- 19
- 18 183
TensorOps
Cyprus
Приєднався 14 сер 2007
We simply help machines learn!
At TensorOps we provide machine learning and AI services.
At TensorOps we provide machine learning and AI services.
LLM Proxy & LLM Gateway Fundamentals
In this video, we explore LLM Proxy-powerful network components designed to route AI traffic and optimize workflows for enterprise applications.
Key Takeaways:
1:25 How LLM Gateways enable smart routing for different tasks
1:55 Methods to improve monitoring and logging for compliance and audits
2:50 Techniques to increase uptime with fallback strategies across AI vendors
Plus, we introduce LLMstudio, an open-source tool that simplifies the deployment of these gateways, offering scalability and customization to suit your needs.
Key Takeaways:
1:25 How LLM Gateways enable smart routing for different tasks
1:55 Methods to improve monitoring and logging for compliance and audits
2:50 Techniques to increase uptime with fallback strategies across AI vendors
Plus, we introduce LLMstudio, an open-source tool that simplifies the deployment of these gateways, offering scalability and customization to suit your needs.
Переглядів: 98
Відео
What can make the Nvidia stock rise or fall?
Переглядів 112День тому
Explore NVIDIA's soaring stock prices, driven by its unrivaled GPU technology in data centers and the surging demand from AI developments. This video delves into NVIDIA's critical role in powering AI revolutions and the speculative pursuit of Artificial General Intelligence (AGI), assessing the sustainability of such growth amidst the booming AI industry and potential market risks Read more her...
Lessons Learned From Managing AI Innovation Projects
Переглядів 112День тому
In this session, Senior Engineering Managers will share the pains and successes of over 18 months into the GenAI revolution. From setting goals, communicating expectations, and choosing the right innovation activities, such as hackathons or PoCs, this session is targeted at business leaders, senior managers, and AI stakeholders like product 00:00 - intro 05:00 - Generative AI Integration and Bu...
Google Cloud and TensorOps Partnership
Переглядів 1028 днів тому
Are you struggling to bring your AI initiatives to life? - Facing challenges like falling short of product requirements - Dealing with excessive AI expenses - wrestling with complex MLOps maintenance At TensorOps, we've partnered with Google Cloud Platform to overcome these challenges and deliver top-tier AI solutions with unmatched speed and efficiency. AI engineers leverage Google Cloud's pow...
![Engineering Techniques to Reduce Cost of LLMs in Production [webinar]](http://i.ytimg.com/vi/iYzL5xb6X6I/mqdefault.jpg)
Engineering Techniques to Reduce Cost of LLMs in Production [webinar]
Переглядів 1,3 тис.2 місяці тому
Understand Your Costs: Discover why many companies struggle with scattered billing and multiple vendor payments and Learn actionable strategies to optimize these expenses without compromising performance Key topics include: 00:00 Intro 01:30 How to Measure & the Importance of Cost Reduction for LLMs 10:40 Optimizing Language Models for Cost Efficiency 12:30 Going for the Smaller Model 14:40 Pro...
Beyond PoC: Enterprise Chatbot Architectures
Переглядів 3925 місяців тому
This one-hour webinar showcasing architectures for enterprise-grade chatbots, moving beyond the proof of concept stage. learn how to build, scale, and improve your LLM applications using Azure Microsoft AI ecosystem. Key topics include: • 00:00 Intro • 07:37 What does a chatbot need? • 11:03 ChatGPT vs GPT • 13:00 Simple GPT Chat Application on Azure • 21:23 End to End Chat Application • 30:53 ...
![A Survey of Advanced Prompt Engineering Techniques [webinar]](http://i.ytimg.com/vi/fQV5AXsNLu0/mqdefault.jpg)
A Survey of Advanced Prompt Engineering Techniques [webinar]
Переглядів 7 тис.7 місяців тому
This one-hour webinar exploring the Secrets of Prompt Engineering , we'll discuss how prompt engineering resembles programming and what common design patterns they share Support the Open-source project! ⭐ us on GitHub: github.com/TensorOpsAI/LLMStudio Key topics include: • 0:00 Intro • 2:11 The GenAI Revolution • 4:00 What are prompts • 5:53 Survey of techniques (part I) • 18:33 Demo: Exploring...
