July 2022: Reid Hoffman pretotyping NFTs using AI with imposter syndrome

Spotted in the wild:

DALL-E: the AI image generator
that will soon flood your feeds  

Reid Hoffman, a co-founder of LinkedIn, is pretotyping NFT sales generated by the latest AI kid on the block, DALL-E, using the Imposter method.

DALL-E is an AI system that can create images from a natural language description in other words, you input a word, and it makes up a picture. Hoffman is debuting and auctioning his collection on the NFT marketplace Magic Eden and seeing if these AI-generated NFTs can get any traction.


What makes this an Imposter?

This is an interesting case of the Imposter being played out. Despite Hoffman explicitly telling his audience that this is an experiment against other NFTs, it is still an Imposter because he's putting something into the market that is pretending to be something it isn't — in this case, images created using DALL-E masquerading themselves as legitimate digital art.

You can read the Twitter thread here and check out the collection here.
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What’s working well? What could be better?
Using Reid’s massive influence and reach is good because it gets plenty of eyes on the experiment. However, this approach makes it an all-in experiment, and blasting it to his entire audience allows for only one shot at a single pretotype. Many small experiments would be better because you can integrate learning from experiment one into experiment two, and so on.

Noting that it is an experiment also inherently skews results as it attracts early adopters people who wouldn't otherwise interact with this might choose to only do so because it's a) popular and b) they know it isn't the real deal and they don't have to put skin in the game if they don't want to.

‘Launching’ this as a finished product and measuring repeat purchases over time would help to gauge real interest rather than the data that's just being accumulated due to the hype of the experiment and the clout attached with Hoffman's name.

Finally, a question I often ask is, what does good look like for him here? In this instance, is it the number of NFTs sold or the dollars raised?

What are the takeaways?
  • Run smaller experiments in batches of around 100 users — this allows you to get more data over time and iterate your experiments to get better results.

  • Measure multiple results to eliminate hype — 'launch' your product as finished and see what people do with it and then continue to measure it.

  • Be clear on what good looks like — this will help you make meaning out of the data you collect.

And for just a bit of fun, check out Craiyon, formerly DALL-E Mini, and give it a go — we tried it with the word 'Exponentially' and got some interesting results:
In the field
We were invited by Stephen Dowling from BVSSH and Jason Conway from Untap Strategy to share the best approach to scaling innovation through rapid experimentation. One of our attendees, business leader and entrepreneur Maria Muir, shared some valuable insights and key takeaways that we think everyone should consider:

1. In the innovation process, we often skip the step of validating if an idea is even worth pursuing before we assemble a team or write a line of code. The question we need to ask is: Should we do this? There is an opportunity to save EVERY time you decide NOT to build something. This is where pretotyping comes in!

2. As proven by Astro Teller, Captain of Moonshots at Google X, 99% of ideas fail. Failure is the default.

3. Running an experiment that is easy, cheap, and fast maximises the time to learning. Leslie spoke about an example of an experiment that cost <$100, took 4 days to set up, with 100 of the best users, and 8 mins to execute. It failed and saved the organisation $500k.

4. Data over Opinion. Experiments will give you the data that you need to make a decision on where you should invest, as it will reveal what action customers will actually take, not what they think they might do as a survey will tell you.

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Until next month, happy innovating!
Leslie
 
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August 2022: Pretotyping Showdown – returning to the office vs. working from home

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June 2022: Infiltrating LinkedIn to get skin in the game