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Atlas Cloud Unveils Super-Efficient AI Decision-Making Platform, Leaving Deepseek in Its Wake

Significantly lowering GPU and server demands, Atlas Inference expedites and economizes the deployment of sophisticated AI, particularly large language models (LLMs), leading to faster, dollar-wise implementation in the realm of artificial intelligence.

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Larger language models can now be deployed faster and at lower costs due to reduced GPU and server...
Larger language models can now be deployed faster and at lower costs due to reduced GPU and server demands thanks to Atlas Inference.

Atlas Cloud Unveils Super-Efficient AI Decision-Making Platform, Leaving Deepseek in Its Wake

Smashing AI Costs and Throughput Limits! 🚀✨

Hint: Atlas Cloud's Inference Solution from NYC Takes the Tech World by Storm!

Yo, here's the scoop!

The one-stop-shop for AI magic, Atlas Cloud, dropped a bomb with their newest addition, Atlas Inference. This badass AI inference platform slashes GPU and server demands, making it simpler for peeps to deploy large language models (LLMs) quicker and cheaper than ever! 💸⚡

Built in cahoots with AI inference engine SGLang, this game-changer boosts GPU efficiency by handling more tokens faster and with less hardware. Take a gander at DeepSeek's published numbers - Atlas Inference's 12-node H100 cluster outwhelms DeepSeek's Very own DeepSeek-V3 model execution, all while using just two-thirds of the servers! 🤯💪

"We engineered Atlas Inference to bust the economics of AI deployment wide open," said Jerry Tang, Atlas' CEO. "By cranking out 54,500 input tokens and 22,500 output tokens per second per node, businesses can now profitably roll out high-volume LLM services, moving from break-even to profitability. I'm betting this will send shockwaves throughout the industry. In a nutshell, we're obliterating industry standards set by the big shots by delivering superior throughput with fewer resources." 🔥🕺

Breaking the major leagues, Atlas Inference thrashes bigwigs like Amazon, NVIDIA, and Microsoft, delivering up to 2.1 times greater throughput using just 12 nodes compared to competitors' larger configurations. Despite this, it clings onto lightning-fast latency, sitting pretty with sub-5-second first-token latency and a snappy 100-millisecond inter-token latency even with over 10,000 concurrent sessions. The cherry on top? Phenomenal performance is delivered by four clever innovations:

  • Dividing Prefill/Decode Operations: This separation of compute-intensive jobs from memory-bound processes optimizes efficiency.
  • DeepEP (Deep Expert) Parallelism & Load Balancers: It keeps GPU usage high, with over 90% utilization.
  • Two-Batch Overlap Technology: By cranking up throughput, it enables larger batches and supports both compute and communication phases simultaneously.
  • Memory Model for Disposable Tensors: This ensures stable operation during long sequences, eliminating potential crashes.

The platform's Core Developer at SGLang, Yineng Zhang, put it this way, "This is a giant leap forward for AI inference. The innovations we've made here could very well become the new normal in GPU utilization, and latency management. We're convinced that this will unlock capabilities previously thought unattainable by the majority of the industry regarding throughput and efficiency." 🌟🚀

Bottom line: Atlas Inference is brimming with cost efficiency and scalability for AI deployment. Rejoice, it supports standard hardware and custom models, giving customers complete control. Plus, you can sling in fine-tuned models, isolate 'em on dedicated GPUs, and enjoy a platform perfect for teams requiring brand-specific voices or specialized domain knowledge.

So, what are you waiting for? Get ready to rock that AI world! Enterprises and startups can dive in right now! 🌟💰🚀

About Papa Atlas Cloud

Papa Atlas is the friendly, all-rounder AI expert, powering top gun AI squads with bombproof, hassle-free infrastructure for training and deploying models. Atlas Cloud also dishes out instant access to up to 5,000 GPUs across a colossal SuperCloud fabric, ensuring 99% uptime and baked-in compliance. Dig it all at atlascloud.ai!

Connect with Atlas

Speak to Jason, the man behind the marketing magic, jason.dotson@atlascloud.ai or ring him at 214-878-3807.

