William (Bill) Kemp’s Post

I find this interesting line by Paul Atreides in Dune 2: "Our enemies are all around us, and in so many futures they prevail. But I do see a way, there is a narrow way through." This is an amazing illustration of the Rubin causal model and potential outcomes. 1) Futures are probabilistic and different choices are associated with potential outcomes. 2) The Mentats can see future and history of the human civilization, but only the chosen one can see the future in an unclouded vision. Now we know this vision is the counterfactuals and potential outcomes - the causal effect! To those who are still working on causal inference theory in the tides of AI: "Lisan al-Gaib!" #dune2 #causalinference #ai

Critical thinking and problem-solving skills combined with technical skills to work with AI efficiently are characteristics needed for career growth. AI algorithms can collect data, analyze and present information and perform tasks quickly and efficiently. However, for human sustainability, we need visionary innovation. AI provides future options based on known historical information and shared knowledge. To excel in using AI, a person needs to be skilled at designing good prompts to receive good results. From there, human critical thinking skills are required to use that information to innovate by asking questions, not of technology, but of ourselves. Innovation comes from being able to understand minute details and the interweave of systems. Technodiversity should be less about creating the next great tool to solve a human problem or revolutionizing processes. Our response should be to evaluate the risks within both biosphere and all its systems and the technosphere and its interconnected machinery, logic and algorithms. There was a time when the need to create electricity led to the building of dams causing massive impact to the environment. This built jobs and required a skilled workforce to do those jobs. Decades later, we destroyed those dams for a sustainable future. Humans have an imperative to research before moving forward. For future jobs, we need people who can use technology efficiently and creatively. As teachers, business leaders and legislators we must consider the risks to continue education as usual. Instead of relying on Learning Management Systems and the use of computers to learn the typical subjects of math, science, language, history and philosophy, we must innovate. Humans can and do construct educational experiments. We learn by doing. We gain knowledge of concepts by seeing them in action. Future thinking combined with problem solving are the skills to learn while young and continue to build throughout life. We should not be turning to technology blindly. We should gain knowledge into how technology works and consider impacts. #futurethinking #riskmanagement #efficiency #balance

Here's how you can make sure your skills and expertise stay relevant in the age of #AI. https://lnkd.in/gJaiCxeG

In optimization, Newton's method is renowned for its quadratic convergence, largely due to its optimal step size determined by the Hessian matrix. Unlike gradient descent, which simplifies the step size to a single coefficient, alpha, through line search, Newton's method utilizes the full Hessian matrix. This difference is crucial. In Newton's method, the step size is a matrix that captures the curvature of the objective function, enabling faster and more accurate convergence. However, when we use gradient descent, we collapse this matrix into a scalar coefficient, which degrades performance and slows down convergence. This degeneration from a matrix to a scalar is what costs us efficiency. While calculating the Hessian can be computationally intensive, leading to the use of quasi-Newton methods like BFGS, understanding the fundamental advantage of Newton's method in maintaining a matrix step size can guide better optimization practices. How do you approach the trade-off between computational feasibility and convergence speed in your optimization tasks? Let's discuss the strategies and experiences that have worked best for you. PS if the content brought you value please share with someone who can benefit from it. If not, please tell me how can I improve my content. #Optimization #NewtonMethod #MachineLearning #GradientDescent #DataScience #AI #Algorithm #Performance #Convergence #BFGS

#ai #artificialintelligence : 5 strategies to activate your agency and stay relevant in the age of AI. https://lnkd.in/gJaiCxeG

World Economic Forum Science is always of the human, for the human, and by the human. The recent IT security catastrophe from CrowdStrike was solved by human, NOT by AI nor by any science/technology. Is there any AI that can answer the following questions of business intelligence? "Who, in the Ontario province of Canada, have new US patents granted on the nearest Tuesday (Eastern Time), when the USPTO releases the newly granted US patents on a weekly basis?" "Who, in the "江蘇" province of China, have new US patents granted on the nearest Tuesday (Eastern Time), when the USPTO releases the newly granted US patents on a weekly basis?" With our intellectual property (IP), a Chinese-English multilingual metadata, we can get the full list answers for the above questions. This is a fact. Do you or any of your contacts need our expertise/IP to do the data analysis that AI can't do? Metadata is an enabler. It is like a treasure map for treasure hunting. Without metadata, like a treasure map, NO data can be found/retrieved, even by the most advanced technologies, like AI, high-end chips, supercomputers, etc. https://lnkd.in/g-aJFnXR

YUVAL HARARI - AI, HUMANITY AND WISDOM When Harari asks why the exponential growth of information and knowledge have not been matched by any growth in wisdom, he also looks to the core idea of relationalism: “Wisdom is much older than human history. It is elemental, the foundation of organic life, created not by an infallible God, but by the evolutionary processes of ecological systems over four billion years.” (p.404). While Western science has finally discovered this ecological foundation, our culture and institutions remain highly segmented, still beating to the drum of ‘winner takes all’ as a supposed ‘law of the jungle’. It points to the failure of the Western knowledge system to ever develop a knowledge system that grapples with the distinction between wisdom and knowledge, and therefore has failed to develop any pedagogy for the development of what we mean by wisdom. What does this mean for the new world of AI? Reading through Harari’s grand analysis, we face the real possibility that the arrival of AI might mark the evolution of a new species on Planet Earth: a non-organic intelligence that has agency of its own.

Indeterminacy seems to me a perfect word to qualify the different aspects of our existence as #humans right now. 🍃 With no exception, technology is moving from a deterministic behavior to an indeterministic one, as a reflection of the emergence of non linear use cases and the increasing complexity and sophistication of disruptive technologies especially #AI, based on stochastic models, and #QuantumComputing, inherently probabilistic ( so not to say random and uncertain 🤫) , as it is governed by the laws of quantum mechanics. This technology behavior shift may imply a call to action for all the stakeholders to embrace uncertainty, to educate about this shift, , to invest in R&D encouraging a "fail fast, learn faster" mindset and to review resilience towards unpredictable and non-reproducible errors and faults. 🔔 #weekendthought #AI #Quantum

As #ArtificialIntelligence's use cases expand, we face a reality in which human agency erodes and decision-making is instead exported to machines. To prevent this from happening, each of us can take steps in our own lives to preserve our agency and decision-making capacity. Thinking through the "Complex Five" of knowns and unknowns is a sure-fire way to prepare for the age of #AI. https://lnkd.in/gJaiCxeG    Author: Roger Spitz, President & CEO, Disruptive Futures Institute 

The opposite of Artificial Intelligence (AI) can be considered Natural Intelligence, which refers to the cognitive abilities and intelligence demonstrated by humans and other animals, as opposed to the machine or computer-based intelligence created by humans. - 4o