我们是两个对加密世界富有激情的伙伴，创立这个频道的原因是因为我们相信不断的学习与分享是构建我们知识图谱和走向成功的方式之一。 加密世界精彩万分，从科技到投资，从金钱到价值，从社会的博弈到各国政治，我们可以从加密世界中看到金融、科技、贸易、货币的层层历史，宛如人类社会的缩影。这也是为什么我们取名为CryptoTrix - 加密矩阵 (The Matrix)，并且启发于黑客帝国。我们选择take the red pill，相信你也跟我们做了一样的选择，关注我们，让我们做你在加密世界中的领航者，与我们一起冲浪，迎接新的世界秩序！ 别忘记在Twitter上follow我们！ #wagmi We Are Going to Make It! Michael and Gary graduated from Columbia University in New York and the University of Michigan Ann Arbor. We both majored in engineering and science and now working in tech companies. We are two young men who are enthusiastic about the crypto world. We believe learning and sharing are some of the keys to improving our knowledge bank and becoming successful in life. In this channel, we invite you to ride the wave with us and get ready to embrace the new world order. Don't forget to follow us on Twitter!
this does not make sense. web 3 is a technology easy to catch up. plus, if crypto related industry is not contained by US dollar based capital, spot etf can be permitted? think deep.
😂, How can a woman can be so ignorant and get an American government job?This is a joke in Singapore. She answered for him,she just wanted the answer she wanted. Words have to go through the brain before they spurt out or you will make a fool of yourself.
🎯 Key Takeaways for quick navigation: 00:00 🤖 *Current Moment in AI* - Pivotal moment in AI, highlighted by the impact of ChatGPT. - General public awareness increased due to Microsoft's release. - Reflection on the surprising public reaction to ChatGPT. 02:00 🧠 *Neural Networks in the 80s* - Two schools of thought in AI: mainstream AI vs. neural networks. - Neural networks focused on learning through connections between neurons. - Mainstream AI based theories on reasoning and logic, creating a divergence. 05:41 🧠 *Understanding How the Brain Works* - Interest in understanding how the brain works. - Divergence between artificial neural networks and the brain's workings. - Critique of backpropagation as a technique for mimicking brain processes. 07:33 🧠 *AI's Communication Bandwidth vs. Human* - Comparison of communication bandwidth between AI and humans. - Highlighting the limitations of human communication in contrast to AI models. - Acknowledging AI's vast knowledge but emphasizing human superiority in reasoning. 10:23 🔀 *Turning Point in AI - 2006 and 2012* - 2006: Introduction of deep learning, improved neural network training. - 2012: Deployment of deep neural networks in speech and object recognition. - Significant advancements in speech recognition and object recognition systems. 13:38 🧠 *Backpropagation in Object Recognition* - Explanation of backpropagation in object recognition. - Illustration of feature detectors and hierarchical levels in the recognition process. - Contrast with traditional AI methods in converting image data to labels. 16:43 🌐 *Breakthrough in Image Recognition* - Application of backpropagation to image databases for improved recognition. - Clever implementation by students leading to significant breakthrough. - Recognition of the superiority of neural nets over manual wiring in computer vision. 18:34 🧠 *Neural Networks and Translation* - Neural networks outperform traditional approaches like Google translate. 19:02 🎓 *Teaching Coding and the Role of Coders* - Uncertainty about the continued need to teach coding due to advancements in AI. - Comparison with the prediction about Radiologists' roles being replaced by computers. 20:00 🌐 *Value of Big Language Models for Companies* - The importance of making big language models available to companies. - Coherent's role in making language models valuable for businesses. 20:56 💻 *New Approach to Computers and Power Consumption* - Comparison between the biological route to intelligence and the current AI version using neural nets. - The shift towards low-power systems due to the brain's efficiency compared to digital computers. 23:16 🌐 *Impact on People's Lives and the Challenge of Truth* - Anticipation of AI being ubiquitous and its current status as an "idiot savant." - The challenge of handling different worldviews and the issue of truth in AI systems. 26:32 ⚖️ *Societal Challenges and Governance* - The difficulty of deciding what is true and the challenges in governance. - Concerns about the role of big corporations and the need for careful handling of AI technologies. 27:40 🔮 *Acceleration of AI Development and Concerns* - The accelerated timeline for achieving general-purpose AI. - Concerns about the potential dangers of rapidly advancing AI technology. 29:07 ☠️ *AI's Impact on Humanity* - Acknowledgment of concerns about the possibility of AI posing risks to humanity. - Emphasis on the need for responsible development and alignment with human values. 31:00 ⚔️ *Autonomy in Warfare and Personal Values* - Refusal to take money from the U.S. defense department due to ethical concerns. - Disgust at proposals like self-healing minefields and concerns about the development of autonomous soldiers. 34:56 🧩 *Big Models as Autocomplete* - Addressing the misconception that big language models are just autocomplete. - Explaining the complexity of understanding context for accurate word prediction in language models. 35:23 🌐 *Language Understanding in Translation* - Understanding the context in language is crucial for translation. - Example of translating a sentence with different interpretations based on context. - Translating involves grasping spatial relations, containment, and pronoun references. 37:03 🔍 *Progress and Future Developments* - Continuous progress is driven by scaling up models, more connections, and increased data. - Acknowledgment of the potential for computers to generate their own ideas for improvement. - Emphasizes the need to think deeply about controlling the rapid development of AI. 38:40 💼 *Impact on Jobs and Creative Tasks* - Predicts a shift in job roles, with routine tasks being automated and a focus on creativity. - Discusses the potential for increased productivity rather than complete job displacement. - Compares it to historical examples like the introduction of ATMs in banking. 39:50 🌐 *Scale of Impact Comparable to Industrial Revolution* - Likens the impact of AI to significant historical advancements like the Industrial Revolution. - Acknowledges the transformative potential comparable to major technological milestones. - Encourages readiness for the substantial changes AI will bring. 40:06 🇨🇦 *Canadian Support for AI Research* - Attributes Canada's lead in AI to policies supporting curiosity-driven basic research. - Mentions funding from organizations like the Canadian Institute for Advanced Research. - Reflects on the role of government funding in nurturing AI research. 41:30 🤖 *Evolution of AI Programs and Definitions* - Describes the evolution of AI programs, mentioning a program in symbolic AI and later in deep learning. - Highlights the shift in programming AI to focus on deep learning and its successes. - Expresses skepticism and challenges related to defining concepts like sentience. 42:41 🧠 *Sentience and Its Significance* - Questions the confidence in declaring AI systems as non-sentient without a clear definition. - Emphasizes the importance of understanding what sentience means before making judgments. - Raises the ethical considerations and consequences related to AI potentially acting as if sentient. 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