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) …
AI can play a crucial part in automating processes and limiting human involvement to a necessary minimum. Public sector spending on artificial intelligence technologies is expected to accelerate, due to the social distancing measures put in place in response to the coronavirus pandemic. According to market research firm IDC, coronavirus may force some businesses to "revise their technology investments downwards", while others, in particular the healthcare industry, should see a spike in AI spend, as short-staffed hospitals look for quicker diagnostics and testing solutions. "AI is a technology that can play a significant role in helping businesses and societies deal with and solve large scale disruption caused by quarantines and lockdowns," said Andrea Minonne, senior research analyst at IDC. "Of all industries, the public sector will experience an acceleration of AI investments. Hospitals are looking at AI to speed up COVID-19 diagnosis and testing and to provide automated remote consultations to patients in self-isolation through chatbots."
Deep Learning (DL) systems are key enablers for engineering intelligent applications due to their ability to solve complex tasks such as image recognition and machine translation. Nevertheless, using DL systems in safety- and security-critical applications requires to provide testing evidence for their dependable operation. Recent research in this direction focuses on adapting testing criteria from traditional software engineering as a means of increasing confidence for their correct behaviour. However, they are inadequate in capturing the intrinsic properties exhibited by these systems. We bridge this gap by introducing DeepImportance, a systematic testing methodology accompanied by an Importance-Driven (IDC) test adequacy criterion for DL systems. Applying IDC enables to establish a layer-wise functional understanding of the importance of DL system components and use this information to assess the semantic diversity of a test set. Our empirical evaluation on several DL systems, across multiple DL datasets and with state-of-the-art adversarial generation techniques demonstrates the usefulness and effectiveness of DeepImportance and its ability to support the engineering of more robust DL systems.
Artificial intelligence (AI) and machine learning will be everywhere, and we will learn to love them for all the right reasons. Let's begin with the big picture. Gartner analysts said that AI -- with a particular emphasis on machine learning -- will eventually infiltrate just about every existing technology. IDC predicted companies will invest over $265 billion worldwide in new intelligence technologies by 2023. Slightly further out, IDC researchers predicted that AI will be inescapable by 2025.
Artificial intelligence (AI) and machine learning will soon be everywhere, and we will learn to love them for all the right reasons. That is my prediction after seeing the latest research about these fast-evolving technologies. Begin with the big picture: Gartner analysts said that AI -- with a particular emphasis on machine learning -- will eventually infiltrate just about every existing technology. IDC predicted companies will invest over $265 billion worldwide in new intelligence technologies by 2023. Slightly further out, IDC researchers predicted that AI will be inescapable by 2025.
The report, the Worldwide Artificial Intelligence Spending Guide, said that in 2019, worldwide spending on AI is expected to be $37.5 billion, but that this amount will almost treble by 2023, hitting just a smidgeon less than $100 billion -- $97.9 billion. Not only does the IDC report present good news for AI, it also refers to the machine learning phrase -- or ML, a nod to those who work in the business and are often quite frustrated by the over use of the AI acronym with all its connotations with hype. David Schubmehl, research director at Cognitive/Artificial Intelligence Systems at IDC said: "The use of artificial intelligence and machine learning (ML) is occurring in a wide range of solutions and applications from ERP and manufacturing software to content management, collaboration, and user productivity. Artificial intelligence and machine learning are top of mind for most organisations today, and IDC expects that AI will be the disrupting influence changing entire industries over the next decade." The IDC report said that investment in AI will be led by retail and banking industries.
The next few years are going to be lively ones for the datacenter, with more than half of new infrastructure being deployed in edge locations, half of core enterprise datacenters and two-thirds of the major edge IT sites leveraging artificial intelligence (AI) and machine learning (ML), more than half of datacenter infrastructure running "as-a-service" solutions, and a steadily growing number of companies relying on colocation partners. Those were a few of the predictions offered by the industry watchers at IDC last week with the release the analyst firm's first annual "Futurescape" forecast focused on the datacenter. Emphasizing trends emerging in 2020, the report was presented in part during a webcast led by some of its authors. "At the core of all of our predictions is the reality that technology is very rapidly moving from the back office to the front office," said Jennifer Cooke, research director of IDC's Cloud to Edge Datacenter Trends and Strategies research team. "And a lot of this is about the boundaries between an organization's internal operations and external ecosystem of customers, partners and markets. These boundaries are just disappearing."
According to IDC, IBM leads the Worldwide Artificial Intelligence Market. Growing 35.6% to $28.1 billion, the artificial intelligence (AI) market experienced steady growth in 2018. The International Data Corporation (IDC), the premier global provider of market intelligence and advisory services for the information technology industry, has produced an objective study of worldwide artificial intelligence market revenue for 2018. Entitled'Worldwide Artificial Intelligence Market Shares, 2018: Steady Growth -- POCs Poised to Enter Full-Blown Production,' it finds amongst many other things that cost of the solution, lack of skilled personnel, and a bias in data have held organisations from more broadly implementing AI. On the other hand, automation, business agility, and customer satisfaction are the primary drivers for AI initiatives.
With digital transformation initiatives flooding the enterprise, it's no surprise that by 2023, more than half of all worldwide GDP is predicted to be driven by products and services from digitally transformed industries, an IDC report found. This amount of digital integration indicates that the global economy will reach digital supremacy in the next couple years. IDC made predictions for 2020 and beyond during a live webcast on Tuesday. The findings were published in IDC's latest FutureScape report. IDC has documented the rise of the digital economy and digital transformations for the last five years.
IDC released today its worldwide IT industry predictions for 2020 in a webcast with Frank Gens, IDC's senior vice president and chief analyst. The focus for the 10 predictions for next year and beyond is the rise of the digital economy. By 2023, IDC predicts, over half (52%) of global GDP will be accounted for by digitally transformed enterprises. To drive digital supremacy, an enterprise must devote half of its budget to supporting digital innovation, establishing a large-scale, high-performing, digital innovation factories and a third-party ecosystem to produce digital products and provide fee-based wholesale digital services to other enterprise. The latter will be an entire new enterprise competency, similar to the management of Amazon's platform for third-party sellers.
Bottom Line: Attacking endpoints with AI, bots, and machine learning is gaining momentum with cybercriminals today with no signs of slowing down into 2020, making endpoint security a must-have cybersecurity goal for next year. Cyberattacks are growing more complex and difficult to prevent now and will accelerate in the future, making endpoint security a top goal in 2020. Cybercriminals are using structured and unstructured machine learning algorithms to hack organizations' endpoints with increasing frequency. Endpoint attacks and their levels of complexity will accelerate as cybercriminals gain greater mastery of these techniques. In response, endpoint protection providers are adopting machine learning-based detection and response technologies, providing more cloud-native solutions that can scale across a broader range of endpoints, and designing in greater persistence and resilience for each endpoint.