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Thursday, October 15, 2026· 3804 stock ideas· 217 writers·
16,020 views· 7,475 clicks

AppLovin Deep Dive

AppLovin rebuilt its ad model with AXON 2.0, lifting LTM revenue to about $7 billion and margins to 77% as Unity competition threatens auction take rates.

APP $88B
Speedwell Research 3 clicks

From X

@BrokenMoats 1 click

Broken Moats on X

Have to at least acknowledge rate reversal and move into low quality and retail/software today...... But oil/diesel/soft commodities/transportation all staying bid, find this more positioning over extended om rates then durable change (especially with the data and the still unresolved issues causing the inflation) AI sold off I think is what is driving both moves in rates (more out needs a home) and retail/rate sensitive/software were the funding shorts (see sectors and components today) ......but geez at these prices an easier trade I think is to fade software/retail then guess next stop on AI and funding.....the are correlated (for now) anyways. Go through the sectors and components and sort by % gain today almost stacked ranked from worst business (biggest intraday gain) to quality at the bottom.....tells you whats going on. Some might say low quality always leads on a reversal.....this is not a start this is after a stealth sharp move higher for $ARHS $ETSY $EBAY $KSS $SHAK $WMT $CBRL $APPN $DOCU $IT $FRSH $BSP etc.
@convequity 1 click

Convequity on X

AI swarms could make network security more important. Anthropic's October 12 research ran an AI model across 15 cheap Android TV boxes at 0.39 tokens per second. The small models still couldn't reliably complete the full replication cycle. I think we're still early. Inference on this hardware is painfully slow. But the idea is interesting because human-level intelligence isn't necessary for something to reproduce and spread. Think of insects: limited individual intelligence, yet populations can spread widely. An AI worm could carry its model with it, adapt to unfamiliar devices and use compromised hardware to run the next copy. A model too large for one device could be split across several. Better processors and more memory in future cameras, TV boxes and other connected devices would make more local inference possible, wherever attackers can gain access. That creates a security problem beyond installing software on individual devices. You're not going to put an endpoint security agent on every camera or TV box. You need to identify those devices through the network, restrict what they can communicate with and isolate them when compromised. A perimeter firewall alone cannot inspect traffic that never passes through it. I think $FTNT could benefit here. Its agentless device discovery and network segmentation fit this problem, especially across distributed sites. More capable AI on unmanaged devices could increase demand for those controls. The opportunity also extends to networking vendors that integrate security into switches and wireless access points, where they can control how devices connect and communicate.

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