No bad stock

NVIDIA Corporation
CEO : Mr. Jen-Hsun Huang

Quarterly earnings growth(YoY,%)

Period	Revenue	Operating Income	EPS	Release Date
2023 Q4	-20.8% YoY	-57.7%	-52.5%	2023-02-22

Colette Kress says,

Q4 Revenue and Yearly Comparison

• Q4 revenue was $6.05 billion, up 2% sequentially, while down 21% year-on-year
• Full year revenue was $27 billion, flat from the prior year

Data Center Revenue and Hyperscale Customers

• Data center revenue was $3.62 billion, down 6% sequentially, and up 11% year-on-year
• Fiscal year revenue was $15 billion and up 41%
• Hyperscale customer revenue posted strong sequential growth, though short of expectations as some cloud service providers paused at the end of the year to recalibrate their build plans
• Revenue growth from CSP customers last year significantly outpaced that of Data Center as a whole as more enterprise customers moved to a cloud-first approach

New Flagship H100 Data Center GPU

• H100 revenue was already much higher than that of A100, which declined sequentially
• The H100 is as much as 9x faster than the A100 for training and up 30x faster than transformer-based large language models
• The transformer engine of H100 arrived just in time to serve the development and scale-out of inference of large language models

AI Adoption and ChatGPT

• Open AI’s ChatGPT has captured interest worldwide, allowing people to experience AI firsthand and showing what’s possible with generative AI
• Generative large language models with over 100 billion parameters are the most advanced neural networks in today’s world
• NVIDIA’s expertise spans across the AI supercomputers, algorithms, data processing and training methods that can bring these capabilities to enterprise
• Generative AI applications will help almost every industry do more faster

Infiniband and HPC Optimized Ethernet Platforms

• Infiniband led our growth as our Quantum 2 40 gigabit per second platform is off to a great start
• In Ethernet, our 40 gigabit per second Spectrum 4 networking platform is gaining momentum as customers transition to higher speeds, next-generation adapters, and switches
• Delivering unmatched performance, latency, and in-network computing capabilities, InfiniBand is the clear choice for power-efficient cloud scale, generative AI

NVIDIA AI Enterprise Software

• Released version 3.0 of NVIDIA AI enterprise with support for more than 50 NVIDIA AI frameworks and pretrained model and new workflows for contact center intelligent virtual assistance, audio transcription, and cybersecurity
• Upcoming offerings include our NeMo and BioNeMo large language model services, which are currently in early access with customers

Jensen Huang says,

Partnership with Cloud Service Providers for NVIDIA AI Cloud Services

• NVIDIA is partnering with major cloud service providers to offer NVIDIA AI cloud services directly to enterprise customers.
• The AI cloud services will be hosted within the world’s largest clouds and will provide easy access to the world’s most advanced AI platform while remaining close to the storage, networking, security, and cloud services offered by the world’s most advanced clouds.
• Customers can engage NVIDIA AI cloud services at the AI supercomputer, acceleration library software, or pretrained AI model layers.

NVIDIA DGX Cloud

• NVIDIA DGX Cloud is the fastest and easiest way to have your own DGX AI supercomputer, accessible via a web browser.
• It is already available through Oracle Cloud Infrastructure and Microsoft Azure, with more cloud service providers expected to follow.

NVIDIA AI Enterprise

• Customers can access NVIDIA AI Enterprise for training and deploying large language models or other AI workloads.

Pretrained Generative AI Model Layer

• NVIDIA will be offering NeMo and BioNeMo, customizable AI models, to enterprise customers who want to build proprietary generative AI models and services for their businesses.

Expanding NVIDIA’s Full Scale of AI Computing Across Private and Public Clouds

• With the new business model, customers can engage NVIDIA’s full scale of AI computing across their private to any public cloud.

Q & A sessions,

Gaming Revenue

• Gaming revenue of $1.83 billion was up 16% sequentially and down 46% from a year ago.
• Year-on-year decline reflects the impact of channel inventory correction, which is largely behind us.
• RTX 40 Series GPUs are bringing enthusiast-class GPU performance to laptops and powering over (ph) gaming and creator laptops, setting up for a great back-to-school season.
• More than 400 games and applications support NVIDIA’s RTX technology for real-time ray tracing and AI-powered graphics.
• GeForce NOW cloud gaming service continued to expand and now has more than 25 million members in over 100 countries.

Pro Visualization Revenue

• Revenue of $226 million was up 13% sequentially and down 65% from a year ago.
• Interest in NVIDIA’s Omniverse continues to build with almost 300,000 downloads so far, 185 connectors to third-party design applications.

Automotive Revenue

• Revenue was a record $294 million, up 17% from Q3 and up 135% from a year ago.
• NVIDIA announced a strategic partnership with Foxconn to develop automated and autonomous vehicle platforms.
• The NVIDIA Drive operating system received safety certification from TÜV SÜD, one of the most experienced and rigorous assessment bodies in the automotive industry.

Q1 Fiscal ’24 Outlook

• Expect sequential growth to be driven by each of our 4 major market platforms led by strong growth in data center and gaming.
• Revenue is expected to be $6.5 billion, plus or minus 2%.
• GAAP and non-GAAP gross margins are expected to be 64.1% and 66.5%, respectively, plus or minus 50 basis points.
• GAAP operating expenses are expected to be approximately $2.53 billion. Non-GAAP operating expenses are expected to be approximately $1.78 billion.
• Capital expenditures are expected to be approximately $350 million to $400 million for the first quarter and in the range of $1.1 billion to $1.3 billion for the full fiscal year 2024.

NVIDIA AI Enterprise

• NVIDIA AI is essentially the operating system of AI systems today.
• By using NVIDIA AI, the entire machine learning operations is more efficient, and it is more cost-effective.
• Announcement made to put NVIDIA’s infrastructure and have it be hosted from within the world’s leading cloud service providers accelerates the enterprise’s ability to utilize NVIDIA AI enterprise.