TensorOps AI Driven Talent Management
Переглядів 1638 місяців тому
Dive into the future of HR with TensorOps AI-Driven Talent Management! 🤖💼 Our latest video showcases how TensorOps is revolutionizing talent management by extracting and analyzing data from multiple sources. Key Features: 🔍 Automated Data Extraction 📊 Intelligent Analytics 🚀 Predictive Talent Acquisition Explore real-world applications and see how your organization can benefit from AI in HR. Pe...
Analyzing the Costs of Large Language Models in Production
Переглядів 4,6 тис.9 місяців тому
💲 Struggling with managing costs of LLMs in production? Find out about our workshop here: www.tensorops.ai/llm-studio-cost-optimization-workshop This one-hour webinar offers a deep dive into the costs aspects of leveraging Large Language Models (LLMs) in production environments. Key topics include: • Breaking Down the Costs Involved in Developing LLM Applications • How to Select the Optimal Siz...
LLMstudio - Local LLMs IDE
Переглядів 18910 місяців тому
How to set up a local environment for LLMs with two lines of code? # pip3 install LLMstudio # LLMstudio server
Launching Deep Learning VMs on Google Cloud
Переглядів 3912 роки тому
Launching Deep Learning VMs on Google Cloud
can u show more detail how to LLM router work for classifire query for choose model to generate answer
This is a really nice report by lmsys on how to build and train such a system lmsys.org/blog/2024-07-01-routellm/
@@tensorops oh, okie thank you, very nice blog
Very informative !
Could you please share the slide url here because it has been overlayed in the video
This is a wild hour long talk 😂
looking forward to contributing to the project
Thank you, we welcome you to join our community on Discord: discord.gg/23Fj5YWj
awesome presentation!!
fantastic
Thank you so much 😀
I write prompts all day long and 10 minutes in and I have already learned some new techniques 👍
Thank you! which ones? out of curiosity
I really enjoyed this webinar. Thank you for putting it out there. We're still so early in the adoption curve. I wouldnt be surprised if this helps noobs for years to come.
Thanks 🙏 we're glad to be a part of your journey to become an AI expert
Can you explain the math of 5 requests per minute translating it to 9,000$ per month?
We recommend looking here gptforwork.com/tools/openai-chatgpt-api-pricing-calculator Assuming 220K requests, with proper prompts that are usually 1000-2000 tokens you can get to these costs. Additionally we want to remind that often a single request to an LLM application triggers more than one API call to an LLM
@@tensorops Thank you so much.
@@tensorops Can you please elaborate on that? "A single request to an LLM application triggers more than one API call to an LLM"
@@balainblue We give an example on the next webinar where you have one query that triggers many LLM calls. Sometimes even simple chains like Map-Reduce or Refine can cause many LLM calls to OpenAI for a simple action as "summarization"
@@tensorops Thank you. I look forward to it.
My voice tone is great x) I sound like a chibi version of myself ahah
😂😂
😂
amazing man you are great i pray your channel will grow and reach millions of subscribers🥰😍
Thank you 💛
Really great insights. Economics is well explained.
Thank you!
Being handed a bill based on tokens generated by a model is preposterous... These LLM apps cost so much right now that you need to have a solid use case in mind.... Else you just wait for a couple more years when inferencing these LLMs wont be as expensive... the only reason these LLMs are so expensive to run is that they are SOTA and Nvidia is the only player right now.
the economics are broken because the hardware setup just isnt there... instead of paying by the hour you pay by the token/call which is insane..... Cloud has been build on the idea that you fire up the instance and you know what you pay.... but these days you need huge cloud instances to run these huge models... The costs will go down significantly to run these models in about 3 years.... you wont have to think about these things...
Where can we download the slides?
😊
Short sweet informative! Thanks both