Besides being known as the happiest country in the world, Finland is a technology leader, ahead of China and the US. Finland is making good on its tech legacy, as the University of Helsinki, the Finnish Centre for Artificial Intelligence FCAI, and the City of Helsinki are collaborating to launch a free webinar on the Ethics of AI, followed by a full Ethics of AI course. The ethics of AI is a wildly broad and complex topic, since AI's implications are broad and complex. No industry has gone untouched by AI. In other words, he predicts that AI could cause a billion people to lose their jobs within a year of that article -- nine months from now, as of writing.

In collaboration with BigML partner, INFORM Gmbh, we're pleased to bring the BigML community a new educational webinar: Machine Learning Fights Financial Crime. This FREE virtual event will take place on October 28, 2020, at 8:00 AM PDT / 9:00 AM PDT and it's the ideal learning opportunity for Financial institutions, banking sector professionals, credit professionals, risk advisers, crime fighters, fraud professionals, and anyone interested in finding out about the latest financial crime-fighting and risk analysis strategies and trends. Financial institutions must innovate to stop the onslaught of fraudulent transactions. The utilization of Machine Learning as a tool for fraud detection is trending. Combining Machine Learning with existing intelligent and dynamic rule sets produces a sustainable strategy to address this challenge.

Artificial Intelligence (AI) and Machine Learning (ML) are the key drivers of the future and understanding it has become important for 21st-century kids. We bring to you an Free Demo webinar on *Artificial Intelligence for Kids* with more focus on real-world application-based projects for school-age kids.

WBS Training Ltd organizes workshops and conferences for the capital markets and treasury divisions of investment companies worldwide, with all our efforts centered solely on the education of our clients. WBS Training does not operate to present dozens of events every year. Instead we select only the most innovative, pertinent and dynamic subjects, thus bridging the gap between the latest theoretical developments through to proven practical trading floor requirements. Therefore, we aim to ensure that such requirements can be effectively implemented in the real financial world. Our depth of experience within the training environment provides us with a greater knowledge and understanding of what our clients require from financial business training.

An estimated 100,000 clinicians in the U.S. alone struggle with substance abuse. How can health care companies discourage medication misuse? This is a challenge AI can help solve. Please join speakers Ranjeet Banerjee, Shervin Khodabandeh, and Sam Ransbotham, all contributors to MIT SMR's recent research report, "Winning With AI," as they explore the current state of AI implementation. Banerjee, worldwide president, medication management solutions at Becton, Dickinson and Company, will show how his organization has used AI and machine learning to combat drug diversion, a serious challenge for clinical operations worldwide.

Hear the discussion from copywriter, voice actor and marketer Rew Shearer as he talks through the why, how, and watch out! of chatbot personality in this short live webinar co-hosted by Chief Conversologist Jam Mayer. One of the hardest elements of creating a chatbot is personality. Building a chatbot can be easy. But getting the conversation right is hard. Do you even need a personality for your chatbot – and why?

Lawyers, be forewarned: In what could be a foreshadowing of things to come, a judge has penalized two lawyers for failing to use artificial intelligence. The case comes to us by way of Ontario. It arose after a woman named Kristen Cass slipped and fell in a tavern in Port Dalhousie, a waterfront community on Lake Ontario, 30 minutes by car from Niagara Falls. The tavern owner defaulted, so her lawsuit proceeded solely against the building's owner, the Port Dalhousie Vitalization Corporation (PDVC). PDVC won summary judgment dismissing the action against it.

Lawyers, be forewarned: In what could be a foreshadowing of things to come, a judge has penalized two lawyers for failing to use artificial intelligence. The case comes to us by way of Ontario. It arose after a woman named Kristen Cass slipped and fell in a tavern in Port Dalhousie, a waterfront community on Lake Ontario, 30 minutes by car from Niagara Falls. The tavern owner defaulted, so her lawsuit proceeded solely against the building's owner, the Port Dalhousie Vitalization Corporation (PDVC). PDVC won summary judgment dismissing the action against it.

"Running a lot faster" is something big tech firms could teach banks that are yet to dip their toes in using artificial intelligence (AI), says Adam Shardlow, Lead Journey Manager for AI at the Royal Bank of Scotland (RBS), who has previously also worked for Amazon. He believes AI and machine learning (ML) makes it possible for financial institutions to personalize their offers and revolutionize the way they communicate with customers. We sat down to discuss the opportunities AI offers to banks to get a single view of the customer, enhance customer relations and boost digital sales. Adam is going to be one of the speakers at W.UP's upcoming free webinar on AI & ML on 27 June, where we will share best practices in AI that banks can put into practice with little effort. Participants will also learn all about developing AI capabilities to increase digital sales, unlocking the power of ML in analytics, real-life use cases of AI in digital banking and innovations that help banks explore AI and provide five-star user experiences.

This webinar will demonstrate how to use the new Azure ML Workbench to solve complicated NLP tasks such as entity extraction from unstructured text. The tutorial aims to analyze a large corpus of unlabeled unstructured text records such as Medline PubMed abstracts and trains a word embedding model. The output embeddings are considered as automatically generated semantic features to train a neural entity extractor. We systematically show how to train a word embeddings model using word2vec neural word embedding algorithm with nearly 20 million Medline article abstracts on an HDInsight Spark cluster and then use the auto-generated features to train a LSTM deep recurrent neural network for medical entity extraction on a GPU-equipped Data Science Virtual Machine.