Long Take: Emergence of Generative Artificial Intelligence sector, and powering DAOs with shallow labor

Gm Fintech Architects —

Today we are diving into the following topics:

• Summary: A lightbulb went off. We have been covering creative artificial intelligence for years, but a new framing of these trends as a generative AI ecosystem by Sequoia illuminated several things for us. First, there is real progress in both infrastructure and applications in this space. Second, augmented humans are able to leverage the entire data set, skill, and labor power of experts at the scale of the human population using these products. And finally, such “shallow” labor of prompting large machine systems could be the core unlock needed for DAOs to build consumer grade products..

• Topics: artificial intelligence, creative AI, generative AI, philosophy, economics, future of work, DAOs, Web3

• Tags: DALL-E, GPT-3, Loot NFT, Botto

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Long Take

Things Popping into View

Source

Have you ever stared at a picture right in front of you, and thought it made perfect sense one way, but then discovered an entire new image in its negative?

Do you see a vase or two faces in the black and white picture above? What about in the thumbnails beneath?

These things are called bi-stable images, and our perception shifts between interpreting them differently. The shape of the thing you did not see was always there, hidden in plain sight. Your not seeing it carries no information — it was merely a function of attention and prioritization by your mind that led you to see one thing first.

We have been thinking about AI and neural networks as applied to human productivity for a while, starting in 2018 with the Augmented Finance and Machine Intelligence report at Autonomous Research.

The term “hallucination” comes up in this writing often. How romantic it is that robots can now hallucinate images, voices, stories! It is the right word for projecting out something into the world out of the uncanny valley.

Still — machine generated / assisted creativity has so far felt like its own thing, a limb, a separate vector of innovation looking for a home in the big complicated world. It can look like a novelty with no clear commercial motion.

But perhaps the shape is already there. Perhaps we just need to see the shape of it.

Collaborating with the Machine

You are reading this on a machine device, on a browser running endless software programs both locally and in some giant cloud server farm. The fact of integrating such cyborg features into daily life are pedestrian. We do not notice the extent to which our cognition has been already altered and enhanced.

But much of that augmentation is at the level of information processing, of making the individual “efficient”, have deeper memory, have more access to knowledge. While our smart phones make us smarter, they do not think on our behalf.

The machine that we are talking about when we talk about artificial intelligence is at the population level, at the scope of humanity. Technologies like DALL-E and GPT3 ingest and digitize not individuals, but all of our population level output. They are a robot intelligence that probabilistically mimics the things people to do to create the overall data structure, in the way that a model of the brain incorporates what neurons do but is not bogged down in each individual neuron’s variations.

And it is with this preamble that we want to introduce the fantastic post and thinking from Sequoia on Generative AI. It has served as the inspiration for this writing. In short, Sequoia sees a new industry platforming happening around generative AI as a productive technology. Let us remind you of the dialectic between building infrastructure and building applications (💎 Long Take here).

Now that the industry has been framed as “Generative AI”, and we noticed its shape in this way, we cannot unsee the framing of what is coming next. Check out the visualizations below.

Source: Sequoia

Anyone who is a user of the products in this emerging industry is able to direct and command population-scale creative machine models to make text, images, code, videos, and eventually, social experiences.