DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
[2025/12] DeepSpeed Core API updates: PyTorch-style backward and low-precision master states [2025/10] SuperOffload: Unleashing the Power of Large-Scale LLM Training on Superchips [2025/10] Study of ZenFlow and ZeRO offload performance with DeepSpeed CPU core binding [2025/08] ZenFlow: Stall-Free Offloading Engine for LLM Training [2025/06] Arctic Long Sequence Training (ALST) with DeepSpeed: Scalable And Efficient Training For Multi-Million Token Sequences DeepSpeed has been used to train many different large-scale models. Below is a list of several examples that we are aware of (if you’d like to include your model please submit a PR): DeepSpeed has been integrated with several different popular open-source DL frameworks such as: DeepSpeed is an integral part of Microsoft’s AI at Scale initiative to enable next-generation AI capabilities at scale. DeepSpeed welcomes your contributions! Please see our contributing guide for more details on formatting, testing, etc. This project welcomes contributions and suggestions. Most contributions require you to agree to a Developer Certificate of Origin (DCO)[https://wiki.linuxfoundation.org/dco] stating that they agree to the terms published at https://developercertificate.org for that particular contribution. DCOs are per-commit, so each commit needs to be signed off. These can be signed in the commit by adding the -s flag. DCO enforcement can also be signed off in the PR itself by clicking on the DCO enforcement check. Xinyu Lian, Sam Ade Jacobs, Lev Kurilenko, Masahiro Tanaka, Stas Bekman, Olatunji Ruwase, Minjia Zhang. (2024) Universal Checkpointing: Efficient and Flexible Checkpointing for Large Scale Distributed Training arXiv:2406.18820
Recall.ai
Recall.ai provides an API to get recordings, transcripts and metadata from video conferencing platforms like Zoom, Google Meet Microsoft Teams, and mo
Record video conferences through a bot joining the call. Best when explicit recording consent is needed, or for building AI agents. Record video conferences and in-person meetings through a desktop app, without a bot in the call. Best for a stealthier recording experience. “Legal tech is high stakes. Working with Recall.ai, we had scalable Zoom meeting support ready in under two months, rather than six." “Recall.ai allows us to build meeting recording features without worrying about infrastructure. It has helped us move faster than we could have with an in-house build." "We’re building an AI Scribe for our doctors, and Recall.ai was the first piece of infrastructure I pushed to bring in. I’d seen how seamlessly it handled meeting data at my last company, which made choosing it again an easy call." "Recall.ai's Meeting Bot API saved us from months of pain. One integration, extremely reliable, and we launched our meeting bot feature in days." “Once we started using Recall.ai's Desktop Recording SDK to power Mem’s meeting recording experience, the painful edge cases that we had to chase on the support side went to zero." “Recall.ai allows us to operate reliable, enterprise-scale meeting transcriptions without worrying about infrastructure or security."
DeepSpeed
Recall.ai
DeepSpeed
Recall.ai
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Recall.ai
DeepSpeed
Recall.ai
