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) …
"Synergy" Why it's annoying: Every time I say it on the job, I feel like I've failed somehow as a human being. Why not just say: "You and I make a good team." "Value-add" Why it's annoying: It feels like a term you use when you want to sound more important. Why not just say: added value "Drinking the Kool-Aid" Why it's annoying: The saying is "there's no such thing as bad publicity." The origin of this phrase comes from tragedy.
The great big handsome-goofy face of Ryan Reynolds looms out of the screen in this fantasy comedy from screenwriter Matt Lieberman and director Shawn Levy (of the Night at the Museum franchise). It's an undemanding and cheerfully silly riff on the themes of virtual reality and artificial intelligence, and what the heck we're all doing in this big old universe of ours: as if someone took The Truman Show or Inception – or even The Lego Movie – and stripped out every serious satirical ambition, replacing it with M&M-coloured spectacle. The result is not something that's in any way challenging, but Reynolds is so puppyishly eager to please. Reynolds plays a normal, boring guy whose name is Guy (amusingly, it is never clear if this is his actual given name, as in Guy Crouchback, or the more generic "guy"). He smiles incessantly, wears a bland, short-sleeved blue shirt and goes to work every day as a bank teller in a serenely marvellous-looking modern city, resembling Vancouver.
In some ways, artificial intelligence (AI) and agility form part of a lifecycle: businesses need to be agile to introduce disruptive tech like AI, whilst AI in turn can help businesses achieve true agility. As difficult as the disruption of the past year has been, it has undoubtedly been a driver for businesses to get their priorities straight. The effects of the global pandemic have clearly distinguished between those organizations that are agile and proactive, and those that are not. The latter group has generally found it much harder to cope with market disruptions and will continue to struggle to seize new opportunities. Chris Pope is VP Innovation at ServiceNow.
The National Science Foundation officially extended the reach of its National Artificial Intelligence Research Institutes across more of the United States. On the heels of funding seven institutes in 2020, the agency last week unveiled its establishment of 11 new ones--where officials will strategically pursue AI research in complex realms like augmented learning, cybersecurity, precision agriculture and more. "The expertise of the researchers engaged in the AI Research Institutes spans a wide range of disciplines, providing an integrated effort to tackle the challenges society faces, drawing upon both foundational and use-inspired research," Director of NSF's Robust Intelligence Program Rebecca Hwa told Nextgov Tuesday. "NSF has long been able to bring together numerous fields of scientific inquiry, and in this program that includes such disciplines as computer and information science and engineering, cognitive science and psychology, economics and game theory, engineering and control theory, ethics, linguistics, mathematics, and philosophy--and that has positioned us to lead in efforts to expand the frontiers of AI." In all, the 18 institutes NSF is investing in so far underpin research spanning 40 U.S. states and the District of Columbia, Hwa confirmed.
In a highly regulated industry like banking, innovation always existed within silos bounded by strict regulations. The risks were just too high to think beyond. Besides exorbitant fines and a loss of operating licenses, banks faced reputational risk. Trust, after all, is what banks trade in. Else, customers will simply switch to a more trustworthy bank.
Artificial intelligence and machine learning are the most disruptive technologies, according to IT professionals in the 2020 CIO Tech Priorities Poll. Respondents say these solutions -- more so than cloud, IoT, and analytics -- have the potential to significantly alter the way businesses and entire industries operate. But where is machine learning having the most impact? That's the question we posed to the IDG Influencer Network, a community of industry analysts, IT professionals, and journalists who contribute their knowledge and expertise to the broader IDG community. Here are some key takeaways from their responses.
Machine learning is getting mainstreamed as many organisations have integrated or are trying to integrate ML systems into their products and platforms. MLOps is the branch of ML that unifies ML systems development (dev) and ML systems deployments (ops). We have curated a list of top MLOps books to help you get a handle on the subject (in no particular order). The Machine Learning Engineering book is one of the most complete applied AI books out there and is filled with best practices and design patterns of building reliable machine learning solutions at scale. Andriy Burkov has a PhD in AI and is currently the machine learning team leader at Gartner.
Our goal is to provide quality news content regarding machine learning in medicine for you in this and coming versions. Dataset shift is one of the main challenges for AI model generalization. For example, in a clinical setting, training data may differ from the data used by the model to provide diagnostic, prognostic, or treatment advice. Finlayson et al. have published letters in the New England Journal of Medicine outlining how to identify and potentially mitigate familiar sources of dataset shift in machine learning systems. Casto et al. have considered causal reasoning to tackle different types of shifts in medical imaging.
Fifteen tech start-ups have raised £6.3 million in investment and grants after taking part in a new AI accelerator programme set up by the University of Edinburgh. The accelerator ran for five months from February and sought to help AI startups with high-growth potential. The final 15 companies were chosen from 89 applicants and include Sharktower, a project management software firm that recently raised £400,000 in seed funding, and Reath, a software firm that helps companies become more environmentally friendly. Since enrolling on the accelerator, Reath has secured £313,000 in funding and signed up Marks & Spencer to a pilot scheme, helping the retailer to improve and track re-use of its packaging. Another participant, MyWay, is a diabetes management app that uses AI to predict the efficacy of treatment, employs 30 people and recently raised £1.2 million in grant funding.