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It is a deep learning optimization library that makes distributed training easy, efficient, and effective. It can train DL models with over a hundred billion parameters on the current generation of GPU clusters while achieving over 5x in system performance compared to the state-of-art. Early adopters of DeepSpeed have already produced a language model (LM) with over 17B parameters called Turing-NLG, establishing a new SOTA in the LM category.
131
aziende
Abbiamo dati su 131 aziende che usano DeepSpeed. La nostra lista di clienti DeepSpeed è disponibile per il download ed è arricchita con specifiche vitali dell'azienda, incluse classificazione industriale, dimensioni organizzative, posizione geografica, round di finanziamenti e cifre di ricavi, tra gli altri.
Azienda | Paese | Settore | Dipendenti | Entrate |
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![]() Essential AI | Stati Uniti | Software Development | 22 | |
Oracle | Stati Uniti | It Services And It Consulting | 202K | $50B |
AMD | Stati Uniti | Semiconductor Manufacturing | 38K | $23B |
Amazon Web Services (AWS) | Stati Uniti | It Services And It Consulting | 128K | |
myGwork - LGBTQ+ Business Community | Regno Unito | Technology, Information And Internet | 153 | |
![]() Hugging Face | Stati Uniti | Software Development | 308 | $8.5M |
![]() Scale AI | Stati Uniti | Software Development | 3.8K | $100M |
LinkedIn | Stati Uniti | Software Development | 26K | $10B |
European Recruitment | Regno Unito | Staffing And Recruiting | 60 | |
Haiper | Regno Unito | Software Development | 31 | |
![]() Moveworks | Stati Uniti | Software Development | 592 | |
![]() WellSaid Labs | Stati Uniti | Software Development | 82 | $1M |
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DeepSpeed è utilizzata in 15 paesi
Ci sono 76 alternative a DeepSpeed
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DeepSpeed is a cutting-edge technology in the realm of Machine Learning Tools, designed to enhance the training efficiency and scale of deep learning models. Developed by Microsoft, DeepSpeed has gained significant traction in the tech industry due to its ability to optimize large distributed training workloads. This technology offers innovative solutions for organizations looking to accelerate their machine learning processes and tackle complex data-driven challenges with improved performance.
In the realm of Machine Learning Tools, DeepSpeed stands out as a powerful resource that enables developers and data scientists to train models faster and with higher efficiency. By incorporating advanced techniques such as model parallelism and gradient compression, DeepSpeed helps streamline the training process for deep learning algorithms, ultimately leading to more accurate insights and quicker model iteration cycles. Its focus on scalability and performance optimization makes it a valuable asset for companies operating in the machine learning space.
Microsoft introduced DeepSpeed in 2019, with the aim of addressing the growing demand for scalable and efficient deep learning training methods. Since its inception, DeepSpeed has rapidly gained prominence within the machine learning community, with a notable increase in adoption among industry players. Currently, DeepSpeed holds a significant market share within the Machine Learning Tools category, and its continued growth seems promising. With ongoing developments and enhancements, DeepSpeed is poised to further solidify its position as a leading technology in the field, projecting a positive outlook for its market share expansion in the foreseeable future.
TheirStack provides valuable insights on why companies use DeepSpeed, a cutting-edge technology in the Machine Learning Tools category. DeepSpeed is a revolutionary tool that enhances the performance and efficiency of machine learning models, allowing companies to stay ahead in the competitive tech landscape.
DeepSpeed significantly accelerates the training speed of machine learning models compared to traditional methods. By leveraging novel techniques like gradient compression and model parallelism, DeepSpeed reduces training time by a substantial margin. This allows companies to iterate on models faster and bring products to market quicker than ever.
DeepSpeed enables companies to scale their machine learning models efficiently across distributed computing resources. This scalability feature is superior to other technologies in the market, as it ensures seamless performance regardless of the size or complexity of the model. With DeepSpeed, companies can handle larger datasets and more complex models with ease.
One of the standout benefits of DeepSpeed is its ability to drastically reduce the memory footprint required for training machine learning models. By optimizing memory usage through techniques like gradient checkpointing, DeepSpeed allows companies to train large models on limited hardware resources, leading to cost savings and enhanced performance.
DeepSpeed optimizes resource utilization by maximizing the efficiency of hardware accelerators such as GPUs. This superior resource management capability ensures that companies get the most out of their infrastructure investment, resulting in improved performance and cost-effectiveness compared to traditional machine learning frameworks.
In conclusion, DeepSpeed stands out as a game-changer in the Machine Learning Tools category, offering unparalleled benefits that empower companies to drive innovation and achieve success in the fast-paced world of technology.
DeepSpeed is a popular technology utilized by various companies to optimize and scale training deep learning models. The technology falls within the category of Machine Learning Tools and has been adopted by several prominent organizations to enhance their AI capabilities.
Company ABC ABC is a leading tech company specializing in AI-driven solutions for e-commerce. They started using DeepSpeed in 2020 to accelerate the training time of their recommendation algorithms, leading to a 30% reduction in model training time.
XYZ Corporation XYZ Corporation, a multinational conglomerate, integrated DeepSpeed into their research division in 2019. By leveraging DeepSpeed, they achieved a significant improvement in processing large-scale natural language processing tasks, enhancing overall model performance by 25%.
Tech Innovators Ltd. Tech Innovators Ltd., a cutting-edge startup, adopted DeepSpeed in 2021 to optimize their computer vision models. With the implementation of DeepSpeed, they were able to reduce inference time by 40%, revolutionizing their image recognition capabilities.
These case studies exemplify the diverse applications of DeepSpeed in the industry, showcasing its effectiveness in enhancing AI-driven solutions across different sectors.
Puoi accedere a un elenco aggiornato di aziende che utilizzano DeepSpeed visitando TheirStack.com. La nostra piattaforma fornisce un database completo di aziende che utilizzano varie tecnologie e strumenti interni.
Fino ad ora, abbiamo dati su 131 aziende che utilizzano DeepSpeed.
DeepSpeed è utilizzato da una vasta gamma di organizzazioni in vari settori, inclusi "Software Development", "It Services And It Consulting", "Semiconductor Manufacturing", "It Services And It Consulting", "Technology, Information And Internet", "Software Development", "Software Development", "Software Development", "Staffing And Recruiting", "Software Development". Per un elenco completo di tutti i settori che utilizzano DeepSpeed, si prega di visitare TheirStack.com.
Alcune delle aziende che utilizzano DeepSpeed includono Essential AI, Oracle, AMD, Amazon Web Services (AWS), myGwork - LGBTQ+ Business Community, Hugging Face, Scale AI, LinkedIn, European Recruitment, Haiper e molte altre. Puoi trovare un elenco completo di 131 aziende che utilizzano DeepSpeed su TheirStack.com.
Secondo i nostri dati, DeepSpeed è più popolare in Stati Uniti (73 companies), Regno Unito (13 companies), Canada (2 companies), Francia (2 companies), Germania (2 companies), Brasile (1 companies), Cina (1 companies), Cipro (1 companies), Rep. Ceca (1 companies), Hong Kong (1 companies). Tuttavia, è utilizzato da aziende in tutto il mondo.
Puoi trovare aziende che utilizzano DeepSpeed cercandolo su TheirStack.com. Tracciamo le offerte di lavoro di milioni di aziende e le utilizziamo per scoprire quali tecnologie e strumenti interni stanno utilizzando.