The benefits of open source software are immense, and it's great to see so many home automation platforms offering 100% free and functional software to Internet of Things enthusiasts all across the globe. The people behind these home automation platforms have worked hard to achieve a strong codebase that you can use to build your own solution, but is open source good enough for the purpose? Or does it fall short of its "open" goal? Just like most other software platforms, a good solution needs an equally strong community that is willing to back it up and improve upon its initial state. That's why we've compiled a whopping 16 open source home automation platforms that we think are most interesting in the landscape of IoT.
If you're confused about which smart speaker to invest in, I don't blame you. There have been quite a few to hit the scene in the last few months. It's highly likely, though, that you're stuck choosing between the big three: Apple's HomePod mini, Google's Nest Audio, and Amazon's Echo. All of which are competitively priced at $99. I know... that shared price point doesn't help make the decision any easier. But beyond pricing, there are a few other things to take into consideration when choosing which smart speaker is right for you, specifically design, audio quality, connected apps, and voice assistant capabilities.
Apple's new, cheaper HomePod is a tough smart speaker to nail down. On the one hand, the HomePod Mini boasts impressive audio quality for its size. The HomePod Mini also has a Thread radio that lets it act as a smart home hub, but for now, there are only a few Thread-enabled smart devices available to control. And while Apple's new Intercom feature makes for an easy way to broadcast messages to household members, it doesn't allow for two-way calling. Now, if you're a dedicated Apple user and you've been waiting for a more affordable Siri-powered smart speaker than the $300 HomePod, the $99 HomePod Mini is your best--and only--bet.
Quantum computing--considered to be the next generation of high-performance computing--is a rapidly-changing field that receives equal parts attention in academia and in enterprise research labs. Honeywell, IBM, and Intel are independently developing their own implementations of quantum systems, as are startups such as D-Wave Systems. In late 2018, President Donald Trump signed the National Quantum Initiative Act that provides $1.2 billion for quantum research and development. TechRepublic's cheat sheet for quantum computing is positioned both as an easily digestible introduction to a new paradigm of computing, as well as a living guide that will be updated periodically to keep IT leaders informed on advances in the science and commercialization of quantum computing. SEE: The CIO's guide to quantum computing (ZDNet/TechRepublic special feature) Download the free PDF version (TechRepublic) SEE: All of TechRepublic's cheat sheets and smart person's guides Quantum computing is an emerging technology that attempts to overcome limitations inherent to traditional, transistor-based computers. Transistor-based computers rely on the encoding of data in binary bits--either 0 or 1. Quantum computers utilize qubits, which have different operational properties.
AutoML enjoys a steadily increasing popularity (see Forbes). Not least driven by the numerous successes in practical analyses. In a world in which more and more devices produce data and are networked with each other, the data "produced" grows disproportionately. Therefore AutoML is of urgent necessity to gain knowledge from these rapidly increasing data on time. We assume that AutoML becomes even more critical in the coming years and that the analysis methods deliver even more precise and faster results. The field of activity of the data scientist will not disappear, but rather, his focus will shift to more specific or sophisticated analysis techniques.
The term artificial intelligence (AI) refers to computing systems that perform tasks normally considered within the realm of human decision making. These software-driven systems and intelligent agents incorporate advanced data analytics and Big Data applications. AI systems leverage this knowledge repository to make decisions and take actions that approximate cognitive functions, including learning and problem solving. AI, which was introduced as an area of science in the mid 1950s, has evolved rapidly in recent years. It has become a valuable and essential tool for orchestrating digital technologies and managing business operations.
If "figure out quantum computing" is still in your future file, it's time to update your timeline. The industry is nearing the end of the early adopter phase, according to one expert, and the time is now to get up to speed. Denise Ruffner, the vice president of business development at IonQ, said that quantum computing is evolving much faster than many people realize. "When I started five years ago, everyone said quantum computing was five to 10 years away and every year after that I've heard the same thing," she said. "But four million quantum volume was not on the radar then and you can't say it's still 10 years away any more."
Artificial intelligence (AI) has both surpassed and replaced humans in many fields. Will AI overpower humanity in the near or distant future? Will AI control humans and replace governments? Or will AI remain a tool that humans will use to improve their performances? Research on brain-computer interface (BCI) has begun and suggests that we implant chips or connect devices to our brain to increase computing power.
On May 8, 2018, Google I/O was held at Shoreline Amphitheatre in Mountain View, California. If you are wondering what Google I/O is, don't worry, I've got your back. In the Keynote, Sundar Pichai, the CEO of Alphabet Inc. (Google's parent company), shared the then-latest developments that Google had been working on. One of the projects that he spoke about was something that maybe no one saw coming; an application of Artificial Intelligence (AI), soon to be on our own smartphones, that left the world in awe. The project was called'Google Duplex'. This initiative enables AI to place a phone call to a hair salon, converse just like us humans, and book a haircut appointment - and the part where your jaws drop is that all of this takes place in the background on your phone, without any intervention of yours!
Digital marketing in the modern era is first and foremost about data. With the huge amount of data available, it is increasingly common to see marketing become the top priority for many businesses because it is directly linked to increasing revenue. Businesses these days need to understand consumer behavior to optimize marketing campaigns. In this article, we'll look at how machine learning can help businesses improve and strengthen their marketing efforts. Also called statistical learning, machine learning is part of the race for useful information, which leads to rationalized decision-making.