Are you interested in a layman conversation to discuss a variety of fictional or realistic possibilities with AI/ML/Robotics and how far we can reach within our the foreseeable future? Let’s connect for CES.
- Contribute to a prototype for boosting max human speed capabilities in every activity – Stuff Made Here ; Mark Rober; Hacksmith
- Contribute to a prototype that boosts max human brain capabilities – Neuralink; Synchron Inc; Kernel Neurotech
- Contribute to solving 215 petabytes of DNA data for max life expectancy – possible solution Columbia University and the New York Genome Center; Nick Goldman; CRISPR
- Contribute to creating an AI that can pass the Turing Test or reach level 4 – Dojo ; DRIVE Thor; Argo AI
- Contribute to reconfiguring a robotic suit that increases everyday safety – Palantir; Sarcos Technology; Boston Dynamics
- Contribute to an AI system that preserves, creates and recreates back up copies of past max human intelligence beyond time constraint – Joe Rogan interviews Steve Jobs; Tensor Holography; Digital Humans
- Contribute to ML pipelines to support experimentation, continuous integration, deployment (CI/CD), verification, validation, and monitoring of ML models in production – Google Cloud Tech; Amazon Web Services; IBM Watson;
- Contribute to SpaceX, NASA & Blue Origin goal for multiplanet species – SpaceX; Blue Origin; Virgin Galactic
- Disclaimer: Contribute can be a very miniscule contribution
Solving the 215 petabytes of DNA in the human body requires a combination of advanced computational methods, data storage technologies, and collaborative efforts among researchers. Here’s an outline of how this can be approached:
- Data acquisition: Obtain high-quality DNA sequences from a diverse range of individuals using state-of-the-art sequencing technologies. This will ensure that the dataset accurately represents the genetic diversity of the human population.
- Data storage: Develop efficient and secure storage solutions for the large volume of genomic data. This may involve using distributed data storage systems and advanced compression algorithms to reduce the storage footprint.
- Data sharing: Establish appropriate protocols and platforms to facilitate data sharing among researchers, while maintaining data privacy and security standards. This will enable scientists to work collaboratively and make the most of the available genomic information.
- Computation: Develop and use advanced computational methods to process and analyze the genomic data. This may involve parallel processing, machine learning algorithms, and specialized hardware like GPUs or TPUs to handle the massive computational requirements.
- Functional annotation: Use bioinformatics tools and experimental data to annotate and understand the functional significance of the DNA sequences. This will involve predicting the function of genes, regulatory elements, and other genomic features, as well as understanding their role in health and disease.
- Population genetics: Analyze the genetic variation within and between populations to understand the evolutionary history of human populations, as well as the genetic basis of complex traits and diseases.
- Clinical applications: Translate the findings from genomic research into clinical practice by identifying potential medical form targets, developing personalized medicine approaches, and improving diagnostics.
- Ethical considerations: Ensure that ethical considerations are taken into account throughout the research process, including informed consent, data privacy, and the fair distribution of benefits from genomic research.
- Education and outreach: Educate the public and healthcare professionals about the importance of genomics and the potential applications in medicine, as well as the associated ethical and social implications.
By leveraging advanced technologies, collaborative efforts, and a multidisciplinary approach, it is possible to address the challenges associated with solving the human 215 petabytes of DNA, leading to a deeper understanding of human biology and the development of new treatments and therapies for various diseases and reaching maximum life expectancy between 100 to 150 years of age.