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Moore's Law

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Dr. Gordon E. Moore - RF CafeDr. Gordon Moore, one of the co-founders of Intel Corporation and a prominent figure in the semiconductor industry, articulated his observation in a 1965 paper titled "Cramming More Components onto Integrated Circuits." In this paper, Moore noted that the number of transistors on integrated circuits was doubling approximately every year, leading to a corresponding increase in computing power.

Initially, Moore's prediction was for the number of transistors on a chip to double every year, but he later revised it to approximately every two years. This doubling period has become the widely accepted interpretation of Moore's Law. The doubling of transistors on a chip every couple of years has profound implications for computing power. It means that with each new generation of semiconductor technology, devices can become smaller, faster, and more powerful, or alternatively, maintain the same level of performance while becoming more energy-efficient.

Moore's Law has served as a catalyst for innovation in the semiconductor industry. It has driven research and development efforts to continually shrink the size of transistors and improve manufacturing processes. This progress has led to the miniaturization of electronic devices and the proliferation of computing power in various fields. The exponential growth in computing power facilitated by Moore's Law has had far-reaching effects on society. It has enabled the development of new technologies, such as smartphones, tablets, and wearable devices, as well as advancements in fields like artificial intelligence, data science, and medical diagnostics.

While Moore's Law has held true for several decades, there are challenges and limitations to its continuation. As transistor sizes approach the atomic scale, manufacturing becomes increasingly difficult and costly. Additionally, issues such as power consumption, heat dissipation, and quantum effects pose significant hurdles to further scaling. Over time, Moore's Law has evolved from a specific prediction about transistor count to a broader concept encompassing overall improvements in semiconductor technology and computing power. Even as the pace of transistor scaling may slow, innovations in areas like architecture design, materials science, and packaging techniques continue to drive progress in computing performance.


AI Competition: ChatGPT-Gemini-Grok 3, GabAI - RF CafeThis content was generated by primarily the ChatGPT (OpenAI), and/or Gemini (Google), and/or Arya (GabAI), and/or Grok (x.AI), and/or DeepSeek artificial intelligence (AI) engine. Some review was performed to help detect and correct any inaccuracies; however, you are encouraged to verify the information yourself if it will be used for critical applications. In some cases, multiple solicitations to the AI engine(s) was(were) used to assimilate final content. Images and external hyperlinks have also been added occasionally. Courts have ruled that AI-generated content is not subject to copyright restrictions, but since I modify them, everything here is protected by RF Cafe copyright. Many of the images are likewise generated and modified. Your use of this data implies an agreement to hold totally harmless Kirt Blattenberger, RF Cafe, and any and all of its assigns. Thank you. Here are the major categories.

AI Technical Trustability Update

While working on an update to my RF Cafe Espresso Engineering Workbook project to add a couple calculators about FM sidebands (available soon). The good news is that AI provided excellent VBA code to generate a set of Bessel function plots. The bad news is when I asked for a table showing at which modulation indices sidebands 0 (carrier) through 5 vanish, none of the agents got it right. Some were really bad. The AI agents typically explain their reason and method correctly, then go on to produces bad results. Even after pointing out errors, subsequent results are still wrong. I do a lot of AI work and see this often, even with subscribing to professional versions. I ultimately generated the table myself. There is going to be a lot of inaccurate information out there based on unverified AI queries, so beware.

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