Optimove, a leading CRM marketing platform, announced it has acquired Graphyte, a real-time, cloud-based personalization platform optimizing the web and mobile experience for consumers. The announcement comes on the heels of Optimove's purchase of Kumulos, a leading provider of a personalized messaging platform for mobile applications. The combined purchase price of the two deals was not disclosed. The acquisitions help bolster Optimove as one of the most comprehensive CRM marketing platforms. Its AI-driven solutions autonomously determine the next-best-action for each customer, eliminating the need for marketers to manually map every customer journey.

An important problem faced by auditors is gauging how much reliance can be placed on the accounting systems that process millions of transactions to produce the numbers summarized in a company's financial statements. Accounting systems contain internal controls, procedures designed to detect and correct errors and irregularities that can occur in the processing of transactions. In a complex accounting system, it can be an extremely difficult task for the auditor to anticipate the possible errors that can occur and evaluate the effectiveness of the controls at detecting them. An accurate analysis must take into account the unique features of each company's business processes. An important problem faced by auditors is gauging how much reliance can be placed on the accounting systems that produce the numbers summarized in the financial statements. Accounting systems contain internal controls, procedures designed to detect and correct errors and irregularities that can occur in the processing of transactions. In a complex accounting system, it can be an extremely difficult task for the auditor to anticipate the possible errors that can occur, determine their downstream effects in the accounting system, and evaluate the effectiveness of the controls at detecting them. An accurate analysis must take into account the unique features of each company's business processes. In the United States, the Securities and Exchange Commission requires a yearly independent audit of the financial statements of public companies.

It's Google's biggest retail partnership -- and the most personalized shopping experience it offers -- as it tries to broaden the reach of its voice-powered assistant Home speaker. Wal-Mart announced Monday that it's expanding its grocery delivery service with ride-hailing service Uber, and it's been testing same-day delivery service with Deliv at Sam's Club in Miami. With other Google Express retailers, personalization takes time as the assistant learns shoppers' preferences, says Brian Elliott, general manager of Google Express. Wal-Mart says it will be tapping its 4,700 U.S. stores and its fulfillment network next year to offer more kinds of customer experiences using voice shopping.

Google was the first company to realize the importance of incorporating machine learning in business processes. This is just one example of how machine learning processes in the recording and processing of data can help businesses grow. With the introduction of automated processes, businesses have become increasingly consumer-centric. Incorporating automated processes to record inventory stock and purchase order data is not a luxury, it's a necessity in today's world.

Artificial intelligence (AI) systems, blending data and advanced algorithms to mimic the cognitive functions of the human mind, have begun to simplify and enhance even the simplest aspects of our everyday experiences -- and the automotive industry is no exception. While self-driving cars and complex decision-making are the prime use cases for modern AI, the auto industry continues to search for new ways to engage customers through existing and new channels. Machine learning methods are particularly applicable when it comes to powering new insights within the auto industry because the data sets are large, diverse, and change quickly. Given the vast selection of cars and finance providers available, machine learning has the potential to help car buyers quickly find the vehicles and financing options that are right for them, vastly simplifying their customer journey.

Artificial intelligence (AI) systems, blending data and advanced algorithms to mimic the cognitive functions of the human mind, have begun to simplify and enhance even the simplest aspects of our everyday experiences -- and the automotive industry is no exception. While self-driving cars and complex decision-making are the prime use cases for modern AI, the auto industry continues to search for new ways to engage customers through existing and new channels. Machine learning methods are particularly applicable when it comes to powering new insights within the auto industry because the data sets are large, diverse, and change quickly. Given the vast selection of cars and finance providers available, machine learning has the potential to help car buyers quickly find the vehicles and financing options that are right for them, vastly simplifying their customer journey.

Words then point to shared ideas in our minds [Gärdenfors, 2014]. 5. Language as shared convention A B Wittgenstein and his language games, Philosophical Investigations, 1958 block pillar slab beam Two people building something. Eventually turns into a shared convention for a community 6. Our brains map community conventions to personal sensations and actions sensation representation action • When someone says "beam," we map that to our experience with beams. See: Benjamin Bergen, Steven Pinker, Mark Johnson, Jerome Feldman, and Murray Shanahan "beam" This is what is means for language to be grounded. We negotiate language and meaning as we go Modified from Gärdenfors (2014), which was based on Winter (1998) A fishing pole is a stick, string and hook You can catch fish with a fishing pole Get me some fish Acknowledgement Acknowledgement Break Break • Levels of discourse • Complicated to go up and down the pyramid 9. Conversation has its own rules (pragmatics) • Conversational maxims: Grice (1975, 1978) • Breaking these rules is a way to communicate more than the meaning of the words. Maxim of Quantity: Say only what is not implied. What did she mean by that?

It became apparent that although the power of this technology is very much appreciated in a number of guises (including natural language processing, computer vision, and the processing of unstructured data for account based marketing), there is some confusion about how it applies to personalisation and segmentation. A latent factor model is another method of filtering – using many factors (possibly hundreds) about users and products in order to explain user actions (e.g. Going further down the route of machine learning, and perhaps the easiest part to understand for the layman (me), is the method of analysing products or content to give them meaning (semantics). Advances in natural language processing (a much-publicised product of machine learning and deep learning) mean that content can be explored for explicit and implicit meaning.

Now similar concerns are being raised by the giants that deal in data, the oil of the digital era. Far from gouging consumers, many of their services are free (users pay, in effect, by handing over yet more data). Technology giants have always benefited from network effects: the more users Facebook signs up, the more attractive signing up becomes for others. They could also mandate the sharing of certain kinds of data, with users' consent--an approach Europe is taking in financial services by requiring banks to make customers' data accessible to third parties.