AI-guru kan hjälpa Teslas bilar att fatta egna beslut

Reinforcement learning (RL) is an area of machine learning inspired by behaviorist psychology, concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward. The problem, due to its generality, is studied in many other disciplines, such as game theory, control theory, operations research, information theory, simulation-based optimization, multi-agent systems, swarm intelligence, statistics, and genetic algorithms. In the operations research and control literature, the field where reinforcement learning methods are studied is called approximate dynamic programming. The problem has been studied in the theory of optimal control, though most studies are concerned with the existence of optimal solutions and their characterization, and not with the learning or approximation aspects. In economics and game theory, reinforcement learning may be used to explain how equilibrium may arise under bounded rationality. In machine learning, the environment is typically formulated as a Markov decision process (MDP), as many reinforcement learning algorithms for this context utilize dynamic programming techniques. The main difference between the classical techniques and reinforcement learning algorithms is that the latter do not need knowledge about the MDP and they target large MDPs where exact methods become infeasible. Reinforcement learning differs from standard supervised learning in that correct input/output pairs are never presented, nor sub-optimal actions explicitly corrected. Further, there is a focus on on-line performance, which involves finding a balance between exploration (of uncharted territory) and exploitation (of current knowledge). The exploration vs. exploitation trade-off in reinforcement learning has been most thoroughly studied through the multi-armed bandit problem and in finite MDPs.

Openai är ett ideellt forskningsbolag som inriktar sig på artificiell intelligens (AI). Företaget siktar på att avancera "vänlig AI". Med andra ord, att övervaka utvecklingen av "människo-lik intelligens" för att säkerställa ett resultat som gynnar hela mänskligheten och undviker globala katastrofrisker. Ett annat mål är att förhindra företag och regeringar från att få för mycket makt genom dem som använder avancerad AI, och i stället se till att fördelarna med AI delas lika. För att nå det målet syftar organisationen till att "fritt samarbeta" med andra institutioner. Företagarna Elon Musk och Sam Altman är ordföranden i Openai. Tidigare forskare vid Google, Ilya Sutskever är forskningschef. Tidigare Stripe CTO Greg Brockman är CTO. Företaget stöds av 1 miljard amerikanska dollar i åtaganden, bland annat genom Reid Hoffman, Jessica Livingston, Peter Thiel, Amazon Web Services, Infosys och YC Research.