🌟 Good morning from Ai4 - Artificial Intelligence Conferences 2024 in Las Vegas! 🌟 We're thrilled to kick off the day at booth #526, where innovation meets enterprise! Our team is ready to demonstrate how TensorOpera AI empowers ownership and scalability for bringing genAI into production. Stop by and chat with us to learn more about our products and services. Whether you’re looking to scale your AI models and applications cost-effectively, or build and deploy them privately on your premises, we have something exciting for you! Let’s make AI4 2024 unforgettable together! 🦊 🚀 #AI42024 #EnterpriseAI #TensorOpera
TensorOpera AI
Software-Entwicklung
Palo Alto, California 2,189 followers
Your generative AI platform at scale
Über uns
TensorOpera® AI Platform (https://TensorOpera.ai) is your generative AI platform at scale to enable developers and enterprises to build and commercialize their own generative AI applications easily, scalably, and economically. It provides unique features in enterprise AI platforms, model deployment, model serving, AI agent APIs, launching training/Inference jobs on serverless/decentralized GPU cloud, experimental tracking for distributed training, security, and privacy. TensorOpera Homepage: https://tensoropera.com/ TensorOpera AI: https://tensoropera.ai/home TensorOpera AI Documentation: https://doc.tensoropera.ai/ TensorOpera AI Blog: https://blog.tensoropera.ai/
- Website
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https://tensoropera.ai/
External link for TensorOpera AI
- Industrie
- Software-Entwicklung
- Größe des Unternehmens
- 11-50 Mitarbeiter
- Hauptsitz
- Palo Alto, California
- Typ
- In Privatbesitz
- Gegründet
- 2022
Standorte
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Primäre
165 University Ave
Palo Alto, California 94301, US
Employees at TensorOpera AI
Aktualisierungen
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✨ TensorOpera AI is heading to Las Vegas for Ai4 - Artificial Intelligence Conferences 2024! Catch us at booth #526 as we showcase groundbreaking GenAI innovations tailored for enterprises and GenAI developer. 📅 When? August 12-14 📍 Where? Booth 526, at Ai4 in Las Vegas #AI42024
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🦊 TensorOpera's Fox-1 small language model (SLM) is independently benchmarked and ranked in top 3. It outperforms other outstanding open-source SLMs, including Gemma 2B by Google, StableLM by Stability AI, and Phi 1.5 by Microsoft. It is available on TensorOpera's Model Marketplace (https://lnkd.in/evjGg4Y2) for deployment on both cloud and the edge. We also provide high throughput API access for Llama3.1-405B API from AI at Meta at low price of $4.90 per million tokens, and many more! Get access to the API or deploy them privately here: https://lnkd.in/evjGg4Y2
🔥 Exciting to see TensorOpera AI's Fox-1 model being independently benchmarked and ranked in the top 3 small language models (SLMs) on the Open LLM leaderboard by HF! Fox-1 outperforms other outstanding open-source SLMs, including Gemma 2B by Google, StableLM 3B by Stability AI, and Phi 1.5 by Microsoft. Now, you can seamlessly use Fox-1 model to build genAI applications and deploy them on both cloud and edge devices (smartphones) via the TensorOpera AI Platform (https://lnkd.in/gNTZuHDw). #SmallLanguageModels #TensorOpera #OpenSource #onDeviceGenAI
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🚀 Llama3.1-405B is live on TensorOpera AI Platform! It’s the most powerful open-source model from Meta, now available on TensorOpera AI at a high throughput and the low price of just $4.90 per million tokens! Getting started to obtain Llama3.1-405B API on TensorOpera AI platform (https://lnkd.in/end_FWiD) is simple: 1) Click: Go to Model Hub > Choose Model > API 2) Copy: Copy the API code and integrate it into your environment 3) Test: Evaluate model performance in the Playground before full integration If you further need dedicated endpoints for production with advanced deployment, observability, and security features, contact Jan-Paul Schwarz at [email protected]. #TensorOpera #Llama3.1 #opensource
