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Friday, October 16, 2026· 3901 stock ideas· 217 writers·
17,054 views· 7,877 clicks

Is The Market Turning The Page?

CoreWeave’s debt and equity price action is framed as a wake-up call for investors amid a broader market discussion.

CRWV $43B
WHAT ARE WE DOING? “Contrarians At The Gate” 42 clicks

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@StableBread

Fajasy on X

Even if the AI model Nubeva Technologies $NBVAF (TSXV: $NBVA) is training to read malware binaries (compiled programs) works, six risks could keep it from paying off: → Labs closing the gap: OpenAI’s GPT-6 Astra nearly doubled GPT-5.6-sol’s score on SRE-Bench, a Columbia University-led test of AI models on reading binaries, within a month of SRE-Bench’s release, and Anthropic says its Claude Mythos Preview model can already reconstruct plausible source code from stripped binaries. The better the labs’ own models get at reading hard binaries, the less they need to pay for outside labels. → Big tech building in-house: Microsoft’s $MSFT Project Ire reverse engineers software files on its own to decide whether they’re malicious. Ire caught only about a quarter of the malware among nearly 4,000 hard-to-classify files in a test Microsoft described in August 2025. But in June 2026, Microsoft said Ire flagged a new malware sample that most major security products, including CrowdStrike’s $CRWD and SentinelOne’s $S, still missed. Google $GOOGL already owns VirusTotal and Mandiant, so the likelier customers are labs that don’t own a malware-scanning site or an incident-response firm already, like OpenAI and Anthropic. → Paid like a contractor: Data labeling companies (firms that turn experts’ knowledge into training data for AI labs) pay 60-70% of what they bill to their contractors, and Scale AI is already recruiting its own malware analysts. So a data labeling company could pay Nubeva by the hour or task, or hire analysts itself, instead of licensing the model or buying the company. → Selling labels teaches the buyer: Every binary Nubeva labels helps the buyer’s model learn the same skill, the reason CEO Randy Chou gave for not patenting how Nubeva reads binaries. So each sale could shrink the edge Nubeva is selling. → Cash and compute: Chou gave no cost for running “hundreds and thousands” of AI agents on a private model. For reference, Nubeva spent $714,772 on R&D in FY2026, equal to 28.7% of its $2.49M in cash as of April 30, 2026. → Missed targets: Nubeva’s AI decryptor builder missed four targets starting in August 2023, so “days and weeks” (Chou’s timeline for the model) is a target, not a result just yet. So even with a working model, Nubeva still has to (1) sign a contract before the labs can read the hardest binaries themselves, (2) get paid for its model and engineers instead of by the hour or task, and (3) fund the training without draining its cash.
@convequity 1 click

Convequity on X

3D chips could create more room for specialist EDA startups. We are not convinced that more difficult chip design automatically translates into a large revenue windfall for $SNPS, $CDNS and Siemens. Fine-pitch stacking changes decisions that used to be made within one die. Put a circuit upstairs and its wires may get shorter, but its heat affects the circuit below. Placement, signal timing and power delivery have to be optimized together across the stack. That creates a reason for $AVGO and $NVDA to build custom tools around their architectures. Broadcom already describes a proprietary design flow built on industry-standard tools. Nvidia publishes its own research on assigning connections across tiers in 3D chips. Our inference is that the chip designers will keep some of the most differentiating optimization work in-house. A startup that solves a costly gap in cross-die planning or optimization could also win business without replacing an entire EDA suite. The incumbents still supply implementation, verification and manufacturing sign-off tools, and they are developing 3D capabilities themselves. Internal tooling is evidence that customers need more than the standard flow; it does not establish that incumbent spending falls. We see a more interesting startup opportunity where a tool can shorten repeated design iterations or improve the resulting chip enough to earn a separate budget. That is the part of the 3D transition we would investigate before assuming the largest EDA vendors capture most of the upside.
@kevin__mak

Kevin Mak on X

$ASTS So many questions about ASTS (please don't reply to unrelated threads to get my attention, just DM me). I have no position in the company. My comments from 3+ quarters ago is that I wanted to see "more metal in space". My concern from 5+ quarters ago was "how do they go from producing 1 satellite in 6 months, to 6 satellites per month, that's a really hard scaling problem". I think Starlink screwed up with their Swarm acquisition and trying to force that tech to work, it put a 18+ month delay on them. My hope was that ASTS would capitalize on that, and it generally appears that they've had scaling issues that prevented that from happening. That isn't really their fault, "space is hard" and "mass production is different from prototypes". I think money isn't a problem for them, they have so much cash (they were smart to take advantage of their high stock price). The problem is execution is hard even if you have lots of cash. Strategically they're in a good place, the MNO's definitely want/need them to work to compete w/ Starlink. But the MNO's are powerless, they're awful at execution (they're only good at increasing your monthly bill!). The BO failure was a really big problem. SpaceX (Starlink) had very little leverage on ASTS before. If they slowroll/deny F9 launches, they just push ASTS towards their competitor (BO). Two competitors (BO and ASTS) become stronger. But since BO was offline, it makes SpaceX the de facto monopolist to ASTS' launch. That gives them a ton of power in this situation and I imagine (but have no way to prove it), they would flex that competitive pressure on the company. That's not illegal anti-competitive behavior, that's just "pressure". It's a tricky set of problems that face the company and the stock price reflects that. I don't have a strong view in either direction of whether things get better or worse from here. But my initial hopes/thesis were steadily eroded by the execution issues (and valuation), hence my eventual exit from my long position. I don't think I'm saying anything thoughtful or what people don't already know/experience. But worth putting it out there because I've received _a lot_ of questions. Disclosure: No position in ASTS.

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