In light of COVID-19 precaution measures, we remind that all ImmuniWeb products can be easily configured and safely paid online without any human contact or paperwork.

Total Tests:
This Week:
Stay in Touch

Weekly newsletter on AI, Application Security & Cybercrime

Your data will stay confidential Private and Confidential

6 Reasons Why AI is Important in 2020

Wednesday, March 25, 2020 By Read Time: 5 min.

AI has been in scope of public attention for many years, bringing some skepticism and fatigue. Is it poised to be a game changer in 2020?

6 Reasons Why AI is Important in 2020

Artificial intelligence has been in the scope of public attention for many years already. It started in 1956, when a summer workshop at Dartmouth College stated in its mission, that in two months the 11 attendees would “make a significant advance” in their task of finding “how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves.”

Since that time AI has appeared not only in academic publications, but also in many fiction books and films. All these produced an aura of super-power mystery and resulted in the hype that we all are witnessing now.

Now almost anyone knows that AI can do a lot, may destroy humankind some day or make funny faces in your mobile. It often looks like everyone knows what ‘AI’ stands for, but does not understand what it means.

It sometimes may end up in a scam, like the one when McDonald’s Corp. acquired the startup Dynamic Yield for $300 million, in the hope of employing machine learning to personalize customer experience. Of course, you do not expect managers of such a company as McDonald to get their information about AI from The Terminator movie. Neither do you suspect field experts in incompetency, the experts who recognized Dynamic Yield for its AI-powered technology and recently even landed a spot in a prestigious list of top AI startups.

But as it turned out Dynamic Yield’s platform has nothing to do with AI, according to an article posted on Medium recently by the company’s former head of content, Mike Mallazzo. He made the case that marketers, investors, pundits, journalists and technologists are all in on an AI scam. The definition of AI, he writes, is so “jumbled that any application of the term becomes defensible.”

AI Demystified

So what is AI? And what it is not?

Surprisingly, it is very difficult to answer these two simple questions, because there are different definitions of AI and many of them fail to cover all its aspects or meaningfully separate from other areas.

First, we should keep clear from so called “Strong AI”, the thing that is often used and abused in many Hollywood productions: all kinds of super smart and deadly dangerous robots, Skynets, Matrices etc. The AI that “can do it all” does not exist. And will not exist in near future.

The real AI, the workhorse behind search engines, funny mobile applications, data-mining systems and video games, is all about solving some practical and very specific problems, such as image processing, data filtering and aggregation, information extraction and similar class of problems.

But can it be useful? Is there some real value in AI or just media hype?

Here is a short list of why AI is great, despite all the hype inspired false expectations and misleading promises.

1. AI Automates Repetitive Learning and Discovery Through Data

We all live in the era of data. If you know what amount of data your business consumes and produces, you agree with it. If you don’t know about the data you have to deal with, it’s high time doing so.

Not long ago there was another hype: the Big Data. That was big for a reason, as it dealt with the infrastructure needed for gathering, storing and processing huge amount of data. Now, the hype is over, but the technology silently works behind many running businesses worldwide.

But what value can your data bring to you? There might be gems in what is stored in your data silos. But looking for these gems is a tremendous effort for a human being, much more difficult than finding a needle in a haystack.

AI can parse your data and learn patterns and discover important and valuable information about, for example, your customer behavior, reason for sale fluctuations and even security issues. It will do it day after day, without being bored or burnt-out.

2. AI Adds Intelligence to Existing Product

You may have an excellent product that has been on the market for years, but if it doesn’t become smarter you may lose your customers to someone who will add one or two smart features.

It’s a no-brainer to guess, that a customer wants a product with just one button (or even better - with no buttons at all). Much like Siri was added as a feature to a new generation of Apple products to streamline a lot of functions of a mobile system.

The only way to cut on a number of ‘buttons’ is to make your product do the work for the customer, guess what needs to be done in different situations. For example, ImmuniWeb® Discovery reduces complexity and costs of cybersecurity and compliance with continuous discovery, monitoring and non-intrusive security testing of the entire external attack surface perimeter by using a set of smart algorithms that do a lot of scanning and data analysis.

3. AI Adapts Through Progressive Learning Algorithms

There have been different ‘incarnations’ of AI: it started with simple neural nets and machine translation in the 1950-s, then, in the 60-s heuristic search became popular, then the area of multi-agent systems came forward, another is automated planning.

Now it’s the time for machine learning. Deep learning algorithms made a major breakthrough in accuracy due to rapid growth of neural network research and increasing computation power availability. Although it’s not totally true to say that AI is machine learning, but it is not too much of mistake either.

Machine learning is a set of algorithms that helps a machine learn patterns in data. The algorithm becomes a classifier or a predictor. So, just as the algorithm can teach itself how to play chess, it can teach itself what product to recommend next online. And the models adapt when given new data.

Here, in ImmuniWeb machine learning is used for analysis of huge amount of metadata we collect about sites of our clients. Our AI system learns patterns that may be linked to security problems that may affect our clients’ businesses.

4. AI Analyzes More and Deeper Data

If AI is often associated with machine learning these days, then machine learning is often implemented in the form of deep learning. Deep learning is a subset of machine learning that features deep neural networks - networks that have several interconnected layers of neurons. The aforementioned major breakthrough in machine learning is mostly about deep learning algorithms.

The main advantage of deep learning algorithms is that they can learn really complex patterns in data. Instead of a simple pattern ‘If X then Y’, deep learning can learn very long and complex chains of dependencies in data points with different weights assigned to every such dependency.

We use deep learning to help our auditors find vulnerabilities in pages and locate possible problems often hidden in tens of thousands of web pages in a client’s site.

5. AI Achieves Incredible Accuracy

Indeed, the accuracy of deep neural networks is often staggering. This probably enables some people to think that AI will conquer the world some time and turn us, the humans, into … something useful (did you see the Matrix movie?).

But before it happens, deep learning brings its benefits to those who feed it with proper data and fine-tune its algorithms.

Deep learning, for instance, helps us find similar pages in a site by ‘looking’ at them. And the speed and accuracy of it is really astonishing.

6. AI Gets the Most out of Data

The more data you have the merrier. But only if you can process it in a meaningful way. Since the role of the data is now more important than ever before, it can create a competitive advantage. If you have the best data in a competitive industry, even if everyone is applying similar techniques, the best data will win.

We are striving to apply smart AI algorithms to all types of data we gather. Recently, we have been digging into the Darknet to find leaks from our clients as early as possible. Quite often we need to act fast to prevent damage to our partners and doing so without fast and reliable data processing and analysis algorithms wouldn’t be possible.

Despite all the hype and even sometimes scam, AI has a lot to offer businesses. It is not a miracle that will turn your business into a success story, but this is a tool that can tremendously improve different aspects of your business.

This is the main reason why we in ImmuniWeb invest so much into AI, prioritize it to be in the core of our technology stack.

Latest news and insights on AI and Machine Learning for application security testing, web, mobile and IoT security vulnerabilities, and application penetration testing.

User Comments
Add Comment

Ask a Question