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🚀 Introducing Fox-1: TensorOpera’s Pioneering Open-Source SLM! We are thrilled to introduce TensorOpera Fox-1, our cutting-edge 1.6B parameter small language model (SLM) designed to advance scalability and ownership in the generative AI landscape. Fox-1 stands out by delivering top-tier performance, surpassing comparable SLMs developed by industry giants such as Apple, Google, and Alibaba. What’s unique about Fox-1? 🌟 Outstanding Performance (Small but Smart): Fox-1 was trained from scratch with a 3-stage data curriculum on 3 trillion tokens of text and code data in 8K sequence length. In various benchmarks, Fox-1 is on par or better than other SLMs in its class including Google’s Gemma-2B, Alibaba’s Qwen1.5-1.8B, and Apple’s OpenELM1.1B. 🌟 Advanced Architectural Design: With a decoder-only transformer structure, 16 attention heads, and grouped query attention, Fox-1 is notably deeper and more capable than its peers (78% deeper than Gemma 2B, 33% deeper than Qwen1.5 - 1.8B, and 15% deeper than OpenELM 1.1B). 🌟 Inference Efficiency (Fast): On the TensorOpera serving platform with BF16 precision deployment, Fox-1 processes over 200 tokens per second, outpacing Gemma-2B and matching the speed of Qwen1.5-1.8B. 🌟 Versatility Across Platforms: Fox-1's integration into TensorOpera’s platforms enables AI developers to build their models and applications on the cloud via TensorOpera AI Platform, and then deploy, monitor, and fine-tune them on smartphones and AI-enabled PCs via TensorOpera FedML platform. This offers cost efficiency, privacy, and personalized experiences within a unified platform. Why SLMs? 1️⃣ SLMs provide powerful capabilities with minimal computational and data needs. This “frugality” is particularly advantageous for enterprises and developers seeking to build and deploy their own models across diverse infrastructures without the need for extensive resources. 2️⃣ SLMs are also engineered to operate with significantly reduced latency and require far less computational power compared to LLMs. This allows them to process and analyze data more quickly, dramatically enhancing both the speed and cost-efficiency of inferencing, as well as responsiveness in generative AI applications. 3️⃣ SLMs are particularly well-suited for integration into composite AI architectures such as Mixture of Experts (MoE) and model federation systems. These configurations utilize multiple SLMs in tandem to construct a more powerful model that can tackle more complex tasks like multilingual processing and predictive analytics from several data sources. How to get started? We are releasing Fox-1 under the Apache 2.0 license. You can access the model from the TensorOpera AI Platform and Hugging Face. More details in our blogpost: https://lnkd.in/dJcWs7N4 https://lnkd.in/d349fnHj
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🔥 How to Create Your Scalable and Dedicated Qualcomm-TensorOpera AI Endpoint? Last week: A Demo of Qualcomm-TensorOpera Dedicated Endpoint in Action This week: How to Create Your Own Endpoints? Deployment Steps on TensorOpera AI Platform (https://lnkd.in/end_FWiD): 1. Go to Deploy > Endpoints > Create Endpoint 2. Select model (e.g., SDXL, Llama3-8B), version, and name your endpoint 3. Select deployment method: dedicated on TensorOpera cloud or your on-premise servers 4. Set the needed number of GPUs per replica (we recommend 1x AI 100 for Llama3 and 2x AI 100 for SDXL replica) 5. Set the number of replicas to meet your average traffic demand 6. Set the autoscale limit to meet your peak traffic variations Customized Auto-Scaling: 1. Customize auto-scaling conditions and speed that scales replicas based on your traffic 2. Balance automatically high SLA & cost efficiency Result: 1. Your own dedicated endpoint running on Qualcomm AI 100 2. Advanced features: Playground, API Access, System Monitoring, Prediction Logs, User Statistics from TensorOpera AI Get early access on https://lnkd.in/eJKVMB9D #TensorOpera #QualcommCloud #GenAIPlatform #ScalableAPIs
