Nvidia example sentences

"Nvidia" Example Sentences

1. Nvidia launched a new generation of graphics processing units this year.
2. Nvidia's graphics cards are very popular with PC gamers and digital content creators.
3. Nvidia continues to dominate the discrete GPU market with its GeForce product line.
4. Nvidia recently acquired Arm to expand its reach into processors for artificial intelligence and machine learning applications.
5. The latest Nvidia GeForce RTX 30 series graphics cards are equipped with ray tracing and AI capabilities.
6. Nvidia's GPUs have become essential components for training AI models using deep learning techniques.
7. Nvidia has helped build many of the supercomputers used for advanced scientific research and data analysis.
8. Nvidia graphics processors power some of the fastest self-driving car and medical imaging systems in development.
9. Nvidia has leveraged its GPU expertise to enter new markets like AI chips for data centers and autonomous vehicles.
10. Nvidia faced some short-term challenges related to the global GPU supply shortage and cryptocurrency mining demand.
11. Nvidia has a strong position in AI chips, GPUs, and other processors used for machine learning and data analytics.
12. Nvidia stock outperformed the market in recent years due to demand for its GPUs and AI chips.
13. Nvidia founder Jensen Huang has helped lead the company's expansion into new growth markets like autonomous driving and data centers.
14. Nvidia reported record revenue in recent quarters driven by strong sales of its GeForce RTX gaming GPUs and data center products.
15. Intel recently launched its own GPUs to compete with Nvidia's products in AI and high-performance computing applications.
16. Analysts believe Nvidia still has opportunities for further growth from rising demand for AI and accelerated computing.
17. Nvidia processors power AI systems used for robotics, natural language understanding, and disease diagnosis.
18. Nvidia's breakthroughs in GPU computing helped create the markets for AI chips and accelerated data analytics solutions.
19. Nvidia has revolutionized data science through the use of GPUs for accelerating machine learning and AI workloads.
20. In addition to GPUs, Nvidia designs AI chips and systems-on-a-chip used for autonomous vehicles and robotics.
21. Nvidia invented CUDA, a parallel computing platform and programming model that accelerated GPU computing.
22. Nvidia has dominated the cryptocurrency mining market over the last few years with its powerful GPUs.
23. Nvidia's DRIVE chip offers autonomous driving capabilities like AI perception, sensor fusion, and surround vision.
24. Experts say Nvidia still has opportunities to expand its businesses in autonomous driving, AI chips, and robotics.
25. Tesla uses Nvidia's AI and GPU processing technology in its self-driving car and infotainment systems.
26. Nvidia recently launched its DGX AI supercomputer to accelerate enterprise AI adoption and research.
27. Nvidia's acquisitions of companies like Mellanox and Icera have helped expand its product portfolio.
28. Nvidia's focus on accelerated computing and deeply parallel processors led to its dominance in GPU computing.
29. Nvidia recently launched TensorRT, a tool for optimizing machine learning models to run efficiently on its GPUs.
30. Many companies like BMW, Audi and Ford integrate Nvidia's DRIVE AI platform into their self-driving car programs.
31. Nvidia is enabling advances in scientific research through its GPU-accelerated supercomputers.
32. Critics say Nvidia's dominance in GPU computing could face challenges from competitors like AMD and Intel.
33. Facebook, Google and Baidu use Nvidia's GPUs and AI chips for building their AI infrastructure.
34. Nvidia announced new products at this year's GTC conference focused on AI, robotics and data science.
35. Experts praise Nvidia for leading the development of accelerated GPU computing and AI.
36. Nvidia started as a graphics company but saw early on the benefits of GPUs for parallel processing workloads.
37. Nvidia's expanded focus on emerging technologies like AI and autonomous driving could help sustain its growth.
38. Nvidia invested heavily in research & development which helped it become a leader in GPU computing.
39. Nvidia sees opportunities for its technology in new fields beyond gaming like robotics, self-driving cars and AI healthcare assistants.
40. Some experts argue that Nvidia has first-mover advantage in GPU computing and AI chips that may be difficult for others to overcome.
41. Analysts are optimistic about Nvidia's growth prospects in the expanding markets for GPU computing, AI chips and self-driving vehicles.
42. Nvidia has established several AI research partnerships with academic institutions and national laboratories.
43. NVIDIA GPUs power AI infrastructure systems used by companies for tasks like image recognition, fraud detection and data mining.
44. Nvidia is focused on accelerated computing through its GPUs, DPUs and other processors that boost performance for neural networks.
45. A recent cybersecurity incident impacted NVIDIA's internal IT systems but did not involve its core products or IP.
46. Nvidia faces competitive threats from AMD, Intel and other chipmakers moving into GPUs, AI chips and self-driving technologies.
47. Nvidia's push into new growth areas has succeeded due to the adaptability of its GPU architecture for accelerated computing.
48. Nvidia envisions a future where GPU computing powers applications across industries through AI and accelerated data analytics.
49. Nvidia plans to continue investing heavily in research and talent to stay ahead of the fast-moving AI and deep learning industries.
50. Nvidia's recent results show that demand remains strong for its GPUs used for gaming, data centers and cryptocurrency mining.
51. Experts say Nvidia's technology leadership and first-mover advantage have helped it become a leader in GPU computing.
52. Some analysts see Nvidia as a bellwether for the opportunities emerging at the intersection of AI, data science and accelerated computing.
53. Nvidia expects data center demand to be driven by AI, accelerated computing and the growth of cloud services.
54. Nvidia is focused on enabling scientific breakthroughs through data center products that accelerate AI, deep learning and high-performance computing.
55. Nvidia GPUs power supercomputers used for research in the life sciences, material science and climate science.
56. Nvidia has established several AI Startup Programs to help early-stage AI companies leverage its technologies.
57. Analysts are keeping a close eye on Nvidia's expansion into new markets to gauge how well it can sustain its high growth rates.
58. Nvidia plans to introduce new AI chips designed specifically for inference applications in data centers and edge devices.
59. Engineers praise Nvidia for helping advance the state of the art in GPUs, AI chips and deep learning technologies.
60. With more companies looking to adopt AI, Nvidia is well positioned to benefit from the growing demand for AI chips and accelerated computing.

