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Thursday, October 15, 2026· 8784 stock ideas· 217 writers·
15,459 views· 7,325 clicks

[scuttleslops] MRVL, APP, AMZN, Chips

Marvell is positioning networking, optical connectivity and server-management chips as AI data centers link GPUs, custom accelerators and racks, lifting five-year targets.

MRVL $241B
scuttleblurb 1 click

From X

@StableBread

Fajasy on X

I tried to work out who’s behind the AI data labeling companies that approached Nubeva Technologies $NBVAF (TSXV: $NBVA). CEO Randy Chou didn’t name the data labeling companies (firms that turn experts’ knowledge into training data for AI labs) or the customers behind them. “If a data labeling company’s coming to us, somebody behind them is asking,” Chou said, adding that the customer typically isn’t limited to cybersecurity companies. OpenAI is one potential candidate, since my previous write-up concluded that the frontier model Nubeva got access to in September was most likely OpenAI’s, through its Daybreak program for vetted defenders. OpenAI launched GPT-6 Astra on September 3, 2026, the day Nubeva announced its access. It’s the first model OpenAI rated Critical for cybersecurity capability. But access to OpenAI’s model wouldn’t prove OpenAI is also behind the data labeling companies, since any lab building cyber models could want labeled malware. Among data labeling companies, three of the largest are publicly recruiting or selling binary analysis expertise, the skill of figuring out what malware programs do: → Scale AI: Its product manager posting calls the cybersecurity portfolio “a product line that does not exist yet” and says the hire will recruit “malware analysts.” → Turing: Sells CyberBench, security tasks for training and testing frontier models, with malware analysis and reverse engineering among its ten categories. TechCrunch called Turing “a key coding provider for OpenAI” in March 2025. → Mercor: Recruits security experts, preferring reverse engineering or binary analysis backgrounds, and counts OpenAI, Anthropic, and Meta $META as customers. OpenAI cut ties with Scale in June 2025, after Meta bought 49% of Scale and hired its founder, Alexandr Wang. So if OpenAI is behind the approach, Turing and Mercor are the likeliest data labeling companies, since both sell to OpenAI and already sell or buy binary analysis expertise. Either way, these data labeling companies are worth $2.2-29B, so even Turing, the smallest, could pay the top of my $12-19M sale range for Nubeva for less than 1% of its last valuation.
@KEDM_COM

KEDM.com on X

A small but interesting one. Bombe AM disclosed a small stake in Mobile Infrastructure $BEEP and is thinking about taking BEEP private. The Chairman and CEO, Manuel Chavez, and the CEO, Stephanie Hogue, are Bombe partners. No price has been offered yet, as Bombe wants due diligence on property performance, capital needs, and capital structure before setting a premium (not our words). BEEP owns and operates parking lots. Shares have been under pressure as earnings don't cover interest expenses. The thing is now trading at roughly 0.5x book, and it looks like their parking lots are being aggressively amortized on the books.
@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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Genpact LTD

Genpact operates workflows AI is designed to automate and can deploy AI across its existing operations.

G $5.9B
Value Investors Club 1 click

Canterra Minerals: Research Note

Canterra Minerals increased Lundberg indicated tonnage 55% to 26.1Mt, with 226.2Kt of contained copper equivalent, supporting a Buchans…

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Kenorland Minerals: Research Flash

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Is EDA Dead?

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Chipstrat

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