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🔥 Qualcomm-TensorOpera APIs: Live in Action! Last week, we announced our partnership with Qualcomm to provide Qualcomm Cloud AI inference solutions for LLMs and Generative AI on TensorOpera AI Platform (https://lnkd.in/eJWJaPbZ). Developers can now claim their own Qualcomm-TensorOpera APIs to be able to: 1. Host dedicated endpoints for Llama3, SDXL, and other models on Qualcomm Cloud AI100 2. Autoscale end-points dynamically according to the real-time traffic 3. Access advanced observability and monitoring metrics for endpoints (# of replicas, latency, throughput, GPU/CPU utilization, etc) 4. Access prediction logs, user feedback, and usage statistics to continuously improve Get started with your own Qualcomm-TensorOpera APIs for $0.4/GPU/hour on dedicated Qualcomm Cloud AI100, or use serverless (usage-based) at $0.05/million tokens (for Llama3-8B) and $0.00005/step (for SDXL). Request access here: https://lnkd.in/eJKVMB9D #TensorOpera #QualcommCloud #GenAIPlatform #ScalableAPIs
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🔥 Qualcomm-TensorOpera APIs: Live in Action! Last week, we announced our partnership with Qualcomm to provide Qualcomm Cloud AI inference solutions for LLMs and Generative AI on TensorOpera AI Platform (https://lnkd.in/eJWJaPbZ). Developers can now claim their own Qualcomm-TensorOpera APIs to be able to: 1. Host dedicated endpoints for Llama3, SDXL, and other models on Qualcomm Cloud AI100 2. Autoscale end-points dynamically according to the real-time traffic 3. Access advanced observability and monitoring metrics for endpoints (# of replicas, latency, throughput, GPU/CPU utilization, etc) 4. Access prediction logs, user feedback, and usage statistics to continuously improve Get started with your own Qualcomm-TensorOpera APIs for $0.4/GPU/hour on dedicated Qualcomm Cloud AI100, or use serverless (usage-based) at $0.05/million tokens (for Llama3-8B) and $0.00005/step (for SDXL). Request access here: https://lnkd.in/eJKVMB9D #TensorOpera #QualcommCloud #GenAIPlatform #ScalableAPIs
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🚀 We are thrilled to announce our collaborations with Qualcomm Technologies to provide the world’s most cost-effective AI inference solutions for LLMs and Generative AI on TensorOpera AI Platform! Through this partnership, AI developers will have the opportunity to access Cloud AI 100 instances on TensorOpera AI Platform for using popular generative AI models, including Llama3 and SDXL. They can choose from various usage models, including API access, on-demand (pay-as-you-go), or dedicated deployments, while leveraging many capabilities like autoscale, comprehensive endpoint monitoring, optimized job scheduling, and AI Agent creation. According to Rashid Attar, Vice President, Cloud Computing, Qualcomm Technologies, Inc, “With the explosion of new generative AI models, developers around the world are hungry for easy, effective access to high-performance AI inference for deployment. By combining TensorOpera’s AI Platform with Qualcomm Technologies’ Cloud AI 100, developers now have immediate access to deploy the most popular GenAI/Large Language Models - Llama3, Mistral, SDXL - at the push of a button. We are excited to collaborate with TensorOpera AI to deliver a high-performance inference platform that offers exceptional value and convenience to developers.” “This collaboration is also aligned with our shared long-term vision of integrated edge-cloud collaborative AI platforms, which we believe will drive widespread adoption of generative AI,” says Salman Avestimehr, co-founder and CEO of TensorOpera. “In line with this vision, TensorOpera will soon launch its new foundation model optimized for smartphones and edge devices. Integrated into the TensorOpera AI Platform, this model enables the development of powerful AI agents directly on mobile devices—a field where Qualcomm has significantly invested by delivering high-performance, efficient compute chips for smartphones.” We invite AI developers and enterprises to explore the services offered by TensorOpera and Qualcomm Technologies. Get started today by visiting https://lnkd.in/eXEcN_Sh to apply for early access to Qualcomm-TensorOpera dedicated or serverless model endpoints. Read the full press release here: https://lnkd.in/eNwzE_CK
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