With the rise of artificial intelligence, we find ourselves standing before a fundamental change. It's on everyone’s mind. Investments are booming, and, when looking back at this point in time there is going to be a Before and After the rise of AI.
For some this transition is going to be a memory of sudden unprecedented success, unimaginable possibilities, while for others it will be a rueful memory of the costs of not adapting quickly enough. What AI will mean to you is determined by whether you're willing to change with it.
We’re experiencing a revolution unlike anything seen before right now because of breakthroughs in computational power, data collection and an AI technique called Deep Learning. Not only did these breakthroughs surprise experts in the field itself, they proved AI was finally ready to be put to work across industries, reigniting an AI revolution garnering billions in investment and putting experts and casual onlookers alike in awe of what’s to come.
With AI, machines can perform tasks that until recently had been reserved for humans like detect leukemia, drive a car, help a restaurant better predict their food demand or optimize logistics for a global retailer. AI does all this by identifying patterns in data. It's tech that appears to think like a human, and is inspired by the human brain. But, unlike humans, AI is only capable of tackling the specific task it’s designed for. You can’t expect the same AI that recognizes stop signs or recommends music to, say, order your pizza.
However, when it comes to solving specific problems one at time, AI can can often reach far higher accuracies far faster than any human. It can process information loads so complex and profound no human could address them. It can work on a problem around the clock and will never forget how to solve it once it learns. This way AI boosts our human intelligence making it possible to find solutions we never could on our own.
Since AI was first introduced in 1956 it has experienced several cycles of widespread optimistic interest in the field followed by ”AI Winters” when funding and enthusiasm dried up almost entirely. Today, investments are surging and all the major tech companies list AI as one of the most important components of their future strategy. So, what happened?
Well, three things:
1. The graphic card surprise
The rapid proliferation of AI could not have been possible without exponential growth in computing power over the last half-century. The major breakthrough came when graphics processing units (GPUs), originally designed for video gaming and graphics editing, unexpectedly proved to be perfectly suited to perform AI computations. More efficient and way cheaper the hardware used before to perform AI computations, suddenly these chips are making AI viable for organizations of all sizes.
2. Access to unlimited data
To solve problems AI needs data about that specific task or problem to process and learn from. Cloud computing, self-monitoring cell phones and a new plethora of tiny, powerful cameras and sensors now offer up trillions of data points every day from which AI can glean new insights and form new capabilities.
3. Going deeper into Deep Learning
Most of the recent triumphs of AI were made possible thanks to a group of AI techniques referred to as Deep Learning, or more scientifically: Deep Neural Networks. With Deep Learning you teach a network of processors by exposing it to data and information about that data. For example, if you want it to identify pedestrians in a crosswalk, you show the network many pictures of people walking and tell it that’s what they are.
AI for everyone
The recent rapid growth of AI paired with a plentiful, almost unlimited access to data democratizes the power, infrastructure and knowledge required for AI to be available to more than just multi-billion-dollar corporations. Organizations of all sizes now stand to reap the benefits that come with AI's new way of solving problems, opening doors we could never open on our own – or even see were there in the first place.