Today, technologies like Artificial Intelligence (AI) and Machine Learning (ML) have integrated into our lives in such a way that it is impossible to imagine a world without them. Think about the smart virtual assistants (Siri and Alexa), the recommendation engines on online shopping platforms (Amazon and Netflix), self-driving cars and smart homes, they all are applications of ML. Certainly, the inclusion of these radical technological innovations has made our lives so much more comfortable. Although ML has been around for a long time (for instance, Turing's Enigma machine), it's only recently that the interest in this concept has peaked. As more companies are getting inclined towards advanced ML solutions and technologies, it is encouraging students and professionals to take up a machine learning course.
Google wants to bring smarts to cool gadgets and devices made using Raspberry Pi 3 or Intel's Edison. The company is chasing makers with open-source tools needed to add artificial intelligence to consumer, industrial, and retail devices made using board computers. The plan may include machine-learning tools, which are central to AI. AI helps Apple's Siri, Amazon's Alexa, and Microsoft's Cortana answer questions, and also helps self-driving cars cruise the streets safely. "We don't have any specifics to announce right now, but we're excited to keep sharing open-source machine learning tools with the community--stay tuned for more this year," a Google spokesman said in an email. Earlier this week, Google published a market research survey in an effort to get a better grip on the maker community and its priorities.
Without a doubt, 2016 was an amazing year for Machine Learning (ML) and Artificial Intelligence (AI) awareness in the press. But most people probably can't name 3 applications for machine learning, other than self-driving cars and perhaps their voice activated assistant hiding in their phone. There's also a lot of confusion about where the Artificial Intelligence program actually exists. When you ask Siri to play a song or tell you what the weather will be like tomorrow, does "she" live in your phone or in the Apple cloud? And while you ponder those obscure question, many investors and technology recommenders are trying to determine whether,,, or will provide the best underlying hardware chips, for which application and why.
The biggest hardware and software arrival since the iPad in 2010 has been Amazon's Echo voice-controlled intelligent speaker, powered by its Alexa software assistant. But just because you're not seeing amazing new consumer tech products on Amazon, in the app stores, or at the Apple Store or Best Buy, that doesn't mean the tech revolution is stuck or stopped. They are: Artificial intelligence / machine learning, augmented reality, virtual reality, robotics and drones, smart homes, self-driving cars, and digital health / wearables. Google has changed its entire corporate mission to be "AI first" and, with Google Home and Google Assistant, to perform tasks via voice commands and eventually hold real, unstructured conversations.
You don't have to agree with Elon Musk's apocalyptic fears of artificial intelligence to be concerned that, in the rush to apply the technology in the real world, some algorithms could inadvertently cause harm. This type of self-learning software powers Uber's self-driving cars, helps Facebook identify people in social-media posts, and let's Amazon's Alexa understand your questions. Now DeepMind, the London-based AI company owned by Alphabet Inc., has developed a simple test to check if these new algorithms are safe.