Tema: AI

#576: Disrupsjon i regnskap og finans bransjen
Lene Diesen
Fra Semine
Tema: AI

#555: Kunstig intelligens og forretningsutvikling
Johan Wedel
Fra Gridd.AI Robotics
Tema: AI

#551: Anvendt AI
Jahn Thomas Fidje
Fra universitetet i Agder
Tema: AI

#546: Fremtidens tekstanalyse gjennom AI
Per Morten Hoff
Fra Anzyz Technologies
Tema: AI

#523 – Vi gjør AI tilgjengelig for alle.
Odd Jostein Svendsli
Fra AIA Science
Tema: AI

#531 – Big AI vs. “hverdags-AI”
Lars Løvlie
Fra Sopra Steria
Tema: AI

#518 – Hvordan og hvorfor vi må åpne black boxen
Odd Are Svensen
Fra Idletechs
Tema: AI

#489 – Fremtidens journalistikk
Haavard Myklebust
Fra Fonn group
Tema: AI

#421 – AI and transformation of the workplace
Jarle Moss Hildrum
Fra Telenor Research
Tema: AI

#414 – AI in Telenor
Astrid Undheim
Fra Telenor ASA
Tema: AI

#339 – Future of human-machine interaction
Tugberk Duman
Fra Futurice
Tema: AI

#319 – Machine Bias
Hanne-Torill Mevik
Fra Making Waves
Tema: AI

#318 – Hva er NLP?
Marit Rødevand
Fra Mito.ai
Tema: AI

#311 – Virtuell assistent
Lars Ropeid Selsås
Fra Boost.ai
Tema: AI

#309 – Livsviktig AI
Helge J. Bjorland
Fra Globus AI
Tema: AI

#290: IFE og Applied AI
Tomas Nordlander
Tema: AI

#215 – Ansvarlig AI
Cathrine Pihl Lyngstad
Tema: AI

#214 – Chatbots
Asbjørn Følstad
Tema: AI

#200 – AI -Keiserens kunstige klær?
André Teigland
Fra Norsk Regnesentral
Tema: AI

#201 – Intelligent og automatisk bildeanalyse
Line Eikvil
Fra Norsk Regnesentral
Tema: AI

#157 – AI in Theory and Practice
Ole Jakob Mengshoel
Fra Dept. of Computer Science, NTNU
Tema: AI

#148 – Maskinlæring for lungelyder
Johan Ravn
Fra Medsensio
Tema: AI

#114 – Kan AI erstatte Google?
Frode Opdahl
Fra Keenious
Tema: AI

#112 – Teknologien og oss
Torunn Aardal
Fra Sykehjemsetaten, Oslo kommune
Tema: AI

#68 – AI og livslang læring
Kristine Eilertsen
Fra Lånekassen
Tema: AI

#67 – Kunstig intelligens i norsk næringsliv
Anne Marthine Rustad
Tema: AI

#65 – Global race for AI excellence
Ieva Martinkenaite
Fra Telenor
Tema: AI

#66 – AI reduserer matsvinn
Bertil Helseth
Fra Intelecy
Tema: AI

#64 – Høydimensjonale data
Valeriya Naumova
Fra Simula Metropolitan Center for Digital Engineering
Tema: AI

#62 – Assisting Intelligence
Knut O Hellan
Fra Companybook
Tema: AI

#63 – Kreativ bruk av data
Erlend Aune
Fra Exabel
Tema: AI

#60 – De største fremskrittene i AI
Halvor Grønaas
Fra Bouvet
Tema: AI

#58 – Kunstig intelligens -den usynlige revolusjonen
Per Kristian Bjørkeng
Fra Aftenposten
Tema: AI

#59 – Kan AI gjøre reiseopplevelsen bedre?
Harald Jellum
Tema: AI

#57 – AI kan gjøre helsetilbudet bedre
Petter Risøe
Fra Diffia AS
Tema: AI

#55 – Overfitting vs. Personalisering
Jon Espen Ingvaldsen
Fra Kantega
Tema: AI

#56 – Kunstig intelligens — mer kunstig enn intelligent
Ariel Fisher
Fra Turning Data Into Products AS / Quantifio
Tema: AI

#53 – Hva er greia med Big Data og AI?
Morten Goodwin
Fra Universitetet i Agder

In computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. More in detail, Kaplan and Haenlein define AI as “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation”. Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”.
The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring “intelligence” are often removed from the definition, a phenomenon known as the AI effect, leading to the quip in Tesler’s Theorem, “AI is whatever hasn’t been done yet.” For instance, optical character recognition is frequently excluded from “artificial intelligence”, having become a routine technology. Modern machine capabilities generally classified as AI include successfully understanding human speech, competing at the highest level in strategic game systems (such as chess and Go), autonomously operating cars, and intelligent routing in content delivery networks and military simulations.
Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism, followed by disappointment and the loss of funding (known as an “AI winter”), followed by new approaches, success and renewed funding. For most of its history, AI research has been divided into subfields that often fail to communicate with each other. These sub-fields are based on technical considerations, such as particular goals (e.g. “robotics” or “machine learning”), the use of particular tools (“logic” or artificial neural networks), or deep philosophical differences. Subfields have also been based on social factors (particular institutions or the work of particular researchers).
The traditional problems (or goals) of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception and the ability to move and manipulate objects. General intelligence is among the field’s long-term goals. Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, artificial neural networks, and methods based on statistics, probability and economics. The AI field draws upon computer science, information engineering, mathematics, psychology, linguistics, philosophy, and many others.
The field was founded on the claim that human intelligence “can be so precisely described that a machine can be made to simulate it”. This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence which are issues that have been explored by myth, fiction and philosophy since antiquity. Some people also consider AI to be a danger to humanity if it progresses unabated. Others believe that AI, unlike previous technological revolutions, will create a risk of mass unemployment.

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