Morning tech briefing: chips, agents, and hardening alerts

AI chip company SambaNova Systems has raised $1 billion at an $11 billion valuation led by General Atlantic, in a first close of its Series F round, with more investors expected to join soon.

“In the next few weeks, a few more investors will be coming in, and the second close is likely to finish up,” Rodrigo Liang, CEO and co-founder of SambaNova, told TechCrunch.

The latest round comes roughly five months after the Palo Alto, California-based startup company unveiled its SN50 chip , alongside a $350 million Series E in February . SambaNova had also been in acquisition talks with Intel, a deal valuing it at roughly $1.6 billion, according to a December report from Bloomberg News .

Asked whether closing its Series E and F rounds meant SambaNova, founded in 2017, had settled on staying independent, Liang was noncommittal. He said the company keeps fielding interest. “We’re always being approached.” The door is open to such an exit in this dynamic AI market, the CEO said, but momentum and growth will most likely drive the company toward “being public at some point.”

SambaNova’s ties to Intel , a backer since its Series C and a participant in this latest round, have deepened. Five months ago, the nine-year-old startup announced a multi-year partnership with Intel to support AI inference development based on Intel’s Xeon chip. The two now co-develop products and take them to market together.

The days of Nvidia’s unparalleled market dominance aren’t over, but challengers and choices are arising from all directions.

ZML , a hot French AI startup endorsed by Turing Award winner Yann LeCun, has released inference -performance software that allows a variety of open-source large language models to run on a variety of chips — including Nvidia’s, AMD’s, Google’s TPU, Apple Metal and Intel Arc.

With ZML/LLMD , the newly launched LLM inference server, the company’s ambition is to break existing silos and make different chips available for AI use cases at their maximum available speed, and sometimes faster, ZML founder Steeve Morin told TechCrunch.

As AI becomes integrated into our work and everyday lives, optimizing inference — aka, the processing of prompts — has been outpacing model training in importance, but often feels patchy behind the scenes, with software and architecture barriers that lead to vendor lock-in, Morin said.

The promise of achieving peak performance across a variety of chips is a technological feat, but it could also be a market disruptor, amid mounting fears over AI-related costs.