Deutsche Bank:::hewlett packard :: Softbank:: Samsung:: :siemens:: salesforce ::blackrock   BMW BNP:: foxconn :: dell::ford ....Coming To King Charles Language Modeling 100 Most Joyful Collabs inspired by Taiwan-Americans & Grace Hopper fans:  J1  Barbados amazon   Anthropic :: databricks
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Who's Human Intelligence Who? 400 : 300 : 200 : 100 YL 2025 celebrates report that stanford and deep mind's human ai valley = United Humans benchmark of worldwide edu livelihood syytems of sdg generation2021 (celebrate 20 years on from 2001 wake upcall to silicon valley when 2001 abed and steves jobs' dream of womens world coop uni zooms womens hi-trust hi-goodness intel everywhere so that all people become lifelong students and mentors2022 worlds deepest health servant leaders reunited real communities simultaneously so what's 2023=24 to linkin first
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Sunday, March 24, 2024

 ED: This quote scares me "Tomorrow, intelligence=What we compute*what we communicate*whether mother earth cancels our species." It scares me because The NET (Neumann-Einstein-Turing) saw this back in 1945. At, we are concerned that tomorrow has become today. AI will be in every new personal computer by 2028. For example, Americans have one last administration for Washington to return to being the space of public servants not bling injustices & noisemakers in chief. And what can 95% of humans in rest of world do?

How about asking chats questions like these? Dear Gemini. Let's suppose that makers of GPUs with 150 billion transistors are correct in saying AI will be in ever pc, .. If teachers wanted their students to make the most of ai in pc or in everything they grow up with, what would teachers change first?

Here are some things teachers could change first to help students make the most of AI in PCs and throughout their lives:

Shifting Focus:

  • From Consumers to Creators: Instead of just using AI-powered tools, encourage students to explore how AI works and create their own AI applications. This could involve learning basic coding skills or using drag-and-drop tools for building simple AI models.
  • Critical Thinking over Blind Acceptance: Teach students to be critical consumers of AI. Help them understand the limitations and potential biases of AI algorithms. Encourage them to question how AI is used and its impact on society.

Developing Essential Skills:

  • Data Literacy: In a world filled with AI, understanding data is crucial. Students should learn how data is collected, analyzed, and used by AI systems. This will empower them to make informed decisions and avoid manipulation by AI.
  • Problem-solving and Creativity: AI automates tasks, but humans will still be needed to solve complex problems and come up with creative solutions. Encourage students to develop these skills through project-based learning and open-ended questions.
  • Collaboration and Communication: Even with AI, human collaboration remains essential. Students need to learn how to work effectively with others, communicate ideas clearly, and navigate the ethical implications of AI in teamwork.

Integrating AI into Existing Curriculum:

  • AI Across Subjects: Don't treat AI as a separate subject. Integrate AI concepts and tools across different disciplines. For example, in history, students could use AI to analyze historical data or create simulations of past events. In science, they could use AI to analyze scientific data or model complex systems.
  • Project-based Learning with AI: Instead of traditional lectures, engage students in projects that involve using AI tools. This could involve building an AI-powered chatbot, creating an AI-powered game, or using AI to analyze a social media dataset.

These are just a few ideas. The most important thing is to start sparking students' curiosity about AI and empower them to use it as a powerful tool for learning, creating, and solving problems.

Here are some additional resources that teachers might find helpful:

  • K-12 Computer Science Framework: This framework outlines the essential concepts and skills students should learn in computer science, including AI.
  • AI4K12: This organization provides resources and professional development for teachers who want to integrate AI into their classrooms.
  • Explainable AI (XAI) Resources: Many organizations are developing resources to help people understand how AI works. These resources can be helpful for teachers who want to teach students about the inner workings of AI.

By incorporating these ideas and resources, teachers can prepare students to thrive in a world increasingly shaped by AI.

