Ve Sharma’s Post

I just got back from Google Cloud Next 23, and I'm so inspired 👨🎓 by the possibilities of generative AI. 🤖 (See my top GCP product highlights below) I'm excited to see what developers, including myself, will build 🏗 next with this next-gen technology. Google is incredibly well-positioned to lead the future of AI. Their partnership with NVIDIA, one of the leading AI chipmakers, is a major coup. And their new Cloud products, such as Vertex AI and Cloud AutoML, ModelGarden, and more, are making it easier than ever for developers to build and deploy AI applications. I'm excited 🤩 to see what the future holds for AI, and I'm confident that Google will be at the forefront of this revolution. Here are some core GCP product highlights 🤔 I've had the opportunity to learn more about: 1. Vertex AI 🤖 is a managed machine learning (ML) platform on GCP that helps companies/startups to build, deploy, and scale ML models faster and easier than ever. It provides a unified experience for managing the entire ML lifecycle, from data preparation to model deployment. 😲 Vertex AI also offers a variety of pre-trained models and tools that can be used to quickly build and deploy ML applications. (shameless plug, I just got my GCP MLOps certification/badge and can attest that this is a fantastic product). 2. Model Garden 👩🌾 is a repository of pre-trained ML models that can be used by developers to build their own applications. It provides a variety of models (over 100+ models) 😲 for different use cases, including image classification, object detection, fraud detection, NLP, etc. Model Garden can help developers to save time and effort in the ML development process, and it can also help them to create more accurate and reliable models in a matter of clicks. 3. Cloud TPUs 🏃♂️ (underlying optional hardware for these products) are specialized hardware accelerators that are designed to speed up the training and inference of ML models. They can be used to train and deploy ML models on-premises or in the cloud. TPUS can help companies to deploy ML models in production more quickly and cost-effectively. On average, TPUs are almost ten times faster than GPUs. 4. PaLM 2 🌴 is a large language model (LLM) is Google's answer to ChatGPT. PaLM2 is better, faster, and smaller than the previous PaLM, but it also outshines gpt-4 in certain areas of reasoning. It has 540 billion parameters, which is more than any other AI model currently available. It is Multimodal - It can process information from multiple sources, such as text, code, and images. This allows it to learn more complex patterns and make more accurate predictions. There's more to PaLM2 but these core features make it a worthy LLM and not to be trifled with! I believe that Google's investments in AI will make them the leading player in the future of AI. I'm excited to see what they will build next, and what myself, and my startup, Aduris, will build with it! 🤩