Intelligence is a fixed goal with variable means of achieving it (018)
Welcome to Artificial Insights: your weekly review of how to better collaborate with AI.
Happy early September everyone!
This week’s newsletter attempts to showcase some of the big ideas shaping the unfolding area of creative AI. The integration of computational creativity into our workflows is not just a diversion, it's becoming a cornerstone of all kinds of thinking. The value of AI isn't merely in automating tasks but in augmenting human capabilities to think beyond traditional boundaries. It's like adding another layer to the mind's canvas, granting us more shades of creativity than we thought possible.
The concept of centaurs in AI takes this collaboration a step further, suggesting a symbiosis between machine learning algorithms and human intuition. This idea builds on the belief that while AI excels in crunching numbers and identifying patterns at a scale impossible for humans, it lacks the emotional intelligence, ethics, and nuanced understanding that come naturally to us. On the flip side, humans can't process vast amounts of data or perform complex calculations in milliseconds. When you combine these different kinds of intelligence—algorithmic and human—you get a "centaur": an entity that harnesses the strengths of both its components, akin to the mythical creature that's part horse and part human. Such a pairing is already revolutionizing not just how we approach problems, but also how we innovate, empathize, and change as a society.
If this resonates, don’t miss our Sandbox demo tomorrow – link at the bottom of the newsletter.
Neri Oxman discusses the intersection of biology, art, and science in design, emphasizing sustainable projects that use natural entities like silkworms and bees. She envisions a future where objects are grown, not built, and nature connects with technology for ecological advancement.
Convergence: Merging biology, art, and science in design.
Sustainability: Utilizing natural entities for unique products.
Future Vision: Growing objects and harmonizing technology with ecology.
Paper outlining four categories of massive risks associated with advanced AI—malicious use, AI race, organizational risks, and rogue AIs—and suggests ways to mitigate them while unlocking AI's benefits.
Risk Categories: Comprehensive categorization of AI risks, providing a structured framework for understanding threats.
Practical Solutions: Offers actionable mitigation strategies, making it a roadmap for safe AI development.
Dual Focus: Balances caution with optimism, emphasizing both AI's risks and its potential benefits.
Dr. Andrew Ng explores opportunities and challenges in AI, covering its applications in various industries and the potential of low-code/no-code tools. He also touches on social issues like bias and job disruption.
Versatility: Dr. Ng emphasizes AI as a general-purpose technology, applicable across multiple domains.
Developmental Speed: Discusses tools like large language models that could accelerate AI application development.
Social Commentary: Goes beyond the tech to address real-world issues, adding depth to the AI conversation.
The article scrutinizes the outsized influence of four tech billionaires—Thiel, Musk, Zuckerberg, and Andreessen—on the digital world, personal data, and societal norms.
Concentration of Power: Highlights the immense influence these individuals have over popular online platforms.
Reality Alteration: Discusses their aim to replace existing societal and economic systems with more opaque versions.
Authoritarian Tendencies: Points out their methods geared towards maintaining market dominance and protecting their fortunes.
In-depth look at AI's capabilities and shortcomings through a project that aims to test AI intelligence. Despite advancements, the video concludes that surpassing human intelligence remains a challenge for AI.
Testing AI's Limits: The video employs challenging tests to probe AI's abilities, revealing its strengths and weaknesses.
Human vs. AI Intelligence: It emphasizes the gap between human and AI intelligence, particularly in tasks beyond memorization.
A type of database that's specifically designed to handle vector data, unlike traditional relational databases that store data in tabular form. Vector databases work best with multidimensional data, which is mostly used in machine learning applications, recommendation systems, and image/audio processing. They are optimal for situations where high-speed similarity searches and efficient storage of vast datasets are critical.
Many are exploring approaches for combining human and artificial intelligence in group workshops and training. If this is something you are interested in, you should consider joining the upcoming public demo of our AI-driven co-creation tool, Sandbox.
Registration in English (tomorrow 5 September – 11 EST / 17 CET)
Registro em Português (tomorrow 5 September – 17 BRT)
Sandbox allows workshop facilitators to integrate GPT into online or in-person exercises as "smart sticky notes". We are still learning where people's needs are, and would love to hear from people working in this space.
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Artificial Insights is written by Michell Zappa, CEO and founder of Envisioning, a technology research institute.
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