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) …
Amazon Web Services on Wednesday rolled out a series of updates to SageMaker, the AWS service that helps customers build, train and deploy machine learning models. The new capabilities are designed to make it cheaper and easier to use machine learning. First, Amazon SageMaker Ground Truth Plus provides customers with access to workforces that are trained in data labeling. The service makes it faster to create high-quality training datasets, and Amazon says it reduces the costs of creating datasets by 40%. Typically, the proces involves building labeling applications and managing a labeling workforce.
Google used a cluster of 2,048 TPUs to train its largest-ever version of its BERT natural language program, consisting of 481 billion parameters, in 19 hours, as a submission to the MLPerf benchmark competition. The deep learning world of artificial intelligence continues to be obsessed with size. As ZDNet has reported, the state of the art in deep learning programs such as OpenAI's GPT-3 is to keep using more and more GPU chips, from Nvidia and AMD, or novel kinds of accelerator chips, to build ever-larger software programs. In general, accuracy of the programs increases with size, researchers contend. That concern with size was on full display Wednesday in the latest industry benchmark results reported by the MLCommons, which sets the standard for measuring how quickly computer chips can crunch deep learning code.
The Covid-19 crisis has placed the spotlight on the healthcare systems around the world. It placed an additional strain on systems that in many cases were already under stress to meet demand and led to a growth in digital medicine. A video from the BBC observers that Covid-19 brings remote medicine revolution to the UK "Apps which allow doctors to connect with patients remotely have been available for a while, but the coronavirus pandemic has seen doctors finding new ways to consult with critical patient care, including reviewing scans and X-rays from home." McKinsey in an article relating to the US healthcare situation and entitled "Preparing for the next normal now: How health systems can adopt a growth transformation in the COVID-19 world" state that "Covid-19 unprecedented impact on health, economies, and daily life has created a humanitarian crisis. Health systems have been at the epicenter of the fight against COVID-19, and have had to balance the need to alleviate suffering and save lives with substantial financial pressures."
Editors and writers curious about AI's ability to generate long-form writing will want to check-out this piece by SEPGRA, an economic think tank. The group decided to give GPT-3 -- one of the world's most powerful AI text generators -- a run for its money by inputting one, simple phrase and asking GPT-3 to respond. The phrase: "Write an essay about text written by AI." The resulting 900-word essay published in this article is emblematic of the tech's current prowess. Essentially: The piece begins with an excellent focus on the specific topic, but becomes ever-more generalized as the article unfolds. In fact, by the close of the essay, GPT-3 completely veers-off into a discussion of AI's oft-reported ability to beat the world's greatest chess masters.
The past five years have seen robots move from a developing technology in a number of sectors to an indispensable tool supporting operations across a vast range of enterprises. Logistics, manufacturing, materials handling, inspection, healthcare... the list of sectors that have "gone robotic" in short order is long indeed, and with industries like construction and delivery reaching a tipping point, there can be no denying we're in the midst of a robotic renaissance. An executive guide to the technology and market drivers behind the $135 billion robotics market. Automation technologies are maturing, developers are merging and standardizing engineering approaches, and technologies like AI and machine vision are intersecting to unlock a new wave of capability and efficiency. We surveyed some of the most respected and innovation-minded executives shaping the world of automation on what they expect in 2022 and beyond.
Lakeland, Florida-Researcher at Florida Institute of Technology Advanced Mobility Institute We are starting a new phase of work on self-driving car testing and verification. The study is moving from software testing to hardware testing at a new on-campus simulation facility, partially funded by a $ 350,000 grant from the National Science Foundation. The highlight of the project, the deceived autonomous Ford Fusion sedan, has recently arrived in Florida Poly. The car is equipped with sophisticated electronics and has been transformed into a drive-by-wire autonomous test vehicle. "Drive-by-wire means that electronic signals can control steering, acceleration, and braking," said Dr. Onur Toker, an associate professor and researcher in electrical and computer engineering.
Omneky utilizes state-of-the-art deep learning to empower businesses to grow. Human-centered AI promotes the idea that foundation models should be built on the basis of understanding human emotion, language and behavior. To accomplish this, it pairs the usual extensive datasets with human science in order to more effectively tailor its outputs to the common user. At my company, we implement this technique in three different areas: informed decision-making, reliability and scalability and when creating customer-specific advertisements that allow us to appeal to a wide range of audiences. Human-centered AI can prove to be a valuable and informed decision-making tool for companies.
So far, artificial intelligence (AI) is a new enough technology in the business world that it's mostly evaded the long arm of regulatory agencies and standards. But with mounting concerns over privacy and other sensitive areas, that grace period is about to end, according to predictions released on Wednesday by consulting firm Deloitte. Looking at the overall AI landscape, including machine learning, deep learning and neural networks, Deloitte said it believes that next year will pave the way for greater discussions about regulating these popular but sometimes problematic technologies. These discussions will trigger enforced regulations in 2023 and beyond, the firm said. Fears have arisen over AI in a few areas.
Artificial intelligence (AI) and machine learning (ML) have a rapidly growing presence in today's world, with applications ranging from heavy industry to education. From streamlining operations to informing better decision making, it has become clear that this technology has the potential to truly revolutionize how the everyday world works. While AI and ML can be applied to nearly every sector, once the technology advances enough, there are many fields that are either reaping the benefits of AI right now or that soon will be. According to a panel of Forbes Technology Council members, here are 13 industries that will soon be revolutionized by AI. The enterprise attack surface is massive.