QKD as a service
1m
·
Creating a podcast
·
QKD as a service is based on key agreement protocols, McEliece Crptosystem and encrypted OTP. Quantum key distribution algorithms will be quantum resistant. Quantum Key distribution as a service will cater to multiple users and generate keys in parallel. Quantum key distribution signals can be generated simultaneously and sent using an optical channel. This is using the key management service pattern which is available in Google, Amazon and Microsoft cloud. The key states are managed through the key management services. The states are generated, used, rotated and destroyed. QKD as a service helps in avoiding attacks and errors. Qubits cannot be replicated because of the law of physics. The secret key are not saved in the Quantum key distribution data stores. The key security is improved because of not saving the quantum keys.
Quantum keys are based on the photon properties for sharing bits between source and destination. The quantum information is used for generation of the keys. The interception of the key is identified as there is a change in the quantum state. The keys which are corrupted will be rejected. Randomness of the keys will be real and hack proof
The episode QKD as a service from the podcast Creating a podcast has a duration of
1:38. It was first published
More episodes from Creating a podcast
Digital Assistants
Digital Assistant tracks users’ habits, activities, and behavioral characteristics. Financial data and products can be personalized to meet and anticipate each user’s unique and changing needs. Each user will have one’s own digital personal financial assistant. Artificial intelligence-based digital assistants can help banks handle their compliance monitoring by creating a natural language processing system to read through the legalities of regulations and reassemble the words into a set of computer-understandable rules. IoT, AI, VR, AR, and bots technologies are changing the way data is created, collected, interpreted, and communicated. It will be important to be able to detect and isolate infected or malicious AI programs immediately, and develop effective policy and laws for governing their development and use so that personal information is safeguarded and not misused.
Personalized medicine - genomics powered by AI
New technique to begin identifying potentially problematic rare genetic variants that exist in the genomes of all people, particularly if additional genetic sequencing information is in the area of personalized medicine. The field of personalized genomics is unable to characterize the rare variants. It is because most of these abnormalities, specifically those that occur in "non-coding" parts of the genome that do not specify a protein, are not tested. Doing so would represent a major advance in a growing field that is focused on the sequencing and analysis of individuals' genomes. This research can scour reams of genetic data along with gene expression to predict the functions of variants from individual's genomes.
Precision medicine blended with genomics modeling helps in identifying the personalized medicine accurately and accelerates the treatment of the disease. In this method, blood-forming stem cells are gathered from the patient to develop blood and
immune cell of different types. Precision medicine blended with genomic modeling can be investigational. This type of technology helps in the revival of the patient’s condition and saving the patient from mortality. In this method, a changed viral vector referred to as lentivirus is used for adding them to the stem cells. This helps in improving gene therapy treatment.
Genomic data with AI and big data helps in improving the targeted treatments to a patient using personalized medicine. Genomic data analysis helps the doctor to think from scratch about the cure using genome data. Genetic testing is used for gathering genome data. It is getting cheaper and health care centers are using it to gather huge genomic data in volumes. Health care centers are using this data with.
Pharma, socioeconomic, and clinical data. Researchers and providers are the users of the data.
AI in Genomics helps to improve the precision medicine or personalized medicine. The goals of the personalized medicine are improving the dis-ease diagnosis, treatment effectiveness, and prognosis. Using AI in genomics, personalized medicine techniques help in detecting patient’s variability in genes. The environmental factors can be isolated from the genetic analysis using the symptoms of the patient. Using this analysis, doctors can customize the treatment and prevent the disease growing in the patient.
No Code AI/ML Platform
No-code AI/ML platforms require no knowledge of programming at all. They can be used by business uses. They need AI in their work and do not have data science and AI teams. You can use No-code solutions to build something simple quickly. You can build classifiers and recommender systems. They are being used in industry for aerial photography, autonomous driving, robotics, and medicine.
Voice based Analytics Platform
Voice-based analytics help enterprises to search for data and generate reports. This solution is based on speech recognition. The reports and results can be presented in different formats as per commands. The voice commands are based on natural language and keyword-based queries. The text-based queries are typically different from voice query length. Voice queries may not be questions but more as commands to search and generate results. The speech recognition and processing happen in steps like coding, synthesis, and recognition. The speech-based queries and commands can be connected or isolated words. The speech can be continuous and spontaneous. The speaker models help in identifying person-specific speech patterns. Speaker specific speech models are accurate and precise for voice-based analytics. Diarisation helps in partitioning the speech into homogeneous segments specific to speaker.
No Code platforms in insurance
I would like to present the Radical rethinking of how we architect and deliver solutions in insurance. There is a trend for using No code Platforms in insurance. No code platform helps insurance companies to radically improve the time to market and delivery of Life, Annuities, Retirement, Accident, P&C consumer, commercial, and Speciality products. Insurance companies can sell their product across different business lines and distribution channels. Digital Transformation in insurance sector can be enabled easily using no code platforms. Applications can be created using drag and drop actions and deployed using DevOps hence reducing total cost of ownership. APIs can be used to integrate with legacy systems. Application can have plugins to configure the APIs.