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Thursday, November 5, 2026

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@ParadisLabs 1 click

Paradis on X

I think Gavin's correct. Open-weight models that compress frontier margins are positive for AI infra -- they don't shrink demand for compute. An example is after Deepseek R1, Tencent, Alibaba and Bytedance *significantly* increased H20 orders...and smaller healthcare & education firms started buying $NVDA H20's to run DeepSeek in-house. So we saw a broadening out of the customer base for the infra providers. In the West, I think $DELL is the best read on whether the buyer base is broadening beyond frontier labs. Hyperscalers mostly buy directly from Taiwanese ODMs, so Dell's AI customers are mostly neoclouds, sovereigns and enterprises. Dell's AI customer count went from >5,000 to >6,500 last quarter (30% growth in one quarter) which management say is mainly down to enterprise acceleration. Feels like that's one of the better public data points on how fast the self-hosting buyer base is growing. Which is a net-positive for AI infra. I don't understand how it can't be?
@StableBread 2 clicks

Fajasy on X

AI labs are paying to close the gap on malware binaries their best models still can’t read. A ransomware nanocap I wrote up last month is now training its own model to read them, after data labeling companies approached its team. Even with far more capable models today, OpenAI and other top AI labs still pay experts to write and grade the problems their models get wrong. And that’s where data labeling companies play a role. They recruit experts in fields where models still make mistakes, like coding, finance, and medicine, and turn what those experts know into graded examples for the labs to train on. Here are just some of the valuations of the largest AI data labeling companies: → Scale AI: Valued at over $29B after $META paid $14.3B for a 49% stake in June 2025. → Surge AI: Was in talks to raise at a $25B valuation in July 2025. → Mercor: Was in talks to raise at a $20B valuation in July 2026. One of the skills the labs need help with is reading malware, the malicious software hackers use to break into or lock up computers. Malware often arrives as a binary, a compiled program in machine code, and many are obfuscated, or scrambled to hide their purpose. In August 2026, researchers led by Columbia University released SRE-Bench, a test of AI models on 262 binaries, and concluded that reverse engineering, or figuring out what a binary does, “remains largely unsolved.” According to Vals AI’s SRE-Bench leaderboard, OpenAI’s GPT-6 Astra claims the top spot, fully solving 56.9% of the binaries. But GPT-6 Astra still can’t fully solve the other 43.1%. Data labeling companies are now recruiting malware experts to train the labs’ models. Scale AI, for example, is hiring a product manager to build a cybersecurity product line, with “malware and binary analysis” among the skills it covers. Mercor also pays security experts $200-250/hour to evaluate AI-generated analyses, preferring people with reverse engineering or binary analysis backgrounds. That demand for malware skills has now reached the ransomware nanocap I wrote up last month. Its CEO said in a new interview that data labeling companies have asked the company to help label what each malware binary does, like whether it’s secretly encrypting files. Its software copies the encryption keys ransomware creates during an attack, so its engineers can build a decryptor (a program that reverses the encryption) and recover a victim’s files without paying the ransom. So is a company the market values at under $10M on track to be acquired by, or partner with, an AI lab or data labeling company? Or is binary analysis another AI plan that misses its targets, like the AI decryptor builder it has pitched since 2023? That's what I talk about in my ~3,500-word company update: https://t.co/IGkfgBX5hR

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Trading Post November 5, 2026

MercadoLibre’s logistics expansion cut margins by 60 basis points, while Mercado Pago grew credit 62% with 7% NPLs.

MELI $77B
Cassandra Unchained 2 clicks

Intel: The CPU Comeback, Discounted

Intel's Q3 2026 results were hit by memory costs and an Israel shutdown, but enterprise AI inference could lift CPU demand as server…

INTC $287B
Monte Independent Investment Research 2 clicks

Problems at Twist Bioscience (TWST)

Twist Bioscience’s $200 rebound followed an Anthropic-linked short squeeze, yet its DNA and protein services face broad competition while…

TWST $8B
Hunterbrook 4 clicks

VSH Earnings Review

Vishay reported record Q3 revenue of $979 million, up 24%, and guided Q4 to about $990 million as rising backlog and margins contrast with…

VSH $3.6B
Cestrian Capital Research 3 clicks

Thursday Tailwinds #13: Nov 5, 2026

Florida marinas are 92% full as boat counts rise and permits constrain new supply, creating pricing power for existing operators such as…

SUI $14B
Trade Ideas Flow 6 clicks

eToro: Expanding Beyond Crypto

EToro trades at 2.89x EV/FCF with $304 million in trailing free cash flow, expanding from crypto into equities, commodities, currencies and…

ETOR $1.9B
Max Arnoldi 5 clicks
SILC · long

Silicom LTD

Silicom (SILC) is pitched as inexpensive on its existing hardware business, with upside framed as a cheap call option.

SILC $183M
Value Investors Club 4 clicks

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