Artificial intelligence (AI) and machine learning (ML) are two technologies that have witnessed a massive growth trend over the years. In a quest to look for a quick, cost-efficient and innovative way to gain advantages from data science, enterprises are relying more on the use of rapidly growing big data available at their disposal. Data and analytics combined with artificial intelligence (AI) technologies will be paramount to predict, prepare and respond in a proactive and accelerated manner to ensure business continuity during this global crisis and after-forward. In 10 Enterprise Analytics Trends to Watch in 2020, Frank Bernhard, author of SHAPE – Digital Strategy by Data & Analytics, notes that in 2020, deep learning should no longer be considered a buzzword, but a "tempest disruptor in how companies will perform with intelligence against their competitors." To enable largely unsupervised learning against unstructured data in a bid to return hidden signals, deep learning will free up the time of in-demand data scientists to connect insights to action.

GlobalData research has found the top artificial intelligence influencers based on their performance and engagement online. Using research from GlobalData's Influencer platform, Verdict has named twelve of the most influential people in artificial intelligence on Twitter during Q1 2020. Ronald van Loon is a recognised thought leader and a top technology influencer. As director of Advertisement, the influencer provides insights and secures analytics data quality, among other responsibilities. He also serves on the Advisory Board of the wefox Group, a Europe-based insurtech start-up.

In this post, I am going to explain a end-to-end use case of deep learning image classification in order to automate the process of classifying defective and non-defective castings in foundry. Casting Process: Casting is one of the major manufacturing process in which molten metal is poured in to a cavity called mould and allowed to cool till it gets solidified into product. Casting defects: These are the defects in the cast product occurred during the casting process and they are undesirable.There are many types of defect in casting like blow hole, pin hole, burr, shrinkage defects, mould material defects, pouring metal defects, metallurgical defects etc. Casting defects are undesirable and cause loss to the manufacturer, therefore the quality department have to do visual inspection of the products and separate the defective one from the good castings. The visual inspection is labour intensive and time consuming, therefore Convolution Neural Networks (CNN) could be used to automate this process by image classification. The figure 1. shows the Casting Inspector app developed in this project.

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In stochastic systems, numerically sampling the relevant trajectories for the estimation of the large deviation statistics of time-extensive observables requires overcoming their exponential (in space and time) scarcity. The optimal way to access these rare events is by means of an auxiliary dynamics obtained from the original one through the so-called'generalised Doob transformation'. While this optimal dynamics is guaranteed to exist its use is often impractical, as to define it requires the often impossible task of diagonalising a (tilted) dynamical generator. While approximate schemes have been devised to overcome this issue they are difficult to automate as they tend to require knowledge of the systems under study. Here we address this problem from the perspective of deep learning.

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The ultimate vision of artificial intelligence are systems that can handle the wide range of cognitive tasks that humans can. The idea of a single, general intelligence is referred to as Artificial General Intelligence (AGI), which encopmasses the idea of a single, generally intelligent system that can act and think much like humans. However, we have not yet achieved this concept of the generally intelligent system and as such, current AI applications are only capable of narrow applications of AI such as recognition systems, hyperpersonaliztion tools and recommendation systems, and even autonomous vehicles. This raises the question: Is AGI really around the corner, or are we chasing an elusive goal that we may never realize? Dr. Ben Goertzel CEO & Founder of the SingularityNET Foundation is particularly visible and vocal on his thoughts on Artificial Intelligence, AGI, and where research and industry are in regards to AGI. Speaking at the (Virtual) OpenCogCon event this week, Dr. Goertzel is one of the world's foremost experts in Artificial General Intelligence.

What do they have in common? They're all beloved fictional characters from TV shows many of us watched when we were young. In 2018, researchers at the Allen Institute published the language model ELMo. The lead author, Matt Peters, said the team brainstormed many acronyms for their model, and ELMo instantly stuck as a "whimsical but memorable" choice. What started out as an inside joke has become a full-blown trend.