Tzager is an A.I. agent built for biomedicine research, drug discovery and personalized medicine, with the main features being Biochemical Analysis, Predictor Research/Models and Literature Review/Management. The difference with Tzager is that it is not just another deep learning algorithm trained to solve very specific problems, but the intelligence system with its own framework based on Causal Equations and Bayesian Networks.
New Tools, Products And Technologies
Chemical Data Has Problems
The state of data access, quality and dissemination in Chemistry is extremely poor - so poor that it is blocking advances in machine learning (ML) and artificial intelligence (AI), and also impeding research and development in traditional methods. The recent surge in AI skepticism is a direct consequence of years of over-hype and promises based on precarious data. Over-the-top expectation were offered without enough consideration for the data quality and volume required to train fancy algorithms. The old adage “^&$% in, ^&$% out” holds true (we can say ‘crap’ right?). This opinion is in line with recent statements by the CEO of Novartis, for example, who runs the second largest pharmaceutical company in the world, lamenting the difficulty in accessing quality datasets to make AI effective.
(Last updated: 23.08.2018)
Online marketplaces are websites with a “many-to-many” business logic. They can host multiple suppliers trading with multiple buyers via different e-commerce tools available as a part of a website functionality.
Why are online marketplaces great?
Online marketplaces can provide a substantial added value to its users. For example, buyers can quickly compare and select better offerings without the need to research multiple websites and surf online for price comparisons or product specifications. Additionally, marketplaces bring more transparency, trust, and standardization to the whole process of sourcing.
Variational AI is a newly formed artificial intelligence (AI)-driven molecule discovery & drug design startup out of Vancouver, British Columbia, Canada. The company has developed Enki, an AI-powered small molecule discovery service.
The founders of Variational AI are planning to build on top of their state-of-the-art expertise in machine learning, reflected in more than 40 research publications, including those presented at NIPS/NeurIPS, ICML, ICLR, CVPR, ICCV, and other top events in the area of artificial intelligence research.
Molecular mechanics (MM) is a traditional computational approach when it comes to modeling in synthetic organic chemistry, medicinal chemistry and versatile aspects of drug design. However, MM methods have significant limitations, for example, when used to study electron-based properties within the drug-receptor microenvironment. Quantum mechanical (QM) methods allow to substantially increase the accuracy of predictions and provide much more relevant models of chemical and biological objects and their interactions, but QM methods are extremely (often prohibitively) computationally costly.
However, a series of advancements over recent years allowed to expand horizons in this direction, for example, the emergence of density functional theory (DFT), the overall increase in the computation power and the emergence of distributed cloud-based computational infrastructures.