Top 10 Limitations of Artificial Intelligence and Deep Learning

Artificial Intelligence (AI) has provided remarkable capabilities and advances in image understanding, voice recognition, face recognition, pattern recognition, natural language processing, game planning, military applications, financial modeling, language translation, and search engine optimization. In medicine, deep learning is now one of the most powerful and promising tool of AI, which can enhance every stage of patient care —from research, omics data integration, combating antibiotic resistance bacteria,  drug design and discovery to diagnosis and

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The 10 Properties of Quantum Machine Learning

The top 10 properties and characteristics of quantum machine learning are discussed by Dr. Amit Ray of Compassionate AI Lab. The four groups of quantum artificial intelligence: shallow quantum intelligence, deep quantum intelligence, and quantum creative intelligence are discussed. The 10 M’s of quantum machine learning are: Majestic, Meritorious, Merger, Methodical, Minimum-Maximum: Global Optimization,Mediation, Metaphor, Manifestation, Maturity and Mitigation.

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Machine Learning to Fight Antimicrobial Resistance

The seven top machine learning projects to fight against antimicrobial resistance are explained. Antimicrobial resistance  is one of the key reasons of human sufferings in modern hospitals. Preventing microbes from developing resistance to drugs has become as important issue for treating illnesses across the world. Artificial Intelligence, machine learning, genomics and multi-omics data integration are the fast-growing emerging technologies to counter antimicrobial resistance problems. Here,  Dr. Amit Ray explains how these technologies can be used in seven key areas to counter antimicrobial resistance issues.

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Five Key Benefits of Quantum Machine Learning

Five Key Benefits of Quantum Machine Learning Here, Dr. Amit Ray discusses the five key benefits of quantum machine learning.  Quantum machine learning is evolving very fast and gaining enormous momentum due to its huge potential. Quantum machine learning is the key technology for future compassionate artificial intelligence. In our Compassionate AI Lab, we have conducted several experiments on quantum machine learning in the areas of drug-discovery, combating antibiotic resistance bacteria,

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What’s Holding Back Machine Learning in Healthcare

What is holding back the large scale implementation of machine learning systems in healthcare and precision medicine? In this article Dr. Amit Ray, explains the key obstacles and challenges of  implementing large-scale machine learning systems in healthcare.   Dr. Ray argued that lack of deeper integration, incomplete understanding of the underlying molecular processes of disease it is intended to treat, may limit the progress of implementing large-scale machine learning based reliable systems in

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Roadmap for 1000 Qubits Fault-tolerant Quantum Computers

How many qubits are needed to out-perform conventional computers, how to protect a quantum computer from the effects of decoherence and how to design more than 1000 qubits fault-tolerant large scale quantum computers, these are the three basic questions we want to deal in this article.  Qubit technologies, qubit quality, qubit count, qubit connectivity and qubit architectures are the five key areas of quantum computing are discussed. Earlier we have

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Quantum Computing with Many World Interpretation Scopes and Challenges

Quantum Computing with Many World Interpretation Scopes and Challenges Many scientist believe that Many World Interpretation (MWI) of quantum mechanics is self-evidently absurd for quantum computing. However, recently, there are many groups of scientist increasingly believing that MWI has the real future in quantum computing, because MWI can provide true quantum parallelism.  Here, I briefly discuss the scopes and challenges of MWI for future quantum computing for exploration into the

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Deep Learning Past Present and Future – A Systematic Review

Deep Learning Past Present and Future – A Review Deep learning is making a big impact in many areas of human life for solving complex problems. Deep learning models share various properties and the learning dynamics of neurons in human brain. Deep learning is an umbrella term. It covers many areas of artificial intelligence. In our Compassionate AI Lab, deep learning is now used in medical health care, radiology analysis, old age

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7 Limitations of Molecular Docking & Computer Aided Drug Design and Discovery

7 Limitations of Molecular Docking & Computer Aided Drug Design and Discovery Over the past decades, molecular docking has become an important element for drug design and discovery.  Many novel computational drug design methods were developed to aid researchers in discovering promising drug candidates. In the recent years, with the rapid development of faster architectures of  Graphics Processing Unit (GPU)-based clusters and better machine algorithms for high-level computations, much progress has been

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Artificial Intelligence for Balance Control and Fall Detection of Elderly People

Artificial Intelligence for Balance Control of Elderly People Designing automated balance control system for elderly people is one of the key project  of our Compassionate AI Lab. Here, Dr. Amit Ray discuses about one of the recent project of AI using deep learning algorithms for automatic balance control of elderly people. He explains how machine learning algorithms can be used to study and improve the dynamical properties of postural stability of

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