https://www.youtube.com/watch?v=GY0myVuhrCo&t=14s&ab_channel=AI4ScientificDiscovery Abstract: Professor Charlotte Deane from the University of Oxford speaks about some of the work her research group have done on Machine Learning for Early Stage Drug Discovery to…
https://www.youtube.com/watch?v=o3TSkGgHI78&ab_channel=AI4ScientificDiscovery Abstract: Industrial Digital Technologies (IDTs) such as robotics, AI and IoT are transforming manufacturing worldwide with significant productivity, efficiency and environmental sustainability benefits. This digital revolution is often labelled…
Industrial Digital Technologies (IDTs) such as robotics, AI and IoT are transforming manufacturing worldwide with significant productivity, efficiency and environmental sustainability benefits. This digital revolution is often labelled Industry 4.0 and at its heart is the enhanced collection and use of data. The food and drink sector has been slow to adopt IDT’s for a variety of reasons including the availability of cost effective sensing technologies, capable of operating in production environments. This presentation will discuss the use of IDTs within the important task of food factory cleaning. It will cover the benefits and challenges of deploying robots, sensors and machine learning technologies for factory cleaning tasks in addition to the ever growing importance of effective factory cleaning during a global pandemic.
https://www.youtube.com/watch?v=NhR7xWlAO4g&ab_channel=AI4ScientificDiscovery Abstract: In the last hundred years mankind has fully absorbed the idea of multi-dimensional space, starting with 4D space time. Due to the increase in computational power, scientists can…
In the last hundred years mankind has fully absorbed the idea of multi-dimensional space, starting with 4D space time. Due to the increase in computational power, scientists can now manipulate molecules in 4D (3D vibrating molecules in VR) and work with multidimensional datasets, which are needed to utilize big data and machine learning. However, our intuition from 3D space can fall down when dealing with higher dimensions and a lack of intuition can lead to mistakes in analysis. In this talk I will discuss how to think about the best dimensional space to use to describe chemical problems, how multi-dimensional space is different, techniques for using it and analysing the outputs of machine learning.
This year the AI3SD Network+ (Artificial Intelligence and Augmented Intelligence for Automated Investigations for Scientific Discovery) ran a workshop at the WebSci20 Conference that took place online due to COVID-19 Restrictions. A full report…
This year the AI3SD Network+ (Artificial Intelligence and Augmented Intelligence for Automated Investigations for Scientific Discovery) will be running a workshop at the WebSci20 Conference in Southampton, UK. Artificial and Augmented Intelligence systems have the potential to make a real difference in the scientific discovery domain however this brings a new wealth of ethical and societal implications to consider with regards to this research (e.g. human enhancement, algorithmic biases, risk of detriment). This workshop looks to explore the ethical and societal issues centered around using intelligent technologies (Artificial Intelligence, Augmented Intelligence, Machine Learning, and in general Semantic Web Knowledge Technologies) to further scientific discovery, with a strong consideration of data ethics and algorithmic accountability. Advances in technology and software are rarely inherently bad in themselves, however that unfortunately does not preclude them from being subverted to ill intent by others; furthermore, as demonstrated by the examples above, even an unintentional lack of care towards ethical codes and algorithmic accountability can lead to societal and ethical implications of scientific discovery. It is our responsibility as researchers to consider these issues in our research; are we conducting studies ethically? What ethical codes can we put in place for scientific discovery research to mitigate against ethical and societal issues. These are really important issues, and they require an interdisciplinary focus between scientists, social scientists and technical experts in order to be comprehensively addressed.
Back in January 2019 AI3SD announced their first funding call. We funded 3 pilot projects, and one of the successful applicants of this funding call was Professor Mat Todd from…
This one-day meeting concerns the application of machine learning/artificial intelligence (ML/AI) approaches to the discovery of new drug leads. Specifically the meeting is about cases where the biological target is not clearly established - so-called phenotypic drug discovery. The meeting centers on a real example - a competition run by Open Source Malaria (OSM), funded by a grant from the EPSRC/AI3SD+ Network. Data on active and inactive compounds in one OSM antimalarial series were published online, and anyone was able to submit a model able to predict the actives. The models were judged against a dataset that was kept private, and the winners were asked to use their models to predict novel molecules. These are currently being made in the lab and biologically evaluated, and the results will be reported at the meeting, providing a real-world test, and a complete case study, of the capabilities of ML/AI approaches to accelerate modern drug discovery. We will hear from some of the eleven competition entrants about how their models were constructed, and will have other presentations on related developments. We hope during this meeting to establish which approaches worked well, which did not, and why. All those interested in the application of ML/AI methods to drug discovery are encouraged to attend. The meeting is free, but there will be a cap on numbers, meaning first come first served, meaning registration is essential. Lunch will be provided as part of this event. GitHub Repository: https://github.com/OpenSourceMalaria/Series4_PredictiveModel
In November 2019 AI3SD held their first annual conference to mark the end of the first year of the Network. A full report on this event has been written by…