Password security is a major concern for companies, and one of the biggest challenges is getting employees to use better password hygiene. To shore up security, you need to find practices that your employees will actually use. To make it easier, consider sharing these five recommendations to help them find
The definition of a luxury brand changes depending on the type of brand you’re describing. In consumer goods, its Louis Vuitton and expensive couture fashion. Everything from handbags to handkerchiefs sports logos from Burberry, Christian Dior, and Chanel.
Comparing today’s AI with biological intelligence, one of the most remarkable differences is the ability of animal brains to somehow understand the ‘essence’ of things: Even a small child can easily recognize a cat after having seen only a few examples.
Artificial intelligence has a broad range of ways in which it can be applied – from chatbots to predictive analytics, from recognition systems to autonomous vehicles, and many other patterns. However, there is also the big overarching goal of AI: to make a machine intelligent enough that it can handle any general cognitive task in any setting, just like our own human brains. The general AI ecosystem classifies these AI efforts into two major buckets: weak (narrow) AI that is focused on one particular problem or task domain, and strong (general) AI that focuses on building intelligence that can handle any task or problem in any domain. From the perspectives of researchers, the more an AI system approaches the abilities of a human, with all the intelligence, emotion, and broad applicability of knowledge of humans, the “stronger” that AI is. On the other hand the more narrow in scope, specific to a particular application the AI system is, the weaker it is in comparison. But do these terms mean anything? And does it matter whether we have strong or weak AI systems?