
Reactive Security vs. AI Solutions
With more sophisticated cyberattacks, we need more advanced security solutions. Instead of minimizing the effects of a breach, we could avoid them all together with intelligent systems.
The singularity is not upon us, so you can put aside your concerns that the machines will soon be taking over. Quite the opposite. The machines are still, very much working for us. And thanks to Artificial Intelligence (AI), those machines not only work for us, but they also work smarter.Â
The very definition of Artificial Intelligence is intelligence demonstrated by machines. But AI is an umbrella for several different technologies (such as Machine Learning and Deep Learning) that come together to make machines capable of sensing, comprehending, acting, and learning with human-like intelligence.Â
Alan Turing’s paper “Computing Machinery and Intelligence” was published in 1950 and is considered the thesis which launched the idea of Artificial Intelligence. In that paper, Turing posed the question “Can machines think?” This paper also introduced the Imitation Game which is played by a man, a woman, and an interrogator. That game served as the basis for the Turing Test, which is a method of inquiry in AI to determine if a computer is capable of thinking like a human being.
No matter how you define it, AI has become an incredibly important technology for modern businesses. If you hire AI developers, companies can become more agile, competitive, and better capable of meeting an ever-growing demand.
If you still don't believe Artificial Intelligence might be right for your business, consider these benefits. AI can:
That shortlist alone should have you champing at the bit to integrate AI into your business.
But how? How can you integrate Artificial Intelligence into your business? It's not as hard as you might think. Yes, you're going to need developers adept at using the required tools to build AI, but once you've hired those developers, they can easily deploy AI in chatbots, big data synthesizers, smart algorithms to assist with audience-building, A/B testing, programmatic ad buying, and listening tools. All of those options can be deployed without nearly the effort you might think.
But before you can get to that point, you need to hire AI developers.
First and foremost, your developers need to know the right programming languages that are best suited for AI. Languages like Java, Scala, and Python are a must.Â
Those developers should also have an understanding of deep learning platforms (such as H20.AI) and deep learning libraries as well as Google's ML Kit. A solid understanding of how to work with and implement cloud platforms (such as Google Cloud, AWS, and Azure) is also critical.Â
There are plenty of APIs (such as OpenGL and PhysX) that will be required. Finally, your developers will need to have a deep understanding of how to use the popular frameworks associated with AI, which includes:
The skills necessary for the development of AI go beyond software. Your developers will also need to have a solid understanding of math and algorithms. AI developers must be strong problem solvers and math will be a crucial aspect of that skill. In that same vein, they'll need to have a solid grasp of probability and statistics. Why? Because AI is built on searching for predictable patterns and trends. Every AI developer should be well-versed in statistical methods and probability theories.
It's also important that your AI engineers be comfortable working with data. Without data, AI can’t learn. For AI to be successful, it will also need to pull data from multiple sources, so those developers must be able to work with numerous data collection methods.
Another skill you might not have considered is signal processing techniques, which are crucial for feature extraction. This also includes Time-frequency Analysis and Advanced Signal Processing algorithms like Wavelets, Shearlets, Curvelets, and Bandlets.
Needless to say, being a developer in the field of AI is much more involved and complex than standard application development.
Another issue that must be considered, when hiring developers for AI is ethics. If your company is to dive into the realm of AI, you must keep ethics front and center. Why? Because you'll be deploying applications in such a way that must allow companies to earn and retain a level of trust with customers. Those Artificial Intelligence apps will be using consumer data in such a way as to empower your company. This requires trust.
For such trust, you'll need to make sure you're hiring developers you can rely on, who can deliver on data security, who are capable of working with transparency, and who can help develop risk frameworks and contingency plans, should problems arise.
The world of AI is only going to continue to grow on a massive scale. Your company needs to start working immediately to hire AI engineers capable of working with this technology. To do that, you'll have to exercise a bit of care and caution to ensure you bring into your team's software engineers that have all the necessary requirements to get the job done right.
You should look to hire AI experts who can answer the following questions:
AI represents simulated intelligence in a machine, ML is the practice of training machines to make decisions without programming, and DL is the process of using artificial neural networks to solve complex problems.
One of the most widely-used examples of AI is Google's search engine which uses predictive analysis to offer recommendations for users to select from.
A Bayesian Network is a statistical model that represents a set of variables and their associated conditional dependencies by way of a directed acyclic graph.
Your job will be to develop AI software that can be integrated into our business systems. You will work with a team to help build and execute our AI strategy and aid with the AI development and production infrastructure, as well as create AI models and deploy them to production.
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