Urgent.News

One page, thousands of outlets. See who else covered it.

Editions

AI

Groq raises $350M to fuel its pivot from AI chips to neocloud

Groq raised $350 million at a $3.5 billion valuation as the former AI chipmaker pivots to a neocloud business and expands its Nvidia-powered data center footprint.

Startup Groq has secured $350 million in new funding as it transitions from an AI chip manufacturer to a neocloud provider offering advanced GPUs and AI infrastructure services. The investment, spearheaded by Disruptive with potential involvement from Nvidia, has inflated Groq's valuation to an estimated $3.5 billion. This figure represents a decline from the $6.9 billion valuation the company held just months prior, following Nvidia's hiring of Groq's founder and CEO, Jonathan Ross, and other key personnel.

Groq's chairman and CEO of Disruptive, Alex Davis, announced that the funds will facilitate the company's expansion into the "world's leading AI inference cloud." Despite the reduced valuation, Groq maintains that this represents a new valuation for its post-Nvidia licensing deal version. The neocloud company now operates 13 data centers worldwide and caters to over 6 million developers, enterprises, and AI-native businesses.

Groq's pivot aims to support the growing demand for medium and larger-sized clusters of Nvidia-accelerated computing for both training and inference tasks. While the cloud-based neocloud sector is experiencing high demand, questions remain regarding its long-term profitability, as companies like Groq invest heavily in infrastructure.

Groq's financials are currently undisclosed, but the company's strategic shift positions it within Nvidia's AI infrastructure ecosystem, a relationship increasingly common among neocloud providers. TechCrunch has sought additional information from Groq.

Written by urgent.news from TechCrunch's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

Read the original at techcrunch.com →

More in AI

QUASAR: How Saliency-Weighted Reconstruction Closes the Loss Floor Gap in LLM Quantization-Aware Training

QUASAR: How Saliency-Weighted Reconstruction Closes the Loss Floor Gap in LLM Quantization-Aware Training Quantization is one of the most practical tools in the LLM deployment toolkit.

  • QUASAR addresses loss floor gap in 2-bit/3-bit quantization of LLMs
  • Saliency-weighted reconstruction prioritizes accurate parameter reconstruction
  • QUASAR achieves up to 29% reduction in KL divergence at 2-bit quantization

More from Monday 17 August →