The move signals Meta's deeper push into artificial intelligence as it seeks greater control over its AI hardware. According to Reuters, the company has begun small-scale deployment of the chip ...

Artificial intelligence (AI) is set to impact every industry of the economy. Two leading AI chip companies have seen their share prices fall sharply this year. However, one stock's astronomical ...

Let's look a three AI chip companies set to benefit that are worth buying during the current Nasdaq correction. Nvidia's revenue growth exploded when AI started to become mainstream due to the ...

If successful, Meta plans to fully integrate the chip into its AI training platforms by 2026, potentially reshaping cost structures and altering the competitive landscape in favor of greater AI ...

While Nvidia will likely get its fair share of this AI chip spending, this represents a huge opportunity for Broadcom. Meanwhile, the company also now has four newer custom AI chip customers ...

Meta, the parent company of Facebook, Instagram, and WhatsApp has started testing its first-ever in-house chip designed for training artificial intelligence (AI) systems. The move marks a ...

Meta is testing its first AI training chip to cut Nvidia reliance and lower infrastructure costs tied to its AI push. Meta tapped TSMC to build its training chips, with plans to deploy them widely ...

Nvidia has signalled no drop in demand for its flagship chips among big artificial intelligence (AI) spenders despite the low-cost challenge posed by Chinese rival DeepSeek. The leading AI ...

OpenAI has announced plans to develop its own custom AI chip, reducing reliance on Nvidia. In a policy shift, OpenAI relaxed censorship rules, embracing ‘free expression’ under the new Trump ...

Many companies are already ramping up their developments for their in-house technology, and the next that reportedly joined this trend is Meta as it is now testing its self-made AI training chip.

One of the sources said Meta's new training chip is a dedicated accelerator, meaning it is designed to handle only AI-specific tasks. This can make it more power-efficient than the integrated ...