Weekly Pre-IPO Stock Secondary Market Update | September 29, 2026

Higgsfield's climb to a $1 billion annualized revenue run rate roughly 18 months after launch ranks among the fastest ramps in private market history, and the August Series B at a $5.4 billion valuation now looks measured against that figure. The product sits on top of third-party models from ByteDance, OpenAI, and Anthropic, which invites the "AI wrapper" critique: if OpenAI launched a video platform tomorrow, would Higgsfield survive? We believe it can, because the complexity of the interface and the pace of product innovation are hard to replicate, and because revenue is shifting from individual creators toward business customers. B2B moats look structurally stronger than B2C ones. Forward deployed engineers and embedded workflows mean a rival must be better by multiples, not percentages, before a customer rips a vendor out, while consumers can cancel a subscription and switch in a day. Higgsfield is roughly split between the two today, so its upmarket move is the key to building durable lock-in. The longer-term vision of on-demand, personalized Hollywood-quality film, with a family member cast as the lead, shows how large the creative market could become.

Inference platforms, the companies that host and run open-source models such as those from ByteDance, Moonshot AI, DeepSeek, and Nvidia, are repricing at speed. Fireworks AI is reportedly heading toward $30 billion, Baseten toward $26 billion, Fal toward the high teens, and Modal near $15.75 billion. Against that backdrop, Together AI's July Series C at $8.3 billion, on more than $1.15 billion in annual bookings, stands out as relative value in the group, even though it owns its GPUs and runs a different business model. The strategic logic is a hedge. Roughly 7% of US debt, including hidden obligations, is reportedly tied to OpenAI and Anthropic, so the frontier labs must succeed, yet the scale of open-source disruption remains unknown. Inference platforms benefit either way: if the labs keep accelerating they need more compute and book more contracts, and if growth slows the compute is still consumed by open models. Our house view is that 90% of compute will be inference rather than training, and that 90% of inference will run on open models. Closed labs can still grow revenue 50% to 75% a year while ceding share, since a smaller slice of a much bigger pie is acceptable to investors. The cloud computing analogy applies: few businesses want to run servers themselves, and most will pay for an API. We see a 3x return over five years as the higher probability outcome from current prices, with several names capable of reaching $100 billion or more.

Island's $400 million raise in September at a $6.4 billion valuation shows that cybersecurity is increasingly an AI infrastructure story. The company has doubled ARR every year since its 2022 launch and consolidates security, identity, data protection, and application access in a single enterprise browser, which positions it to govern AI agents. Demand backdrop is strong: Palo Alto Networks, arguably the largest cybersecurity platform, is up 112% year to date, and agents online now reportedly outnumber humans. The media narrative around AI hacking points directly to better security as the answer, yet investors have been slow to connect those dots. Exit planning matters, because many cyber vendors are strong in a niche with a limited TAM (total addressable market) and are ultimately acquired, as Wiz was by Google for roughly $32 billion. The question for Island is whether Palo Alto buys it or builds the capability itself. We like the space on a risk-adjusted basis, but stock selection will drive returns.

AMD's roughly $8.2 billion all-stock acquisition of Fei-Fei Li's World Labs, which builds simulated 3D worlds used to train robots, signals that chipmakers intend to move closer to the model layer as physical AI comes into view. The deal may position AMD as the preferred chipmaker for robotics, tuning silicon to run world models efficiently. Decart, a similar business, reportedly drew a bidding war from SpaceX, Anthropic, Nvidia, and Google, so demand for the category is clear. Both companies chose a buyout over building independent frontier labs, suggesting world models are not yet seen as the next trillion dollar standalone opportunity. The broader trend is full-stack specialization, with chips, models, and software tuned for a specific outcome such as a robot, which can lower power use and shrink model size without sacrificing quality. We expect robots in homes within a couple of years, and note that investors may find AI infrastructure suppliers to robotics a more attractive entry point than the humanoid makers themselves.