Today, Siri can read to you. Soon, Siri will read for you.

Finding time to read these days is tough. Between social media algorithms constantly flooding us with notifications and our tendency to choose more entertaining alternatives, it’s not uncommon to go long stretches without reading something meaningful, fulfilling, or impactful. Not for a lack of desire, though.

We all want to be able to read that growing stack of books. We all want to feel informed of what’s going on in the world. Personally, I find myself wanting to achieve Warren Buffett’s benchmark:

“Read 500 pages…every day. That’s how knowledge works. It builds up, like compound interest. All of you can do it, but I guarantee not many of you will do it.”

Warren Buffett

Clearly, in these days of exponential information, finding time to read is a billion-dollar problem. This is why Blinkist and other manual summarization tools exist. But, machine-learning experts believe that the answer lies in AI.

Using machine-learning to summarize and make sense of text isn’t an easy problem to solve and actually has been a part of scientific theories for quite some time. However, it’s just in the past couple of years that promising improvements have been made.

A little-known tool known as SMMRY is using AI to summarize articles in a matter of seconds. It analyzes the prominence of words, determines the weight (importance) of a given sentence, and compresses each article down to the most important 7 sentences.

Ironically, I stumbled upon a fairly scientific paper discussing this topic and used the SMMRY tool to extract the insights for me. It eliminated some of the necessary background information to fully comprehend the article, which you can expect when it kills 77% of the text. Yet, I still got the main gist and feel smarter after using it.

On the other hand, Salesforce is attacking the problem a little differently. They are teaching an algorithm from examples of good summaries, an approach called supervised learning. They also emphasize an artificial attention to the text to help ensure that it doesn’t produce too many repetitive strands of text (a common problem with summarization algorithms).

Both of these tools have a long way to go before we can trust them to summarize at the level of, or higher than, the human brain.

Nonetheless, you really can run rampant with all the possible use cases of a highly effective AI Summarizer. It would do wonders for graduate students researching for their Senior Thesis. Paralegals could find the precedent they are looking for in a fraction of the time. And everyone would feel empowered to pour over books and books of information.

Ideally, a well-functioning AI Summarizer would be integrated within our existing device interfaces.

By 2028 Siri will have integrated this summarization functionality – whereby I scroll through my timeline, stop on an article, and prompt Siri: “Hey Siri, what’s this article about?” – receiving a thoughtful, effective summary of the document before diving deep into it.

What’s stopping you from reading every day?