AI Reality For The Masses

I posted this article a few years ago. This is an update.


AI To Benefit All

Overall, AI has the potential to bring many benefits to society, but it’s important to ensure that these benefits are distributed in a way that is equitable and inclusive. By working together, we can help to harness the power of AI for the good of all.

A Few Benefits

  1. Frees up humans for other pursuits: By automating repetitive or mundane tasks, AI can free up humans to focus on more creative, complex, and meaningful work.
  2. Increases human creativity: AI can help humans to generate new ideas, insights, and solutions by processing large amounts of data, identifying patterns, and generating novel combinations of ideas.
  3. Solves issues and common problems: AI can be used to solve a wide range of problems, from medical diagnoses to environmental monitoring to traffic management.
  4. Improves efficiency and productivity: By automating routine tasks and optimizing processes, AI can improve efficiency and productivity in many industries, from manufacturing to finance to transportation.
  5. Enhances decision-making: AI can help humans to make better, more informed decisions by providing data-driven insights, identifying patterns and trends, and predicting outcomes.
  6. Enables new discoveries and innovations: AI can help to accelerate scientific discoveries and technological innovations by processing large amounts of data, simulating complex systems, and generating new hypotheses.
  7. Increases access to resources and services: AI can help to improve access to resources and services, particularly in areas such as healthcare, education, and financial services.
  8. Enhances safety and security: AI can be used to detect and prevent crime, identify and respond to natural disasters, and enhance cybersecurity

Who Affords The Most

  • Our Governments
  • Big Business
  • Independent researchers
  • Technology Firms with Cloud data centers.

Governments have an important role to play in setting regulatory frameworks and policies that promote the responsible development and deployment of AI, while also protecting the interests and rights of citizens. This might include regulations around data privacy, algorithmic bias, and transparency in decision-making.

Big businesses, especially those in the tech industry, are major investors in AI research and development, and have significant influence over the direction and priorities of the field. They also have a responsibility to ensure that their AI systems are developed and used in an ethical and socially responsible way.

Independent researchers and academic institutions play a critical role in advancing the state of the art in AI, developing new algorithms, models, and techniques, and exploring the potential applications of the technology. They can also help to identify and address ethical and social issues that arise in the development and deployment of AI.

Technology firms with cloud data centers are important players in the deployment of AI, as they provide the computing infrastructure and resources needed to train and run large-scale AI models. They also have a responsibility to ensure the security and privacy of data, as well as the responsible use of their cloud computing resources.

Overall, the development and deployment of AI will require collaboration and coordination among a wide range of stakeholders, including government, industry, academia, and civil society. By working together, we can help to ensure that AI is developed and used in a way that is responsible, ethical, and beneficial for all.

Closed Networks

I don’t think it will be you and I. From the available public resources there will be closed networks that do nothing but process purchased records. IE. Medical, browsing history. Etc.

With millions of records being digitized it won’t be long before those are made available to process and correlate to parent type of documents. Human intervention won’t be required at this stage due to automation.

Researchers To Improve Speed

Researchers are looking for ways to improve the speed, delivery and accuracy of (ML – Machine Learning) and AI curated results. By, forming, and modifying the algorithms used to generate results.

One approach to improving machine learning algorithms is to optimize them for specific tasks or applications, such as image recognition, natural language processing, or recommendation systems. This might involve modifying existing algorithms or developing new ones that are better suited to the specific requirements of the task.

Another approach is to improve the quality and quantity of data used to train machine learning models. This might involve collecting more data, improving the accuracy of labeling and annotation, or using techniques such as data augmentation or transfer learning to make better use of existing data.

Researchers are also exploring new techniques for training and evaluating machine learning models, such as reinforcement learning, adversarial training, and self-supervised learning. These techniques can help to improve the accuracy and robustness of machine learning models, and enable them to perform more complex tasks.

