader, approach climate change from different perspectives, yet they arrive at similar conclusions.”
We will be able to embed storytelling directly into business strategy development, tell meaningful and memorable stories that truly connect with employees and customers, craft moments that are personalized and frictionless, and as a bonus, have the ability to harness Watson to optimize distribution across channel, demo and geography.
This is particularly resonant as I believe that just as the last twenty years mandated that every organization strive to be a technology company, the next twenty will command every winning corporation to be a content or media brand. In my view, Watson and AI will be the ingredient brand catalyzing tomorrow’s innovation at leading corporations in many ways; but media for certain will be top of the list, as AI assists them in becoming the top content studios of the future. Smaller businesses can scale these ideas using Watson as well as compelling content creation becomes an increasingly important driver of business strategy.
Tomorrow’s business success stories will be fueled by AI that extends beyond the CTO and areas of pure technology and infrastructure, to the CMO and areas ranging from culture to communication to creativity. The winning formula of the future as articulated by IBM will be creativity + technology = meaningful engagement, and the ability to activate purposeful change.
