Microsoft (NASDAQ: MSFT) founder Bill Gates spoke to a group of students in 2004.
According to The New York Times Gates was a little concerned about the decline in the number of IT majors , as well as the notion that the field had matured and there were not many breakthroughs left in the area.
One student expressed doubts that there would ever be another tech company as successful as Microsoft. Gates & # 39; answers are eye-opening:
& # 39; & # 39; If you invent a breakthrough in artificial intelligence, then machines can learn, worth 10 Microsoft's . & # 39;
He was not & # 39; t kidding …
Fast forward to today, and of course some have figured it out. This particular type of artificial intelligence is called machine learning .
If anything, Gates was too conservative in his estimates. Experts say the market opportunity is now far, far greater than 10 Microsoft's.
And Gates is not alone in his optimism. Other top business executives are also on board.
- Jeff Bezos, founder of Amazon (NASDAQ: AMZN) said he believes this new technology is the key to Amazon's future.  Sun CEO Greg Papadopoulos calls it "a real revolution."
- Even superinvestor Warren Buffett says it will have a "hugely beneficial social impact."
When machines go to college
We I have previously referred to machine learning as the beginning of today's AI explosion. It is "simply" software that captures data, learns from it and then can form a conclusion about something in the world.
Thus, the key to understanding machine learning is that it is software that writes itself . Instead of explicitly programming software what to do, you instead give it large amounts of data and let it learn on your own. This allows machine learning to solve problems that previous software with even billions of lines of code could not have solved.
A more powerful subgroup of machine learning is deep learning which essentially simulates how neurons in the human brain strengthen connections between each other to learn.
If you are wondering how companies like Amazon, Google, Microsoft and Facebook have grown to be among the largest in the world, part of the answer is how well they have integrated machine learning and deep learning in every aspect of their business.
So many examples, so little space
Amazon is a perfect example. It was among the fastest-growing companies in the world to adopt the technology, and it serves as a preview of what's to come. As CEO Jeff Bezos noted in a letter to shareholders:
"Machine learning drives our algorithms for demand forecasting, product search rankings, product and offer recommendations, merchandising placements, fraud, translations and much more. The effect of machine learning will be this type – quietly but meaningfully improving the core business. "
With Amazon's success, other retailers have also been forced to play their games. Walmart Chief Data Officer Bill Groves mentioned at a technical conference last month how his company uses NVIDIA hardware and machine learning for product alerting, supply chain management and consumer behavior understanding, "So when the customer comes in the product they want to put on the shelf. "
A great example of non-retailing on the power of machine learning is Facebook, which uses it to determine what's going on in your news feed and which ads you can respond to. (The company's election-related controversies also point to the extreme challenges of employing such powerful technology.)
Facebook is taking huge advantage of the network effect, making a service more valuable as the number of users grows. And this company has one of the largest cache of consumer data in the world. All this data wouldn't be nearly as valuable without a way of understanding it all, and that's where machine learning comes in, as Facebook can target advertising in extremely specific and effective ways.
Alphabet & # 39; s (NASDAQ: GOOG) (NASDAQ: GOOGL) Google has also been among the early leaders. It's another company with a gold mine of data that can target ads on the web in eerie ways. Alphabet even offers services such as machine learning and image recognition through cloud services to other companies.
Alfabetes Waymo self-driving car division is of course also very dependent on AI. The "brains" of an autonomous car must constantly assess the ever-changing environment and make life or death decisions for a second. This is done so effectively that even now – in the early stages of the self-driving revolution – it is easy to see how AI can save millions of lives in the future.
There is much, much more than I can fit here. Credit card companies have used machine learning to improve fraud protection. Netflix uses it to give you movie recommendations. Advances in robotics will change our lives far beyond the vacuum. This has huge implications in the health care system.
To bring the story to full circle, Gates & # 39; s own Microsoft only runs Amazon in cloud computing and uses AI for things like object recognition and voice translation in its Azure platform.
Microsoft offers the Azure Machine Learning cloud service that allows any developer to build and train their own machine learning models, something Gates back in 2004 would have been very excited about.
Bottom Line for Investors
Honestly, this article is just a small first step to help you as an investor understand that AI, machine learning and deep learning are an important part of every industry and almost all major companies. It reminds me of a couple of decades ago when smart investors understood that gradually, almost every company would be an "Internet company." The same goes for AI.
As processors grow faster, storage becomes cheaper, software improves, and data collection becomes more efficient, AI will only become smarter and more important. It is clear to me that the major leading companies over the next decade and beyond will also be the most innovative in the development and use of AI.