Finally, there is ongoing research into the development of hardware and software infrastructure that can support the training and deployment of large-scale machine learning models. This includes the development of specialized processors and accelerators, as well as the development of cloud-based platforms and services that can provide scalable computing resources for machine learning applications.

Overall, the ongoing research and development in machine learning and AI is helping to drive new advances and applications in the field, and is enabling the technology to be used in increasingly complex and diverse applications.


Man machine interfaces the stuff from science fiction is already making an appearance in the form of implantable devices.

Man-machine interfaces are rapidly evolving and becoming more common in everyday life. Implantable devices such as pacemakers, cochlear implants, and deep brain stimulators are already being used to treat a variety of medical conditions, and new implantable devices are being developed for a wide range of applications.

One area of focus for implantable devices is the development of neural interfaces, which allow humans to interact directly with computers or machines using their brain signals. These interfaces can be used for a wide range of applications, from controlling prosthetic limbs to communicating with computers and other devices using thought alone.

Another area of focus is the development of wearable devices that can monitor and track a wide range of physiological and environmental data. These devices can be used to monitor health and fitness, track environmental conditions, or provide real-time feedback on performance or behavior.

As man-machine interfaces become more advanced and more common, there are also important ethical and social implications to consider. These include issues around privacy and data security, the potential for increased dependence on technology, and the potential for unequal access to these technologies based on socioeconomic factors.

Overall, the development of man-machine interfaces is an exciting area of research and innovation, with many potential applications in healthcare, education, entertainment, and other fields. However, it’s important to ensure that these technologies are developed and used in a way that is safe, ethical, and inclusive


Uncharted and cataloged, Science in some backroom, is going on with or without full disclosure to the public. I don’t have proof. I don’t think, I need it. 🙂 As this is only an opinion.

And It’s true that there is ongoing scientific research and innovation taking place in many areas, and it’s likely that not all of this research is publicly disclosed or widely known. This can be due to a variety of factors, including intellectual property concerns, national security considerations, or simply the fact that research takes time to be validated and disseminated.

However, it’s important to note that much of scientific research is conducted through academic and professional channels that prioritize transparency, peer review, and open access to information. While there may be some research that is not publicly disclosed, there is also a wealth of information and knowledge that is openly available and accessible to the public.

Moreover, the responsible development and deployment of new technologies and scientific advancements often requires a collaborative and inclusive approach that involves a wide range of stakeholders, including government, industry, academia, and civil society. This requires transparency and public engagement, as well as a commitment to ethical and social responsibility.

Overall, while it’s possible that some scientific research is not fully disclosed to the public, it’s important to approach these claims with a critical and evidence-based mindset, and to prioritize transparency, collaboration, and ethical responsibility in all scientific research and innovation

But, when news leaks out of foreign governments and private corporations doing genetic testing with human embryos , what are we supposed to do?

When news leaks out about genetic testing with human embryos being conducted by foreign governments or private corporations, it’s important to approach the information with a critical and evidence-based mindset, and to seek out reliable sources of information to verify the claims.

Assuming that the claims are true, it raises important ethical and social questions about the responsible use of genetic testing and editing technologies. These technologies have the potential to bring many benefits, from treating genetic diseases to enhancing human performance, but they also raise significant ethical concerns around issues such as informed consent, privacy, equity, and the potential for unintended consequences or unintended social effects.

In response to these concerns, there are a number of national and international organizations that have developed guidelines and regulations around the use of genetic testing and editing technologies. These include ethical codes and principles developed by professional organizations, as well as regulatory frameworks developed by governments and international bodies.

It’s important to engage in informed and responsible public discourse around these issues, and to work towards developing ethical and socially responsible policies and practices for the development and deployment of genetic testing and editing technologies. This requires collaboration and engagement among a wide range of stakeholders, including scientists, policymakers, ethicists, and the general public

Thoughts & Ideas, Joseph Kravis 🙂

Categories: #kravis, 3D, ART, MODELING, AI

1 reply

  1. Can you be more specific about the content of your article? After reading it, I still have some doubts. Hope you can help me.

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