Four Weekly Tech Newsletter – Oct 14
Lead articles from October 14
The next generation of artificial intelligence
The field of artificial intelligence moves fast. It has only been 8 years since the modern era of deep learning began.Progress in the field since then has been breathtaking and relentless.Five years from now, the field of AI will look very different than it does today. Methods that are currently considered cutting-edge will have become outdated; methods that today are nascent or on the fringes will be mainstream.
Ten essential leadership qualities for the age of AI
AI and automation will change the very nature of work. It’s really important that leaders don’t ignore this AI- and data-driven revolution. Working out how to use AI, dealing with people-related challenges, avoiding the ethical pitfalls of AI, making sure you have the right technology in place, and so on – all are key considerations for the business leaders of today and tomorrow.
The anatomy of an endpoint attack
Cyberattacks are becoming increasingly sophisticated as tools and services on the dark web – and even the surface web – enable low-skill threat actors to create highly evasive threats. Unfortunately, most of today’s modern malware evades traditional signature-based anti-malware services, arriving to endpoints with ease. As a result, organizations lacking a layered security approach often find themselves in a precarious situation.
The grim fate that could be 'worse than extinction'
What would it take for a global totalitarian government to rise to power indefinitely? What would totalitarian governments of the past have looked like if they were never defeated? The Nazis operated with 20th Century technology and it still took a world war to stop them. How much more powerful – and permanent – could the Nazis have been if they had beat the US to the atomic bomb? Controlling the most advanced technology of the time could have solidified Nazi power and changed the course of history.
Machine learning uncovers new TB drugs
Machine learning is a computational tool used by many biologists to analyze huge amounts of data, helping them to identify potential new drugs. MIT researchers have now incorporated a new feature into these types of machine-learning algorithms, improving their prediction-making ability. Using this new approach, the MIT team identified several promising compounds that target a protein required by the bacteria that cause tuberculosis.
ML and AI in the food industry: solutions and potential
Artificial Intelligence and Machine Learning solutions offer large possibilities to optimize and automate processes, save costs and make less human error possible for many industries. Food and beverage is not an exception, where it can be beneficially applied in restaurants, bar and cafe businesses as well as in food manufacturing. These two segments have common use cases where AI in the food industry can be applied, and different ones, linked to different problems that must also be solved.