#New Chip Vera Rubin Announcement

Nvidia launched a new chip: Vera Rubin. Here how it compares to its predecessor Blackwell:

• 10x lower inference costs
• 4x fewer GPU required for MoE training
• 5x more energy efficient
• 5x longer uptime
• 10x higher reliability
• 18x faster assembly and maintainance.

sources: https://x.com/nvidia/status/2008357978148130866

#Nvidia $20B Groq Acquisition

ℹ️ You guys may have noticed a trend in the recent AI acquisitions: they hire the founder + few leadership position and leave the rest of the team in a zombie company, this happened with Meta > Scale, Google > Windsurf, and now NVIDIA > Groq and Meta > Maus. So why is that? Well it turns out this solution avoids antitrust scrutiny.

Groq has entered into a non-exclusive licensing agreement with Nvidia for Groq's inference technology. Groq Cloud will continue to operate without interruption. This blog post breaks down the antitrust loophole that enabled NVIDIA to close this $20B deal: https://ossa-ma.github.io/blog/groq.

#What Nvidia Actually Bought (And What It Didn't)

Nvidia acquired:

• All of Groq's intellectual property and patents
• Non-exclusive licensing rights to Groq's inference technology
• Jonathan Ross (CEO), Sunny Madra (President), and the entire senior leadership team

Nvidia explicitly did NOT buy:

• GroqCloud, the cloud infrastructure business, which continue with its CFO Simon Edwards. This is because KSA (Kingdom of Saudi Arabia) uses this service, and Nvidia preferred to avoid extra scrutiny on offering inference to a foreign country.

#GPUs vs TPUs vs LPUs — Why are LPU are important to Nvidia?

Jonathan Ross built TPUs at Google, then started Groq to build LPUs. LPUs is a new architecture that optimize for inference and Jonathan is a strong leader in the industry.

#Global AI Compute capacity now totals over 15 million H100-equivalent