r/adtech

Hey guys, if you missed it, CytoDyn just settled $500K with investors over claims it misled the market about its drug leronlimab some time ago. And they have already sent the agreement to the court for final approval.

In a nutshell, in 2021, CytoDyn was accused of overstating the effectiveness and regulatory progress of leronlimab. In short, the FDA later said the company’s claims were not supported by data, revealing no clear benefit. 

After this news came out, the stock dropped 25%, and investors filed a lawsuit for their losses.

The good news is that the company recently agreed to settle $500K with them, and already sent this agreement to the court for final approval. So, if you invested in $CYDY when all of this happened, you can check the details and file your claim here.

Anyway, has anyone here invested in $CYDY at that time? How much were your losses, if so?

At U of Digital, we internally put together this list of companies that seem to be among the first movers in the AI ad network space. Curious if anyone here has tried them out, partnered with them, or knows of other players we should add.

Here’s the list so far:

• ADS4GPTS
• Dappier
• ZeroClick
• Evercopy / EverAds
• ProRata ai (Gist Ads, Gist Answers, Gist Attribution)
• Imprezia
• Aryel (In-Chat Ads)
• Kontext
• Koah
• OpenAds AI
• nexad

Has anyone here worked with these? Any insights on how well they actually perform? And are there any other startups in this space worth looking into?

Pre‑AI, user growth was the hard ceiling on revenue. You hit a point where the platform had basically saturated its audience, and the only real growth lever was “more users = more impressions.”

With AI‑driven ad systems, especially in walled gardens, the constraint looks different. The limit isn’t audience size, it’s decision quality: how well the system predicts, ranks, matches, and times the right creative for the right person.

If the model keeps getting better at prediction and learning from conversion feedback, the same user base can yield more and more value. Reach is still nice, but it’s not the primary bottleneck anymore.

So in an AI world, “user growth story” feels less important than “decisioning story.” The real question becomes: how efficiently can a platform turn existing attention into outcomes?

Which might be one reason walled gardens are thriving again: Google and Meta just posted their strongest quarterly ad numbers since the pandemic, with Google up 16% to $77B and Meta up 33% to $56.3B.

Meta released TRIBE v2, an AI model trained on 500+ hours of fMRI scans from 700+ people that predicts how the human brain responds to almost any image, video, or sound. It’s tri‑modal (vision, audio, language) and can do zero‑shot predictions for new people and tasks, effectively acting like a virtual brain that lights up in response to your content.

Marketers are already calling it an “MRI for ads”: upload a spot, get a second‑by‑second map of predicted attention and emotional response, and compare different creatives before you spend on media or run brand‑lift studies. You can already try browser‑based demos where you upload video, audio, or text, and TRIBE v2 returns predicted brain activity as interactive 3D heatmaps for different regions in seconds

Food for thought:
- Neural excitement is an intermediate signal, not a guarantee of sales
- Meta says this is for research/non‑commercial use (for now).

Read on:
https://aidemos.atmeta.com/tribev2
https://www.datacamp.com/tutorial/tribe-v2-tutorial