If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Knowledge on NoSQL databases seems to be an increasing requirement in data science applications, yet, the taxonomy is so diverse and problem-centered that it can be a challenge to grasp them. This post attempts to shed light on some of the concepts, often delving into each design's specificities. We start by briefly introducing NoSQL and the reasoning behind its appearance, followed by an analysis of each of the four members of the NoSQL family, their behavior, and main mechanisms, in addition to their advantages, disadvantages, and typical use cases. NoSQL (Not-only SQL) came into prominence in the mid-late-2000s as alternatives to traditional SQL. Instigated by the Web 2.0 industry, it allows for horizontal scaling, distributed databases, and flexible models (schema-less design).
Dave Ryan leads the Global Health & Life Sciences business unit at Intel that focuses on digital transformation from edge-to-cloud in order to make precision, value-based care a reality. His customers are the manufacturers who build life sciences instruments, medical equipment, clinical systems, compute appliances and devices used by research centers, hospitals, clinics, residential care settings and the home. Dave has served on the boards of Consumer Technology Association Health & Fitness Division, HIMSS' Personal Connected Health Alliance, the Global Coalition on Aging and the Alliance for Connected Care. What is Intel's Health & Life Sciences Business? Intel's Health & Life Sciences business helps customers create solutions in the areas of medical imaging, clinical systems, and lab and life sciences, enabling distributed, intelligent, and personalized care.
Medical researchers are employing AI to search through databases of known drugs to see if any can be associated with a treatment for the new COVID-19 coronavirus. An early success story comes from BenevolentAI of London, which using tools developed to search through medical literature, identified rheumatoid arthritis drug baricitinib as a possible treatment for COVID-19. In a pilot study at the end of March, 12 adults with moderate COVID-19 admitted to the hospital in either Alessandria or Prato, Italy, received a daily dose of baricitinib, along with an anti-HIV drug combination of lopinavir and ritonavir, for two weeks. Another study group of 12 received just lopinavir and ritonavir. After their two-week treatment, the patients who received baricitinib had mostly recovered, according to a recent account in The Scientist.
Most of the buzz around artificial intelligence (AI) centers on autonomous vehicles, chatbots, digital-twin technology, robotics, and the use of AI-based'smart' systems to extract business insight out of large data sets. But AI and machine learning (ML) will one day play an important role down among the server racks in the guts of the enterprise data center. AI's potential to boost data-center efficiency – and by extension improve the business – falls into four main categories: Put it all together and the vision is that AI can help enterprises create highly automated, secure, self-healing data centers that require little human intervention and run at high levels of efficiency and resiliency. "AI automation can scale to interpret data at levels beyond human capacity, gleaning imperative insights needed for optimizing energy use, distributing workloads and maximizing efficiency to achieve higher data-center asset utilization," explains Said Tabet, distinguished engineer in the global CTO office at Dell Technologies. Of course, much like the promise of self-driving cars, the self-driving data center isn't here yet.
Frameworks and libraries can be said as the fundamental building blocks when developers build software or applications. These tools help in opting out the repetitive tasks as well as reduce the amount of code that the developers need to write for a particular software. Recently, the Stack Overflow Developer Survey 2020 surveyed nearly 65,000 developers, where they voted their go-to tools and libraries. Here, we list down the top 12 frameworks and libraries from the survey that are most used by developers around the globe in 2020. About: Originally developed by researchers of Google Brain team, TensorFlow is an end-to-end open-source platform for machine learning.
The spread of artificial intelligence into surveillance technology has given every CCTV camera the potential to turn into a spy for the state. And on the internet, images scraped from social media sites or videos can be used to build massive surveillance databases like Clearview AI. A hoodie might change that. Researchers from Facebook and the University of Maryland have made a series of sweatshirts and T-shirts that trick surveillance algorithms into not detecting the wearer. The shirts exploit a quirk that was found in computer vision algorithms nearly five years ago.
Every solution depends on computational infrastructure. On the technology layer, the system designer makes decisions about how and where to store datasets, what kind of computing device is needed to train and serve models, and the software stack it relies on, e.g., programming languages, frameworks, and other dependencies.
This June, 2020, NASA announced that intelligent computer systems will be installed on space probes to direct the search for life on distant planets and moons, starting with the 2022/23 ESA ExoMars mission, before moving beyond to moons such as Jupiter's Europa, and of Saturn's Enceladus and Titan. "This is a visionary step in space exploration." said NASA researcher Victoria Da Poian. "It means that over time we'll have moved from the idea that humans are involved with nearly everything in space, to the idea that computers are equipped with intelligent systems, and they are trained to make some decisions and are able to transmit in priority the most interesting or time-critical information". "When first gathered, the data produced by the Mars Organic Molecule Analyzer (MOMA) toaster-sized life-searching instrument will not shout out'I've found life here', but will give us probabilities which will need to be analyzed," says Eric Lyness, software lead in the Planetary Environments Lab at NASA Goddard Space Flight Center. "We'll still need humans to interpret the findings, but the first filter will be the AI system".
Getting started with Artificial Intelligence can lead to numerous questions and confusion, given the speed the world is changing and adopting this technology. There are plenty of resources available online but there has to be a start point. In this article, there is a brief introduction of Artificial Intelligence covering all its important aspects which one must go through to get a clear picture of this emerging technology. Artificial Intelligence has made commendable progress and is developing at a lightning-fast speed covering every industry of a market. AI has become a necessity rather than an extra activity to know about this technology and its evolving faces. Artificial Intelligence can be understood as a simulation of human intelligence.
Right now, a robot that has to navigate around a home, like a robotic vacuum, knows what a refrigerator is when it sees one, but unlike a human, it doesn't necessarily know that that means it's in the kitchen. Therefore, if a piece of furniture gets moved, it can disorient the robot unless one takes the time to manually program it with the object's new location. A team of researchers from Facebook's AI program and Carnegie Mellon University are teaming up to change that. Using a system dubbed Goal-Oriented Semantic Exploration, the team is using machine learning to teach robots a little bit of common sense when it comes to the placement of household furniture. Looking for the latest gov tech news as it happens?