SQREEM Bets on a Large Behavioral Model—Not an LLM—to Predict Audiences

The useful part

SQREEM Touts The Large Behavioral Model – Not The LLM – As The Winning Predictive Engine | AdExchanger: On Wednesday, the behavioral intelligence company appointed Stephen Yap as its new CEO to help make that case. Yap's stint at Perion came at a time when the company was looking to improve its efficiency and combine a number of tech tools into a single platform.

How it works

• After all, how many AI startups these days market themselves as not using machine learning?
• The yoga crowd loves it." If you follow the behavioral thread far enough, you'll eventually see that people who buy travel insurance purchase green tea 22% more often than the average person.
• SQREEM aggregates real-time data through connections into social media platforms, as well as by looking at publicly available open-web data and open-web traffic.
• None of the data can be traced back to an individual, said Raiss, but the platform can track public perception in real time, such as engagement patterns and behavioral shifts before and after a particular...
• Most of the conversations they had were questions about how exactly the parasite spreads.

What to take from it

Brands can connect their own internal agent or dashboard to SQREEM, Yap said, "so we're part of their infrastructure." In response to the Cyclospora query, the model surfaced three audiences who engage with the topic most frequently, Yap said: elderly people, parents with newborns and people with preexisting health issues. The number of AI companies that have "spawned" in the last six months or so is "remarkable," Yap told AdExchanger. Part of what attracted him to SQREEM is that it offers "something that the industry's never seen before," as he put it.

Example or evidence

• It appeals to folks interested in skin care, as well as those who are looking for coffee alternatives.
• For instance, during the peak of the Cyclospora outbreak this summer (or, as Yap so ominously referred to it, "the lettuce issue") one of SQREEM's grocer clients noticed that its profits were dropping.
• SQREEM queried its LBM to understand who was engaging in conversations around Cyclospora and what the main topics of those conversations were.
• Since most of the concerns people had were information based, said Yap, the grocer realized that rather than steering clear of Cyclospora conversations, it should be "embracing" them.

Details worth keeping

In a world overrun with LLMs, SQREEM wants credit for not having one. But, to his credit, this claim has some legitimacy to it. That's the tea Rather than relying on machine learning, SQREEM's large behavioral model (LBM) uses "state-space models," which are a type of mathematical AI model that look at certain variables and track how systems change over time.

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