Common Phases

1. Nvidia is a well-known manufacturer of graphics cards and GPUs.
2. I bought an Nvidia GeForce GTX 970 graphics card for my gaming PC.
3. Nvidia recently released their RTX 2000 series of graphics cards with ray tracing capabilities.
4. The new Nvidia RTX 3080 graphics card has amazing performance for the price.
5. Nvidia's latest GPUs use the Turing GPU architecture.
6. Nvidia AI has helped advance the field of artificial intelligence through deep learning.
7. The Nvidia Shield TV is a popular streaming media player.
8. Nvidia GPUs power many AI startups and research labs.
9. Nvidia's self-driving car software is used by automakers around the world.
10. Nvidia Deep Learning Accelerator cards are used for AI training in data centers.
11. Nvidia has transformed how AI and deep learning work through their GPUs.
12. The Nvidia Drive platform helps automakers develop self-driving car systems.
13. Nvidia stock has done very well over the last few years.
14. Nvidia has disrupted the AI and autonomous vehicle industries with their technology.
15. Nvidia G-Sync monitors work well with Nvidia graphics cards.
16. I want to build a machine learning workstation with an Nvidia RTX GPU.
17. Nvidia CUDA and cuDNN help accelerate AI development.
18. Nvidia launched their Jetson AI computing platform for edge devices.
19. The Nvidia data center business has seen rapid growth in recent years.
20. Nvidia's technology has helped fuel the rise of AI and machine learning.
21. Nvidia founders Jensen Huang and Chris Malachowsky started the company in 1993.
22. Nvidia has many technologies to accelerate AI, like TensorRT and cuDNN.
23. Nvidia GPUs excel at matrix math operations needed for deep learning.
24. The Nvidia architecture is optimized for parallel computing.
25. Nvidia tegra chips power many tablets, phones, and cars.
26. The Nvidia Volta GPU architecture consists of 5 billion transistors.
27. Nvidia GPUs are ubiquitous in the AI and deep learning community.
28. Nvidia set up an AI research lab to advance AI and deep learning.
29. Nvidia has revolutionized the gaming industry with their graphics technology.
30. I hope Nvidia continues pushing artificial intelligence forward.
31. Jensen Huang has been the CEO of Nvidia since 1993.
32. The first Nvidia graphics card was called the NV1.
33. Nvidia technology enables millions of developers working on AI.
34. Nvidia aims to be a major player in the AI revolution.
35. Nvidia is focused on building end-to-end platforms for AI and autonomous vehicles.
36. Nvidia dominates the market for AI training accelerators.
37. Nvidia has been incredibly innovative over the last two decades.
38. Nvidia tech powers everything from supercomputers to smartphones.
39. Nvidia has produced some of the fastest GPUs ever made.
40. Nvidia's advantage lies in their specialized GPU architecture.
41. Nvidia has revolutionized AI through deep learning.
42. Nvidia's efforts have helped advance robotics and self-driving cars.
43. Nvidia acquired Icera, a cellular baseband chip company, in 2011.
44. Nvidia aims to create the brain of AI through their AI computing platforms.
45. Nvidia's future ambitions include powering Level 5 full self-driving cars.
46. I hope Nvidia continues breakthrough innovations in the field of AI.
47. Nvidia research focuses on deep learning, robotics, and autonomous vehicles.
48. Nvidia GeForce graphics cards changed the PC gaming industry forever.
49. Jensen Huang has grown Nvidia into one of the biggest tech companies in the world.
50. Nvidia's work has the potential to transform many industries.
51. Nvidia is working on AI chips for training and inference.
52. Nvidia took the graphics industry by storm when they launched their first GPUs.
53. Nvidia CUDA cores allow massive parallel processing needed for deep neural networks.
54. Nvidia technology underpins so much research in AI and machine learning today.
55. Nvidia technology has helped advance AI at a much faster pace.
56. The innovative Nvidia team continues pushing the boundaries of what's possible with AI and autonomous technology.
57. Nvidia's strategies have led to dominance in the graphics card market.
58. Nvidia is looking to capture more of the fast-growing AI chip market.
59. The Nvidia team continues crafting breakthrough GPUs that change the world.
60. The future of AI depends heavily on innovation from companies like Nvidia.