The power of AI is its ability to turn unstructured data into structured data

To the extent that large language models (and I should note that while I’m focusing on image generation, there are a whole host of companies working on text output as well) are dependent not on carefully curated data, but rather on the Internet itself, is the extent to which AI will be democratized, for better or worse.

The real power of AI lies in its capability to reclaim vast quantities of data at unknown speeds. This enables AI to identify perceptivity and make assumptions that would be unattainable for humans to achieve individually. This data-driven approach provides significant advantages across various industries, leading to further informed decision-makin

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There is so much more structure in the world than we tend to believe. And LLMs and other AI models are structure discovery machines.

In the current state of the art,  models are only as good as the data they’re trained on  and  the models can’t generate new training data themselves.  AI-generated output is based on the data that trained the AI in the first place, so any data it creates will be a regurgitation of the data it already has. That means that humans

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While LLMs continue to devour web-scraped data, they’ll increasingly consume their own digital progeny as AI-generated content continues to flood the internet. This recursive loop, experimentally confirmed, erodes the true data landscape. Rare events vanish first. Models churn out likely sequences from the original pool while injecting their own un... See more

Almost every company I talk to, and basically every solution vendor, has been pushing for people to use AI to “talk-to-your-data,” an approach allows the AI to retrieve content from a company’s proprietary databases and then work with the documents and data it retrieves. The problem is that AIs hallucinate, or make up plausible information, all the... See more

When it comes to identifying where generative AI can make an impact, we dig into challenges that commonly:

• Involve analysis, interpretation, or review of unstructured content (e.g. text) at scale


• Require massive scaling that may be otherwise prohibitive due to limited resources


• Would be challenging for rules-based or traditional ML approaches

There is no AI Strategy without a Data Strategy

Training AI models requires data. Whether you’re training existing models, developing models from scratch, or simply testing theories, high-quality data is crucial.

Incumbents have the data because they have the customers. They can immediately leverage customers’ data to train models and tune algorithm... See more