Sunday-June-4–2023

The race mentality we have with AI is not that does not exist, but that the overall race is self-destruction.

Innovation happens over time to build these utopias, Industrial Revolution won’t equal the current time. We ultimately stopped building that infrastructure, especially in America innovation has not been powerful as it could have been but with the technology we have in today’s society it can happen with more of an impact on human life our industries don’t understand the correct direction of where we need to head vs where we are heading

3 components required for the implementation of computerized input - processing- output model

- The computer hardware which provides the physical mechanisms to input and output data, for manipulating data, and for electronically controlling the various input, output, and storage components.
- The software both application and system which provides instructions that tell the hardware exactly what tasks are to be performed and in what order
- The data that is being manipulated, this data may be numeric. It may be alphanumeric it may be graphic or it may take some other form but in all cases it must be representable in a form that the computer can manipulate, In modern systems the input entry, output display and storage of the data and software used for processing often takes place at a location different from the computer where the actual processing occurs.

In some installations actual processing is distributed among computer systems with particular results passed to the individual systems that require them. Which brings a 4th component

- The communication component which consists of hardware and software that transport programs and data between interconnected computer systems.

How to think Non-Likear

How to think NON-Likear PDF

Monday-June-5, 2023

 Notes, Thoughts, inner dialogue. I did not use Grammarly or any text as I hope you can come out with your own take aways as I allow my thoughts to flow in the speaking of human nature and the future of technology. Linear thinking has no place in the AGI period.

Eugene Goostman, a chatbot created in ST. Petersburg, came close to passing the Turing test, in 2014 by using a personality trick. What is intelligence? understanding how the Turing test was built to map out intelligence amongst bots it makes me wonder about SATs, and other test that humans take. Preparing for systems that were placed at birth but like the Eugene Goostman, humans also manipulate to win. We use whatever tactics we can to get an advantage in any situation, but do we still know what intelligence is?

There is no clear definition of intelligence, that is one of the most important problems while most try to keep finding it. They create issues out of insecurities. Instead of using the resource of technology with assisting with the one brain that can think abstract and to understand its self-awarness. Reasoning and (Self-introspection) our subconsious distinguishes, the difference betweens animals and other things that our brands know the names for.

Like a baby when they begin to form a understanding for the world.

computers becoming humans or like humans, need to somehow be modeled internally with our way of thinking. We still need the understanding of what makes a human intelligent before moving forward with warp speed trying to develop something more powerful than the nuclear bomb. Programming intelligence requires the understanding of how decision making works.

Charles Babbage originally created the computer to operate on numbers following defined procedure (an Algorithm) Modern computers follow the same idea of controlled computations but now with more energy to cause harm. Now there may not be away of. stopping consumers of AI doing what they want without harming the process of learning properly about how Artifical Intelligence and Human Intelligence works together in the future of mankind.

As computers were created to their own algorithm frequency, as humans we have created our own societal codes that indeed hindered more of the percentage than we have helped. So the future of technology has a bit more weight this time around and it is very important things are fine tuned from warp speed and "racing" terms.

Creative Process: No one is right.

 

 

The Important Future of Medicine

The integration of Artificial Intelligence (AI) in medicine has the potential to revolutionize healthcare practices. As we examine present technologies, it becomes evident that AI possesses the capability to surpass human limitations and contribute significantly to medical advancements. However, it is crucial to navigate the challenges associated with reliability and decision-making to ensure responsible and effective utilization of AI. This essay explores the potential of AI in medicine, the need for expertise in its implementation, and the role it can play in addressing critical issues in the US healthcare system. 

AI and the Human Element in Medical Decision-making:

Present technologies rely on accumulating and integrating information found on the internet, providing a degree of randomness similar to human responses. 
However, the challenge lies in attributing reliability to the vast knowledge obtained from the internet. Medical knowledge within AI systems, such as GPT, is derived from various sources, including reputable medical institutions, research papers, and discussions on platforms like Reddit. 
The competence of medical professionals reading AI-generated suggestions is vital to ensure the effective utilization of AI as a hypothesis-generation tool in diagnosis.

The Challenges of AI Reliability and Decision-making:

While AI can offer valuable insights, relying solely on it for medical advice may lead to solutions that lack real-world grounding and responsibility towards patients. The integration of AI into medical decision-making requires striking a balance between maximizing reliability, which may result in generic and unhelpful recommendations, and minimizing liability, which can lead to speculative suggestions based on limited data. 
Medical professionals need to interpret and contextualize AI-generated information, considering their expertise and patient-specific factors.

Understanding the Flaws in the US Healthcare System:

The US healthcare system faces numerous challenges, including excessive administrative costs, limited access to affordable care, and suboptimal outcomes compared to other countries. 
The system has become an employment program supporting a large number of administrators, contributing to financial burdens for patients. Additionally, complex regulations and incentives hinder effective oversight and price regulation, resulting in inflated healthcare costs and limited accountability for harmful practices.

Leveraging AI Modeling to Address Healthcare Challenges:

AI modeling can help us understand how the US healthcare system arrived at its current state and provide insights into potential solutions. By incorporating AI into regulatory agencies like the FDA, streamlined processes can reduce barriers for introducing new medications, leading to lower costs for patients. Reevaluating the incentives and culture within the healthcare system is necessary to prioritize patient well-being over excessive regulation and profit-driven practices.

Overcoming Obstacles and Fostering Change:

Revitalizing the US healthcare system requires a concerted effort to address deep-rooted issues. To mitigate the resistance to change, creating alternative systems that can compete with existing structures is crucial. Introducing new healthcare models based on successful systems from other countries can encourage competition, ultimately pressuring the current system to reform and adapt. By allowing for more choice, flexibility, and accountability, a reimagined healthcare landscape can emerge.

The integration of AI in medicine holds immense promise for the future of healthcare. While challenges related to reliability and decision-making exist, responsible implementation and the involvement of competent medical professionals can maximize the potential benefits of AI. 
Furthermore, addressing systemic issues in the US healthcare system requires a comprehensive approach that incorporates AI modeling, alternative systems, and a reevaluation of regulations and incentives. 
By embracing innovation and fostering change, we can pave the way for a more efficient, accessible, and patient-centered healthcare system.