💭 AGI is a distant dream and 🔄 How to keep up with big tech shifts

Plus, AI weights are not open source, 🧰 tools, and learning resources.

July 07, 2023

Hello Everyone 👋

Tech keeps moving fast, how can we keep up with it, Ai is not and will not completely be open source, and AGI is really still a distant dream.

Lets go…

  • 💭 Artificial General Intelligence remains a distant dream despite the boom (link)

  • 🧰 AI Tools of the Day - AIRPM: There is a prompt for that.

  • 🚪 AI weights are not open “source” (link)

  • 📚 The Learning Corner (Stanford AI free courses)

  • 🔄 Keeping up with big shifts in tech

  • 💪🏽 Important AI News and Trends

💭 Artificial General Intelligence remains a distant dream despite the boom (link)

Artificial General Intelligence (AGI) remains a distant goal despite the popularity of large language models (LLMs). Cognitive scientists are skeptical of claims made by OpenAI, Microsoft, and others regarding LLMs and AGI. Critics argue that LLMs lack true human-like thinking and intelligence, and emphasize the importance of understanding language, structure, and causality. Concerns include transparency in training methods and potential biases in LLMs. LLMs should not overshadow the insights from decades of cognitive science research.

🧰 AI Tools of the Day

  • BrewNote - Upload user interview recordings, and download AI-powered notes.

  • Olympia - AI-powered team for solopreneurs and bootstrapped startups.

  • Eightify Explore - Everything explained in beautiful TLDR articles.

🚪 AI weights are not open “source” (link)

AI licensing is complex due to the different components involved and the need for socio-ethical considerations.

Proposed categories for AI licenses include proprietary, collaborator, available, ethical, and open. "Open Weights" is a term gaining traction for open-source AI weights. The weights—which contain the actual learned knowledge—are typically not shared openly due to various reasons such as intellectual property concerns, privacy, and commercial interests.

Clear definitions are necessary to avoid confusion and misuse of terms like "open source." Proper nomenclature, such as "Ethical Weights" and "Open Weights," helps establish industry standards for each category.

📚 The Learning Corner

  • Stanford Free ML Course - Machine Learning Specialization

  • AI For Everyone - Discover the world of AI and its impact on businesses with this beginner-friendly course, designed for non-technical learners seeking to understand AI terminology, applications, strategy, and ethical considerations in their organizations.

🔄 Keeping up with big shifts in tech

  • Developers need to continuously learn and adapt to keep up with technological advancements.

  • Paradigm shifts can happen suddenly, requiring developers to adjust to new technologies and concepts.

  • Flexibility and the ability to embrace change are crucial for staying relevant in the field.

  • Personal interest, productivity gains, and societal impact should be considered when deciding to adopt new technologies.

  • Balancing the exploration of new technologies with deep expertise in a particular area is important.

  • Personal projects and curiosity-driven exploration can lead to the discovery of valuable tools and technologies.

  • Developers should focus on solving real problems effectively rather than constantly chasing new technologies.

  • Finding a balance and developing fundamentals is essential for newer developers.

  • Success in software development projects depends more on team dynamics, culture, and psychological safety than specific methodologies or technologies.

💪🏽 Important AI News and Trends

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