The brief history of artificial intelligence: The world has changed fast – what might be next? Just 10 years ago, no machine could reliably provide language or image recognition at a human level. But, as the chart shows, AI systems have become steadily more capable and are now beating humans in tests in all these domains.

The brief history of artificial intelligence: The world has changed fast – what might be next? Just 10 years ago, no machine could reliably provide language or image recognition at a human level. But, as the chart shows, AI systems have become steadily more capable and are now beating humans in tests in all these domains.

Training computation is measured in floating-point operations, or FLOP for short. One FLOP is equivalent to one addition, subtraction, multiplication, or division of two decimal numbers. All AI systems that rely on machine learning need to be trained, and in these systems, training computation is one of the three fundamental factors that are driving the capabilities of the system. The other two factors are the algorithms and the input data used for the training.

For the first six decades, training computation increased in line with Moore’s Law, doubling roughly every 20 months. Since about 2010, this exponential growth has sped up further, to a doubling time of just about 6 months.

In her latest update, Cotra estimated a 50% probability that such "transformative AI" will be developed by the year 2040, less than two decades from now. Many AI experts believe that there is a real chance that human-level artificial intelligence will be developed within the next decades, and some believe that it will exist much sooner.

Sifting the Essential from the Non-Essential. Few things have more of an impact on your life and career than the ability to zero in on what really matters. Most information is irrelevant. Most of your time is wasted. Knowing what to ignore is the key to unlocking another level. In the process, we skip the most important thing of all: our mind.

Einstein’s greatest skill was the ability to sift the essential from the inessential — to grasp simplicity when everyone else was lost in the clutter. Only a master can make the complicated simple. Only a master can see the simple point that others miss. "I soon learned," Einstein wrote, "to scent out what was able to lead to fundamentals and to turn aside from everything else, from the multitude of things that clutter up the mind."

The biggest mistake that most of us make is that we try to consume more information without understanding what’s relevant and what’s not. The constant search for more is the natural response of someone who doesn’t truly understand what matters and what doesn’t. Often, wanting more information is a sign you don’t understand the problem. If you understood the problem, you’d want specific information.

Most information is irrelevant. Most of our time spent chasing it is wasted. But only those who can learn to sift the essential from the inessential, only those who can learn to see the simplicity, know what to ignore.

The skills to better filter and process are within our grasp:

1. Focus on understanding basic, timeless, general principles of the world and use them to help filter people, ideas, and projects.
2. Take time to think about what we’re trying to achieve and the 2-3 variables that will most help us get there.
3. Remove the inessential clutter from our lives.
4. Think backwards about what we want to avoid.

By incorporating these actionable advice into our lives, we can improve our ability to sift through the noise and focus on what truly matters. The fast-paced advancements in artificial intelligence and the increasing capabilities of AI systems highlight the importance of honing our filtering skills. As AI continues to evolve, the ability to discern what is essential and what is non-essential will become even more critical.

In conclusion, the brief history of artificial intelligence demonstrates the rapid progress made in AI systems, and the potential for human-level artificial intelligence to be developed in the near future. The advancements in training computation, algorithms, and input data have propelled AI capabilities beyond what was once thought possible. Simultaneously, sifting the essential from the non-essential is a skill that we must cultivate in order to navigate the overwhelming abundance of information in our lives. By focusing on understanding basic principles, identifying key variables, eliminating clutter, and thinking backward, we can enhance our ability to filter and process information effectively. As we look toward the future of AI and its impact on society, the ability to discern what truly matters will be a valuable asset in navigating the ever-changing landscape.