
How AI is helping historians better understand our past
The historians of tomorrow are using computer science to analyze how people lived centuries ago.
How AI is helping historians better understand our past Read MoreArtificial Intelligence (AI) is a broad term with no single authoritative definition — and frequently, people mean different things when they use it.
However, AI commonly means:
The term AI is often imprecise. AI is sometimes used interchangeably with machine learning, but the two terms are not identical. Machine learning is one promising set of techniques used to develop AI, but others exist. We disambiguate machine learning and AI more fully [see the link below].
AI is also a moving target. The “AI effect” is a paradox in which problems thought to require AI, once largely solved, are no longer seen as requiring “intelligence.” This dynamic further contributes to ambiguity around the definition of AI.
—CSET Glossary, “Artificial Intelligence”
Generally, [Artificial Intelligence] constitutes a fuzzy term referring to the ability of a machine to perform cognitive functions. Approaches to AI can be subdivided into deductive—that is, model-driven (such as expert systems)—or inductive—that is, data-driven.
—CACM, “There Is No AI Without Data“
The historians of tomorrow are using computer science to analyze how people lived centuries ago.
How AI is helping historians better understand our past Read MoreDefense tech companies have latched on to the metaverse hype—but what they’re building will be a far cry from Meta’s virtual world.
The US Military Is Building Its Own Metaverse Read MoreVerified AI is the goal of achieving strong, ideally provable assurances of correctness and trustworthiness of AI systems with respect to mathematically specified requirements. Five challenge areas for verified AI: Environment modelling, Formal specification, Modeling learning systems, Scalable formal engines, and Correct-by-construction design.
Toward Verified Artificial Intelligence Read MoreHonorees from this year’s 35 Innovators list are employing AI to find new molecules, fold proteins, and analyze massive amounts of medical data.
AI’s progress isn’t the same as creating human intelligence in machines Read MoreWhat if cybercriminals could hide pernicious payloads in places where commercial cybersecurity software were unable to detect it? Unfortunately, this approach is both possible and increasingly viable.
Hidden Malware Ratchets Up Cybersecurity Risks Read MoreThere is promising, if somewhat slow, progress on making facial recognition software less biased.
The Troubling Future for Facial Recognition Software Read MoreSuperheroes worry about having their identities revealed, while the rest of us in the real world worry about surveillance technologies and how they can be easily abused.
Modern Tech Can’t Shield Your Secret Identity Read MoreThe E.U. is an early mover in the race to regulate AI, and with the draft E.U. AI Act, it has adopted an assurance-based regulatory environment using yet-to-be-defined AI assurance standards.
Trust, Regulation, and Human-in-the-Loop AI: within the European region Read MoreJust-in-time shipping is dead. Long live supply chains stress-tested with AI digital twins.
How AI digital twins help weather the world’s supply chain nightmare Read MoreThe controversy over Project Maven shows the department has a serious trust problem. This is an attempt to fix that.
The Department of Defense is issuing AI ethics guidelines for tech contractors Read MoreDIU launched a strategic initiative in March 2020 to implement the DoD’s Ethical Principles for Artificial Intelligence (AI) into its commercial prototyping and acquisition programs.
Responsible AI Guidelines Read MoreThe U.S. Department of Defense officially adopted a series of ethical principles for the use of Artificial Intelligence today following recommendations provided to Secretary of Defense Dr. Mark T. Esper by the Defense Innovation Board last October.
DOD Adopts Ethical Principles for Artificial Intelligence Read MoreWatch our (home) movie: Trillions of Questions, No Easy Answers
Trillions of Questions, No Easy Answers: A (home) movie about how Google Search works Read MoreAI has not yet delivered on the promises in industry practice. The core business of industrial enterprises is not yet AI-enhanced.
We see a major need for future research regarding functional capabilities and realization technologies for an enterprise data marketplace.
We believe that deep networks excel because they exploit a particular form of compositionality in which features in one layer are combined in many different ways to create more abstract features in the next layer.
A key question for the future of AI is how do humans learn so much from observation alone?
Three key ways artificial intelligence is changing what it means to compute.
How AI is reinventing what computers are Read MorePainstaking new techniques for archiving social media posts could provide crucial evidence in future prosecutions.
The Race to Archive Social Posts That May Prove Russian War Crimes Read MoreWith vast amounts of data becoming available to intelligence analysts, new tools will help them sift and interpret it all—but they will introduce new risks, too.
As Russia Plots Its Next Move, an AI Listens to the Chatter Read MoreThe Artificial Intelligence Database: Explore the technology like never before with [WIRED’s] new database, which collects all of our stories on artificial intelligence and filters them by sector, source data, end user, company, and more.
The Artificial Intelligence Database Read MoreHere, we showcase regionally developed projects that explore the use of non-traditional data sources and AI to help measure progress toward the [Sustainable Development Goals].
Non-Traditional Data Sources: Providing Insights into Sustainable Development Read More