Anthropic reportedly plans to launch within weeks a hybrid artificial intelligence (AI) model that includes reasoning capabilities.
The model aims to give developers more control over the cost of using an AI model by enabling them to control the amount of computational resources it spends on a problem, Seeking Alpha reported Thursday (Feb. 13), citing a paywalled article by The Information.
Anthropic’s upcoming hybrid AI model uses more computational resources to answer hard questions and acts like a traditional large language model (LLM) to handle simple questions, according to the report.
This cost-effective approach is meant to appeal to the enterprise market that the company aims to serve, the report said.
Anthropic did not immediately reply to PYMNTS’ request for comment.
This report came about a week after OpenAI released what it called its “most cost-efficient” reasoning AI model, the o3-mini.
The o3-mini is part of OpenAI’s o1 series, which can reason through tasks but takes longer to respond than non-reasoning models. However, unlike the other models in that series, the o3-mini is “small” but “powerful and fast,” OpenAI said. The model outperforms earlier models especially in science, coding and math, and comes in three reasoning levels: low, medium and high.
It was reported Jan. 22 that Google was investing more than $1 billion in Anthropic, upping its stake after already giving the AI firm around $2 billion, and that Anthropic was also on the verge of landing another $2 billion from a group of venture capital investors.
Together, these deals were expected to bring Anthropic’s valuation to around $60 billion.
On Feb. 6, Anthropic and ridesharing company Lyft said they are working together to create AI products to serve Lyft’s riders and drivers.
The first phase of the collaboration is already underway, with Lyft’s customer care AI assistant being powered by Anthropic’s AI model, Claude, via Amazon Bedrock.
The collaboration will also include other AI applications designed to enhance the rideshare experience for both riders and drivers, Lyft’s participation in early testing for new products and capabilities, and Anthropic’s training of Lyft’s engineering teams to accelerate their ability to build AI-powered features.