The Insider Scoop:

Atlas Inference is making waves because of its impressive throughput and resource efficiency advantages over industry veterans like Amazon, NVIDIA, and Microsoft. Here's a quick rundown of how they stack up based on recent data and industry benchmarks:

Throughput and Resources

  • Throughput Mastery: Atlas Inference claims that a 12-node cluster smashes larger setups from major rivals, providing up to 2.1 times greater throughput.
  • Token Turbo: Atlas throws down numbers processing 54,500 input tokens and 22,500 output tokens per second per node. They also maintain short latencies despite handling over 10,000 concurrent sessions.

Resource Efficiency

  • Lower Hardware Demands: Atlas smokes DeepSeek's reference implementation with only two-thirds of the servers, suggesting superior resource utilization and lower infrastructure costs.
  • Cut Costs, Boost Profits: Atlas emphasizes their approach as game-changing, claiming to dramatically reduce infrastructure requirements and operational costs, tackling the fact that hardware can account for up to 80% of AI operational costs.

Matchup with Amazon, NVIDIA, and Microsoft

| Feature/Company | Atlas Inference | Amazon (AWS) | NVIDIA DGX Cloud | Microsoft (Azure) ||------------------------|------------------------------|-------------------------|--------------------------|------------------------------|| Throughput (Relative) | Up to 2.1x higher (per node) | Baseline | Baseline | Baseline || Hardware Utilization | Fewer nodes needed, high util. | Standard | Optimized via software | Standard || Latency | Sub-5s first-token, 100ms inter| Varies by setup | Low but not specified | Varies by setup || Cost Efficiency | Higher (less hardware, lower cost) | Standard | Optimized, but not to same degree | Optimized, but not to same degree || Ease of Integration | Not specified | High (via Bedrock) | High (DGX Cloud) | High (Azure AI) |

  • Amazon: AWS Bedrock and SageMaker offer top-notch LLM deployment, but Atlas alleges superior throughput and resource efficiency.
  • NVIDIA: DGX Cloud offers optimized performance and high-end GPU infrastructure, but Atlas contends their proprietary optimizations generate greater throughput and cost savings at scale.
  • Microsoft: Azure’s user-friendly tooling and model fine-tuning earn high marks for developer experience and easy onboarding, but Atlas asserts better throughput and hardware efficiency for LLM inference tasks.

The Skinny

Atlas Inference poses as a frontrunner in throughput and cost efficiency for LLM inference, outrunning Amazon, NVIDIA, and Microsoft in both departments. Atlas concentrates on eliminating servers and operational costs while retaining brief latencies and outstanding support for high concurrent sessions, making profitable high-volume LLM services a reality.

However, it's worth noting that independent third-party benchmarking is necessary to confirm these claims fully. Integration, developer experience, and data governance remain strong points for the big players. 📝⚖️

  1. The tech world is abuzz with excitement over Atlas Cloud's latest offering, Atlas Inference, a game-changing AI inference platform that slashes data center costs and performance barriers.
  2. Atlas Inference, in partnership with SGLang's AI inference engine, not only boasts superior throughput but also reduces GPU and server demands, making large language model (LLM) deployment faster and cheaper than ever.
  3. In a head-to-head comparison with industry giants like Amazon, NVIDIA, and Microsoft, Atlas Inference delivers up to 2.1 times greater throughput using just 12 nodes compared to larger configurations, all while maintaining lightning-fast latency.
  4. Atlas Inference'sCore Developer, Yineng Zhang, predicts that the innovations behind the platform will become the new standard for GPU utilization and latency management.
  5. Microsoft, Amazon, and NVIDIA dominate the tech industry with their cutting-edge technology, but Atlas Cloud challenges their dominance by focusing on cost efficiency and scalability in AI deployment.
  6. The AI whiz, Atlas Cloud, not only boasts instant access to up to 5,000 GPUs across a vast SuperCloud fabric but also delivers 99% uptime and built-in compliance, making it a go-to choice for startups and enterprises alike.
  7. In the realm of data-and-cloud-computing, businesses seeking to profit from high-volume LLM services will find Atlas Inference an ideal platform, as it moves them from break-even to profitability by offering unprecedented throughput with fewer resources.
  8. As the AI race heats up, Atlas Cloud stands out as a force to be reckoned with, redefining the norms of GPU utilization and latency management, and breaking through barriers previously thought unattainable for the majority of the industry.
  9. With its unmatched technology, flexible hardware compatibility, and cost efficiency, Atlas Cloud is poised to revolutionize AI deployment, making it accessible to businesses and startups of all sizes.

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