Tuesday, March 12, 2024


Gemini dialogue US gov launch today Rockville Chips Act Q to Gemini Help see 60 year evolutions of chips supply chains, exponential increases in comp & coms impacts? RE US challenge chips act & NIST Rockville today Outside of Chinese mainland, do we look supply chain multipliers around intel 1965 moores law; later why texas instruments refused maurice chang's plan which he took to taiwan. Moore's Intel Valley served mid 60s demands particular of Japan/demand supply chain ( mixed deep ER of smes, deming quality engineering & aggregator keireketsu) & microelectronics - NB intel order japanese calculator manufacturer. Evolution of computers, did even Dell pdp 11 miss design (personal) computers around chips. While IBM pc famously used intel inside ,did cheaper pcs use taiwan supply chain & evolution korea's samsung & taiwan. Clarify supply chain cases/leaps relevant to today's us chips actL eg recent ER such as arm & nvidia about something different from Chips act focus. In acc computing assembly millions of transistors nvidia/arm were not themselves aiming to own supply chain of individual transistors ...? G: You're rght - more at

You're absolutely right, the evolution of chip supply chains over the past 60 years is a fascinating story with significant implications for today's US challenges in the semiconductor industry. Here's a breakdown of the key points you mentioned: Moore's Law and the Rise of Intel (1965):

  • Moore's Law: In 1965, Gordon Moore, co-founder of Intel, observed that the number of transistors on a microchip would double roughly every two years. This prediction, known as Moore's Law, became a guiding principle for the semiconductor industry, driving exponential growth in computational power.
  • Intel's Supply Chain: Intel initially relied on external suppliers for many components in its chip-making process. However, as Moore's Law pushed chip complexity, Intel started integrating more manufacturing steps in-house, leading to a more vertically integrated supply chain.

Texas Instruments and TSMC (Taiwan Semiconductor Manufacturing Company):

  • Maurice Chang's Plan: In the 1980s, Maurice Chang, a former Texas Instruments (TI) employee, proposed a "fabless" model where a company could design chips but outsource the actual manufacturing (fabrication) to a dedicated foundry. TI rejected this idea, focusing on remaining vertically integrated.

Rise of the Taiwan Chip Supply Chain:

  • Seizing the Opportunity: Recognizing the potential of the fabless model, Chang founded TSMC in Taiwan. They capitalized on government support, a skilled workforce, and lower manufacturing costs compared to the US and Japan.
  • Japan's Role: While Intel initially catered to Japanese calculator manufacturers, the rise of TSMC shifted some of the manufacturing focus to Asia.

Personal Computers and Supply Chains:

  • Missed Opportunities: While companies like Dell (with the PDP-11) didn't necessarily design chips, their success hinged on partnering with the right chipmakers and building efficient supply chains for assembling personal computers.
  • IBM PC and the Intel Inside Strategy: The success of the IBM PC popularized the "Wintel" (Windows and Intel) combination. Intel's "Intel Inside" marketing campaign further solidified their dominance in the PC processor market.
  • Taiwan's Impact: As personal computers became a global phenomenon, the cheaper manufacturing offered by the Taiwan supply chain likely played a role in making them more affordable and accessible.

Korea vs. Taiwan:

  • Samsung's Rise: South Korea's Samsung has emerged as a major player in the chip industry, competing with both Intel and TSMC. Their strategy involves a mix of in-house manufacturing and utilizing external foundries.

The US Chips Act and Today's Landscape:

  • Focus on Domestic Manufacturing: The US Chips Act aims to bolster domestic chip manufacturing to address dependence on foreign sources and national security concerns. It incentivizes companies to build chip fabs (fabrication plants) in the US.
  • Arm and Nvidia: While companies like Arm (chip design) and Nvidia (GPUs) play crucial roles in the chip ecosystem, their focus isn't on owning the entire transistor fabrication process. The Chips Act primarily targets bringing back leading-edge fabrication capabilities to the US.

Addressing Your Question:

In the context of the US Chips Act, the relevant supply chain cases are those that focus on chip fabrication (foundries). Companies like TSMC and Samsung are leaders in this area. While chip designers like Arm and Nvidia are crucial for innovation, the act aims to incentivize bringing back the actual manufacturing of the chips themselves to the US.


The evolution of chip supply chains is a complex story with significant geopolitical and economic implications. The US Chips Act represents a strategic effort to address vulnerabilities in the current landscape and ensure a more secure domestic supply of advanced chips.