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) …
The failures of artificial intelligent systems have become a recurring theme in technology news. Recommendation systems that promote violent content. Trending algorithms that amplify fake news. Most complex software systems fail at some point and need to be updated regularly. We have procedures and tools that help us find and fix these errors.
When prompted to generate "a mural of a blue pumpkin on the side of a building," OpenAI's new deep ... [ ] learning model DALL-E produces this series of original images. OpenAI has done it again. Earlier this month, OpenAI--the research organization behind last summer's much-hyped language model GPT-3--released a new AI model named DALL-E. While it has generated less buzz than GPT-3 did, DALL-E has even more profound implications for the future of AI. In a nutshell, DALL-E takes text captions as input and produces original images as output. For instance, when fed phrases as diverse as "a pentagonal green clock," "a sphere made of fire" or "a mural of a blue pumpkin on the side of a building," DALL-E is able to generate shockingly accurate visual renderings.
Last year, we identified blockchain, cloud, open-source, artificial intelligence, and knowledge graphs as the five key technological drivers for the 2020s. Although we did not anticipate the kind of year that 2020 would turn out to be, it looks like our predictions may not have been entirely off track. Let's pick up from where we left off, retracing developments in key technologies for the 2020s: Artificial intelligence and knowledge graphs, plus an honorable mention to COVID-19-related technological developments. This TechRepublic Premium ebook compiles the latest on cancelled conferences, cybersecurity attacks, remote work tips, and the impact this pandemic is having on the tech industry. In our opener for the 2020s, we laid the groundwork to evaluate the array of technologies under the umbrella term "artificial intelligence."
In a sign of the profound changes being wrought in computing by artificial intelligence, Toronto-based AI chip startup Tenstorrent on Wednesday announced it has hired legendary chip designer Jim Keller to be its chief technology officer. Keller most recently served at Intel and before that re-invented the microprocessor architecture at Advanced Micro Devices. Keller said in prepared remarks, "Software 2.0 is the largest opportunity for computing innovation in a long time. Victory requires a comprehensive re-thinking of compute and low level software." Added Keller, "Tenstorrent has made impressive progress, and with the most promising architecture out there, we are poised to become a next gen computing giant."
While many trends are both influencing and restraining enterprise technology adoption, they can all be broadly categorized under three pillars: Infrastructure, Architecture, and Technology. Let's explore what these trends are and how they influence DevOps and DevSecOps adoption in tech corporations worldwide. In computing, architecture is a collection of protocols encompassing the utility, structure, and execution of software applications. Architecture outlines the working of an application and determines the function of each aspect, such as data storage and computing capability, among others. Trends in architecture bring about changes in how technology is manifested and radically modify the work cycle for organizations developing software, making it an influential field over DevOps.
It has been only two weeks into the last month of the year and arxiv.org, the popular repository for ML research papers has already witnessed close to 600 uploads. This should give one the idea of the pace at which machine learning research is proceeding; however, keeping track of all these research work is almost impossible. Every year, the research that gets maximum noise is usually from companies like Google and Facebook; from top universities like MIT; from research labs and most importantly from the conferences like NeurIPS or ACL. In this article, we have compiled a list of interesting machine learning research work that has made some noise this year. This is the seminal paper that introduced the most popular ML model of the year -- GPT-3.
Evolved packet core (EPC, Figure 5) is a distributed system of different nodes, each consisting of diverse network functions (NFs) that are required to manage the LTE network. The EPC consists of data and control data planes: the data plane enforces operator policies (e.g., DPI, QoS classes, and accounting) on data traffic to/from the user equipment (UE), whereas the control plane provides key control and management functions such as access control, mobility, and security management.
Karoly Bozan (email@example.com) is an assistant professor in the Palumbo-Donahue School of Business at Duquesne University, Pittsburgh, PA, USA. Kalle Lyytinen is a Distinguished University Professor and Iris S. Wolstein Professor of Management Design at Case Western Reserve University, Cleveland, OH, USA. Gregory M. Rose is an associate professor in the Carson College of Business at Washington State University, Pullman, WA, USA.
Japan's arm-based Fugaku supercomputing system has been acknowledged as the world's most powerful supercomputer. In June 2020, the system earned the top spot in the Top500 ranking of the 500 most powerful commercially available computer systems on the planet, for its performance on a longstanding metric for massive scientific computation. Although modern supercomputing tasks often emphasize somewhat different capabilities, Fugaku also outperforms by other measures as well. This architecture just wins big time," said Torsten Hoefler of the Swiss Federal Institute of Technology (ETH) Zurich. "It is a super-large step." Hoefler shared the 2019 ACM Gordon Bell Prize with an ETH Zurich team for simulations of heat and quantum electronic flow in nanoscale transistors performed in part on the previous Top500 leader, the Summit System at the U.S. Department of Energy's Oak Ridge National Laboratory (ORNL) in Tennessee.