Claim◆Article

Despite predictions of consolidation, more companies are training strong models and an increasing number of organizations are releasing these models openly.

The writer contrasts earlier predictions of lab consolidation with the current reality where more companies are investing hundreds of millions to billions and releasing open models. ✦ AI generated

The author of 'Latest open artifacts (#23)...' · Interconnects · 2026-08-02 · original ↗

Share card ↓Export .md Export .txt

We’re at a place where more companies are training strong models — easily investing hundreds of millions to billions of dollars in the total effort still — and an increasing number of organizations are releasing these models openly.

Read full article ↗excerpt · fair-use quotation

Around this claim

Mechanism · 1

Building token machines is a likely path to value, so labs that were expected to consolidate are instead finding value in continued operation.The author of 'Latest open artifacts (#23)...' · Interconnects · conf 80%

Evidence · 1

The open model ecosystem has professionalized significantly — model weights now ship with vLLM patches and partner integrations, unlike a year ago when the community had to figure everything out from scratch.Florian Brand · Interconnects · conf 75%

In practice · 1

Thinking Machines has become a leading open-weight model company in the USA, with its open model finetuning service generating hundreds of millions in revenue per year.The author of 'Latest open artifacts (#23)...' · Interconnects · conf 90%

Context · 1

Nobody actually knows the ceiling of capabilities for current models because the model release cycle (every 2-3 months) is faster than the time needed to fully explore what a model can do with long-running inference (weeks to months).Noam Brown · No Priors · conf 70%

Counterpoint · 1

The trading evolution across four eras - from pre-electronic trading floors (pre-1990s), to the first wave of electronification (1990s), to automated trading (late 1990s-2015), to quantitative trading with ML (2015-present) - has weeded the market, so that today only a handful of truly large firms remain because serious prop shops must invest hundreds of millions in research clusters.Alex Itkin · The Pragmatic Engineer · conf 70%

This moment responds to

supports → A safer bet than consolidation is predicting continued adoption of open models, and the ecosystem is entering a decisive era over how far open models can go.The author of 'Latest open artifacts (#23)...' · Interconnects supports → A multi-model future is inevitable because using multiple models together produces more creative ideas than any single model, and companies are always incentivized to experiment with the ecosystem's new models to improve productivity and reduce costs.Alex Atallah · 20VC