Continual, a startup that aims to bring operational AI to the modern data warehouse-centric data stack, today announced that it has raised a $4 million seed round led by Amplify Partners, with Illuminate Ventures, Essence, Wayfinder and Data Community Fund also participating in the round. With this announcement, Continual is also opening up its service as a public beta, after testing it with a number of select customers in recent months. The data warehousing space is vast but also dominated by a small number of players, like Snowflake, Amazon Redshift, BigQuery and Databricks. This makes it easier for startups that want to tap into the data stored in them to build their own innovations on top. For Continual, that means providing businesses with an accessible tool for building predictive models.

Sometimes these notebooks find their way into production, but their code and structure are often far from ideal. In this session, we cover some best practices around creating and operationalising notebooks. We will talk about structure, code style, refactoring in notebooks, unit testing, reproducibility and more. Nikolay Manchev is a machine learning enthusiast and speaker. His area of expertise is Machine Learning and Data Science, and his research interests are in neural networks with emphasis on biological plausibility. Nikolay was a Senior Data Scientist and Developer Advocate at IBM [masked]) and currently acts as the Principal Data Scientist for EMEA at Domino Data Lab. Talk 3: Generative Deep Learning - The Key To Unlocking Artificial General Intelligence by David Foster Generative modelling is one of the hottest topics in AI. It's now possible to teach a machine to excel at human endeavours such as painting, writing, and composing music. In this talk, we will cover: - A general introduction to Generative Modelling - A walkthrough of one of the most utilised generative deep learning models - the Variational Autoencoder (VAE) - Examples of state-of-the-art output from Generative Adversarial Networks (GANs) and Transformer based architectures.

In this session, we will explore: -How the merging of AI and the Industrial Internet of Things (IIoT) acts as a critical enabler for the transformation of Operations -Discuss best practices making Operational AI a crucial catalyzer for the "operationally intelligent organization"

Apr. 19, 2018 - The University of Waterloo has launched the Waterloo Artificial Intelligence Institute this month, bringing together researchers and businesses in an effort to prepare Canada for future economic and advanced technology disruption. The university describes Waterloo AI as focusing on end-to-end innovation ranging from foundational to operational AI. "Foundational AI advances the field as a whole through research in a number of areas, including statistical learning, deep learning, game theory and data science. Operational AI develops scalable, secure and transparent solutions for a wide range of applications," it says. As part of its mandate, Waterloo AI will pursue new areas of research with societal and business impact including manufacturing, autonomous systems, human-machine interaction, healthcare and more, and will emphasize "timely access to expertise to individuals and industry." "The launch of Waterloo AI enhances Canada's leadership in foundational and operational AI as it brings together world renowned researchers with industry to accelerate innovation and prepare for future disruptions," said Feridun Hamdullahpur, university president and vice-chancellor.

The University of Waterloo has launched the Waterloo Artificial Intelligence Institute today. The AI Institute will focus on foundational AI -- which includes research in statistical learning, deep learning, game theory, and data science that advances the entire industry -- and operational AI, which develops scalable, secure, and transparent solutions for a wide range of applications. "The launch of Waterloo AI enhances Canada's leadership in foundational and operational AI as it brings together world-renowned researchers with industry to accelerate innovation and prepare for future disruptions," said Feridun Hamdullahpur, president and vice-chancellor at Waterloo. "By connecting research talent with industry expertise, Waterloo AI will identify problems and produce solutions that will actively benefit our society." Waterloo AI will pursue new areas of research with societal and business impact, including healthcare, environmental protection, urban planning, manufacturing, autonomous systems, and human-machine interaction, and will emphasize timely access to expertise to individuals and industry.