AI21 Labs’ Post

𝐍𝐞𝐰 𝐁𝐥𝐨𝐠 𝐀𝐫𝐭𝐢𝐜𝐥𝐞! We are happy to announce our latest blog post: "ML model deployment: How to deliver a Machine Learning model to the customer". This article provides a clear and concise approach to deploying your machine learning models, making their predictions accessible to users through a REST API. 𝐊𝐞𝐲 𝐭𝐨𝐩𝐢𝐜𝐬 𝐜𝐨𝐯𝐞𝐫𝐞𝐝 𝐢𝐧𝐜𝐥𝐮𝐝𝐞: ◽ Containerization with Docker: Package your application and its dependencies into a container for easy deployment. ◽ Deployment on Google Cloud Platform's Cloud Run: Simplify the process of running your containers in the cloud. ◽ Autoscaling: Ensure your application can handle varying loads seamlessly. Whether you are new to model deployment or looking to refine your processes, this guide offers valuable insights and practical steps. 𝐑𝐞𝐚𝐝 𝐭𝐡𝐞 𝐟𝐮𝐥𝐥 𝐚𝐫𝐭𝐢𝐜𝐥𝐞 𝐡𝐞𝐫𝐞: https://rb.gy/repmil #machinelearning #modeldeployment #datascience #MLOps #docker #cloudrun #technology #innovation

When reading the manual doesn't help. It's NOT MY FAULT this took longer than it should have. I read the quick start, but not the actual pages. It should be enough. But now you, too, can save time getting blob counts from Azure with go :). https://lnkd.in/g4TzPitK

I highly recommend this one for anyone seeking to grasp the whole picture of the MLops cycle,it offers a comprehensive, in-depth exploration of both theory and practical applications on building and managing ML systems, covering everything from team formation and development process to advanced topics like scaling, cloud deplotment, ML-driven microservices and pipelining operations. https://lnkd.in/ghjBAbYh

#Google releases the #Jetstream engine for PyTorch as an Open Source project. https://lnkd.in/gRKJrnKp. This is a major milestone for training and inference of PyTorch based #ML models, particularly #LLM models like Llama2, on #GCP Cloud #TPU.

Integrating LangChain with Azure Container Apps dynamic sessions https://lnkd.in/dSwsDxyR

Mesop is still under development, and the documentation lacks in certain aspects. Deploying a Mesop application is not straightforward and requires containerization unless you are deploying it directly to Google Cloud

이번에 Google cloud 의 Gemini 가 업데이트 되면서 System instructions 이 preview 로 새로 들어왔습니다. GPT 랑 유사한 System prompts 같은 효과가 나올듯한데 참고하시기 바라겠습니다. System instructions enable users to steer the behavior of the model based on their specific needs and use cases. When you set a system instruction, you give the model additional context to understand the task, provide more customized responses, and adhere to specific guidelines over the full user interaction with the model. For developers, product-level behavior can be specified in system instructions, separate from prompts provided by end users.

A word on Taipy www.taipy.io Who wants a modern simple and reliable approach to creating charts and displaying data in multiple forms? Well, Taipy, an open-source Python application to . What is Taipy ? A. Taipy is *the* simple-to-use next-generation open-source Python application builder. Taipy turns data and AI algorithms into full web applications quickly and easily. B. So simple that you don't even have to be knowledgeable about web development! You don't need to have either front-end or back-end knowledge to use the app builder. C. Because Taipy is a production-ready web application.Taipy generates interactive interfaces including charts and all sorts of widely used controls. D. Taipy can be developed as Python scripts or used within Jupyter Notebooks. E. Taipy was developed so that you can use your favorite development tool! Taipy provides all the functionalities you need; whether you want to develop on IDEs or on notebooks... F. Taipy uses simple low code syntax to create interactive and customisable multipage dashboards with augmented markdown. G. Taipy allows you to create your whole application in a single language. H. Taipy reduces development and instalment times drastically. I. Taipy lets you create applications, such as dashboards and Machine Learning apps. Why Taipy? 1. Innovative Scenario Management- a unique functionality that allows data scientists, but also end-users, to do What If? analyses 2. Taipy studio, the graphical editor is an easy to use and simple way to configure your pipeline. 3. Taipy means data flow orchestration 4. Taipy means highly interactive interfaces 5. Taipy means highly interactive webpages without prior expertise 6. Taipy means powerful and customised data 7. Taipy means intuitive components to organise and manage data Very recently, Taipy launched Taipy Cloud. Taipy cloud is the platform that simplifies application deployment, ensuring it remains accessible and stable as demonstrated here: https://lnkd.in/eQc5JrWy

Are you tired of manually copying AI transcripts to .docx files and waiting to back them up in the cloud? Look no further! Our new custom solution only requires two inputs: your API keys for Google Drive and OpenAI. By utilizing this tool, users have saved nearly 3 whole working days per month on tasks like reporting issues, archiving chats, developing workflow plans, and more. Check out the solution here: https://lnkd.in/ehEd5hzS #timemanagment #devops #customsolutions #dowhatreallymatterswithyourtime

Explore how #LLMs can simplify & automate cloud operations using GPTScript on Civo Cloud - check out this tutorial for a step-by-step guide ➡️⬇️https://buff.ly/3vGNRsy