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.
Currently, our algorithm is able to consider a human plan for solving the Rubik's Cube, suggest improvements to the plan, recognize plans that do not work and find alternatives that do. In doing so, it gives feedback that leads to a step-by-step plan for solving the Rubik's Cube that a person can understand. Our team's next step is to build an intuitive interface that will allow our algorithm to teach people how to solve the Rubik's Cube. Our hope is to generalize this approach to a wide range of pathfinding problems.
Over 20 years of experience creating AI that delivers business impact. One of the reasons I wrote a book titled AI is a Waste of Money was that I kept hearing the same AI horror story over and over. The story usually goes like this: A business adopts AI, hoping it will improve one or more of its business functions. Instead, the business finds itself in the grips of what I've come to call "the AI death spiral." While using AI increases their revenues, it completely destroys profitability.
Fox News Flash top entertainment and celebrity headlines are here. Check out what's clicking today in entertainment. Disney is defending the host of a new "Star Wars" web series amid backlash to tweets some deemed to be racist toward White people. Krystina Arielle announced this month that she will host "The High Republic Show," a web series offering news and insights into the latest multimedia subseries of the immensely popular science fiction franchise. However, shortly after announcing Arielle as the host of the new bi-monthly show, some combed through her past tweets and found several that spoke in somewhat harsh terms about White people's role in dismantling racism.
A well-known hacker has leaked this week the details of more than 2.28 million users registered on MeetMindful.com, Here is a step-by-step guide to reducing your digital footprint online, whether you want to lock down data or vanish entirely. The dating site's data has been shared as a free download on a publicly accessible hacking forum known for its trade in hacked databases. The leaked data, a 1.2 GB file, appears to be a dump of the site's users database. The content of this file includes a wealth of information that users provided when they set up profiles on the MeetMindful site and mobile apps.
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.
A group of researchers from Stanford have developed a way to combine processors and memory on multiple hybrid chips to allow AI to run on battery-powered devices such as smartphones and tablets. The team believes that all manner of battery-power electronics would be smarter if they could run AI algorithms. The problem is efforts to build AI-capable chips for mobile devices have run up against something known as the "memory wall." The memory wall is the name for the separation of data processing and memory chips that have to work together to meet the computational demands of AI. Computer scientist Subhasish Mitra says the transactions between processors and memory can consume 95 percent of the energy needed to perform machine learning and AI, severely limiting battery life.
High-throughput sequencing technologies have rapidly developed during the past years and have become an essential tool in plant sciences. However, the analysis of genomic data remains challenging and relies mostly on the performance of automatic pipelines. Frequently applied pipelines involve the alignment of sequence reads against a reference sequence and the identification of sequence variants. Since most benchmarking studies of bioinformatics tools for this purpose have been conducted on human datasets, there is a lack of benchmarking studies in plant sciences. In this study, we evaluated the performance of 50 different variant calling pipelines, including five read mappers and ten variant callers, on six real plant datasets of the model organism Arabidopsis thaliana. Sets of variants were evaluated based on various parameters including sensitivity and specificity. We found that all investigated tools are suitable for analysis of NGS data in plant research. When looking at different performance metrics, BWA-MEM and Novoalign were the best mappers and GATK returned the best results in the variant calling step.
Augmented analytics: the combination of AI and analytics is the latest innovation in data analytics. For organizations, data analysis has evolved from hiring "unicorn" data scientists – to having smart applications that provide actionable insights for decision-making in just a few clicks, thanks to AI. Augmenting by definition means making something greater in strength or value. Augmented analytics, also known as AI-driven analytics, helps in identifying hidden patterns in large data sets and uncovers trends and actionable insights. It leverages technologies such as Analytics, Machine Learning, and Natural Language Generation to automate data management processes and assist with the hard parts of analytics. The capabilities of AI are poised to augment analytics activities and enable companies to internalize data-driven decision-making while enabling everyone in the organization to easily deal with data.
Technology and digital innovation are increasingly becoming the hottest trends in healthcare. The hype is largely well justified, considering the significant strides the field has made in recent years. One of the most significant areas where technology has really made an impact is in the field of cancer care and treatment. Among the most famous examples is IBM Watson, which has made vast inroads in the field of cancer. The Watson platform was developed with a broad vision to bring "data, technology and expertise together to transform health."