Describing systems in terms of choices and their resulting costs and rewards offers the promise of freeing algorithm designers and programmers from specifying how those choices should be made; in implementations, the choices can be realized by optimization techniques and, increasingly, by machine-learning methods. We study this approach from a programming-language perspective. We define two small languages that support decision-making abstractions: one with choices and rewards, and the other additionally with probabilities. We give both operational and denotational semantics. In the case of the second language we consider three denotational semantics, with varying degrees of correlation between possible program values and expected rewards. The operational semantics combine the usual semantics of standard constructs with optimization over spaces of possible execution strategies. The denotational semantics, which are compositional, rely on the selection monad, to handle choice, augmented with an auxiliary monad to handle other effects, such as rewards or probability. We establish adequacy theorems that the two semantics coincide in all cases. We also prove full abstraction at base types, with varying notions of observation in the probabilistic case corresponding to the various degrees of correlation. We present axioms for choice combined with rewards and probability, establishing completeness at base types for the case of rewards without probability.

Artificial Intelligence (AI) has broadly achieved popularity in the music industry in recent years. The primary reason behind it is an evolution that took place in the streaming sector in recent years. Another reason is core music streaming app development. Most artists and streaming app companies are investing in streaming app like Pandora, Spotify, and many others. It helps them to analyze everything starting from users' preferences of the listeners and deliver work accordingly.

The China Welfare Institute launched a Soong Ching Ling Cultural Space on Friday offering the public free education, art and humanity exhibition services. The space on Wuyuan Road unveiled its first exhibition, organized by the China Welfare Institute Children's Palace and Extreme Vision Technology Co, for visitors to learn scientific principles of artificial intelligence, its development trends and how it is applied in our life. There are installations for visitors to experience facial recognition technology. At the entrance is a large screen that can capture facial expressions and produce appropriate memes. Another installation can take a photo of a pair of visitors and analyze the similarity of their appearances.

These days, customer experiences increasingly need to be enabled with the help of intelligent technology. In the past months I have given some examples of how business areas can use AI to improve their part of customer engagements to enable better experiences. Now they have different AI's, but then what? It is time to connect some dots and talk platform. Talking platform does not mean that direct interactions and people are not important – on the contrary; but an increasing number of customers are using the web, social media, or an app to identify suitable products or services, or to resolve an issue, when needed.

Artificial intelligence is the real deal for seemingly every company out there. The big names, including Apple, IBM, Microsoft and Google, are investing large sums to get a competitive advantage on AI. The TV news magazine "60 Minutes" aired a lengthy profile on the status and potential of artificial intelligence, including having their correspondent interview a robot. Should your organization strike up a deeper conversation on AI? Gartner analyst Tom Austin looks at whether smart machines are the smart choice for you.