Two from The Deep View. First up, as an introduction to Pathway, August 11:
Pathway breakthrough challenges AI economics
One of the first "neolabs" to announce something tangible is showing off an AI breakthrough that would fundamentally change the architecture of today's AI, making it cheaper to operate and requiring far less data center power.
Pathway unveiled a 150-million parameter small reasoning model, BDH-CQ, on Tuesday, along with benchmarking results that back up Pathway's claims that its post-transformer architecture could deliver comparable performance at a fraction of the cost and computing resources of today's leading frontier models.
According to the ARC-AGI-1 benchmark, BDH-CQ achieved 29.5% pass@2 accuracy (it solved nearly a third of the problems on the test when given two guesses) with a computed inference cost of $0.0007 per task. So how does that compare with OpenAI's most cost-effective model? GPT 5.6 Luna (Low), which OpenAI just reduced in price by 80% on July 30, scored 34.5% on the same benchmark. However, even at its new cut-rate price, it cost 11 times more than Pathway's new model.
Part of that is because the Pathway model is small, doesn't need chain-of-thought to achieve reasoning, and needs less data because of its improved memory. So Luna has slightly better performance at an astronomically more expensive price. And Luna itself is a fraction of the price of the leading frontier models. So while it's very still early, what Pathway has achieved holds tremendous promise for future efficiency and cost reductions of frontier-class models....***...."We need to be able to squeeze more intelligence per dollar, and for this you need to change the paradigm," Zuzanna Stamirowska, CEO and co-founder of Pathway, told The Deep View. "This is a very deep innovation, and we wouldn't have done it if it wasn't going to be, and if it didn't have a chance to capture the market."
The Pathway team believes their breakthrough is "a PageRank moment for intelligence," referring to the turning point when Larry Page and Sergey Brin realized they could make web search dramatically better by ranking pages based on the structure of links between them and not just the keywords on the page....
....MUCH MORE
The Google reference is not just a metaphor, it looks like she poached some serious talent from the GOOG.
And the linked podcast which we used for the headline, August 9:
Why LLMs are reaching their limits and what's next
What comes after large language models?
In this episode of The Deep View Conversations, we talked with Zuzanna Stamirowska, CEO of Pathway, to explore why her team believes today’s dominant AI architecture has fundamental limits, and what it could take to move beyond them.
Pathway is developing Dragon Hatchling, a new architecture designed to give AI native memory, continual learning, and a different approach to reasoning. Stamirowska explains why today’s LLMs can appear to remember without actually internalizing what they learn, why reasoning through language creates its own constraints and costs, and how Pathway is trying to build models that can think in a more abstract way.
The conversation looks at how those architectural changes could affect hallucinations, interpretability, safety, and the enormous compute demands of modern AI. Stamirowska shares how her background in complex systems and game theory shaped Pathway’s approach, why the company made an early bet on challenging the transformer, and how the AI coding revolution has already radically changed the way her own team works....
....MORE, including the video
