AI & Machine Learning

Technology is changing by leaps and bounds. The initial predictions for 2020 point to a serious integration of AI and human experience to study how Intelligent Automation technologies can be used to augment an enterprise experience. Here are the top Artificial Intelligence (AI) trends that will change the decade.

RPA holds great promise for the logistics industry, in particular, which currently relies on vast amounts of paperwork and stacks of manually entered data to operate and conduct day-to-day shipping transactions. Generating and processing the right documents is time-consuming, monotonous work that is ripe for RPA disruption.

How effective is deep learning in scientific research, where problems are often much more complex than classifying an image and requirements are much more sensitive than recommending what to buy next? The opportunities for applying deep learning to scientific discovery are numerous.

Data privacy is a controversial topic today, and as new regulations emerge globally to protect consumer data, that’s not likely to change. The path forward for restoring consumer trust requires full transparency as to what data organizations collect and how they use it. Using transformational technologies and techniques such as unsupervised machine learning, we can leverage AI to a greater extent for the benefit of consumers and the world at large, while keeping data privacy intact.

Will advances in artificial intelligence redefine the boundaries of human creativity? (Credit: Depositphotos) Will machines ever be able to replace or replicate human creativity? That is a question that we repeatedly ask ourselves as we continue to innovate and invent new creative tools. The printing press, the gramophone, the camera, the camcorder, the typewriter, the

Cloud Computing became an essential component of the AI evolution. As customers spend more time on their devices, businesses increasingly realize the need to bring essential computation onto the device to serve more customers. This is the reason that the Edge Computing market will continue to accelerate in the next few years. The challenge of being successful in the Edge AI economy is to understand the direction of computing, architecture, and build next-generation AI-enabled applications and devices that make full use of the tools available within the AI and machine learning eco-system. 

From smartphones and medical tools to autonomous vehicles and e-commerce, AI technologies will be applied to many different areas. They will enable companies to make important discoveries and develop vital products. But increasingly complex algorithms require hardware with huge computing capacity, leading to a growing interest in the development of better computer processors – powered by AI. They’re vital for the future of many industries, which is why the race to develop advanced AI chips is expected to intensify.

There are a lot of pitfalls and obstacles to dodge if you want to avoid condemning your AI startup to bankruptcy before your journey has even begun. The list of failures is long, and includes some of the biggest names of the IT industry, as well. Knowing how you can fail is vital to identify those challenges and skip through them as easily as possible. Success requires lateral thinking, planning ahead, and smart strategies to emerge among a horde of potential competitors.

One question that is being asked in workplaces around the world is: will AI take my job? This is perhaps unsurprising given the dystopian predictions being bounced around by the media of robots outsmarting us and destroying millions of livelihoods.  While it’s clear that AI is changing the face of the workforce, we should not get swept up in the media frenzy. Indeed, if we take a step back and calmly consider the more realistic impact of AI, the picture is far less worrisome. The growing role of this technology instead holds fantastic promise.

We take it for granted that we’re supposed to act ethically and, usually, that seems pretty simple. Don’t lie, cheat or steal, don’t hurt anybody on purpose and act with good intentions. In some professions, like law or medicine, the issues are somewhat more complex and practitioners are trained to make good decisions.Yet ethics in

Cognitive scientist Gary Marcus believes advances in artificial intelligence will rely on hybrid AI, the combination of symbolic AI and neural networks (Image credit: Depositphotos) Deep learning, the main innovation that has renewed interest in artificial intelligence in the past years, has helped solve many critical problems in computer vision, natural language processing, and speech recognition.