Stepping Up to the $20+ Billion Per Year ASI Race

Microsoft was already spending over $10.7 billion per quarter to build out data centers and AI compute (Q4 2023). There are reports that Microsoft will increase this capital spending to $50 billion per year. This would be averaging $12.5 billion per quarter. This capex spending is up from $7.8 billion in Q3 2023 (Jan-Apr 2023). …

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AI is Deterministic Based Upon the Starting Data – AI Alignment Could Be Relatively Easy

An OpenAI employee has observed that Large Language Models starting with the same dataset converge to the same point. This would mean curating the data is the critical step in creating safe ASI (Artificial Super Intelligence). If we can front load the AI with the desired ethical and pro-humanity examples, then the resulting AI system …

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Knowledge vs Data is Over 50,000 Times Compression

Peter Diamandis and Emad Mostaque had a Twitter (X) Space to discuss AGI governance, the future of AI, open-source models, and more. Emad Mostaque is the CEO and Founder of Stability AI, a company funding the development of open-source music- and image-generating systems such as Dance Diffusion and Stable Diffusion. Utopia or a Happy Dystopia …

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OpenAI Q* Could Be Based Upon A* Search Without Expansions

John Gibb and Dr Scott Walker talk about what the OpenAI Q Star is. The classic A* algorithm maybe the basis for Artificially Intelligence Super Agents. They discuss potentially game changing Q* algorithm that OpenAI might have tweaked and made into a first Artificially Intelligent Agent. A* (pronounced “A-star”) is a graph traversal and path …

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Teslabot Could Help xAI Grok Catch OpenAI GPT5 in AGI Race

Dr Alan Thompson has been closely tracking all AI and large language models at lifearchitect.ai. Alan believes the Q Star rumors are a red herring but he has been saying the critical next steps to go to 60-80% AGI are humanoid robotics. Humanoid robotics that are could pass Steve Wozniak’s test of AGI: walk into …

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OpenAI Q Star Could Have a Mostly Automated and Scalable Way to Improve

The battle at OpenAI was possibly due to a massive breakthrough dubbed Q* (Q-learning). Q* is a precursor to AGI. What Q* might have done is bridged a big gap between Q-learning and pre-determined heuristics. This could be revolutionary, as it could give a machine “future sight” into the optimal next step, saving it a …

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