Ziaul Kamal’s Post

New strides in making AI accessible for every enterprise Google Cloud’s Vertex AI is rolling out multiple updates to make AI accessible for every enterprise including lower costs and more languages. Read mode on following blog post!

New strides in making AI accessible for every enterprise Google Cloud’s Vertex AI is rolling out multiple updates to make AI accessible for every enterprise including lower costs and more languages. Read mode on following blog post!

New strides in making AI accessible for every enterprise Google Cloud’s Vertex AI is rolling out multiple updates to make AI accessible for every enterprise including lower costs and more languages. Read mode on following blog post!

Aren’t RAG & Grounding are formidable arsenal, until they aren’t ! Making Gen AI deployable in production and how to carry out grounding with Gemini Sudio and Vertex AI !

Google is a Leader in The Forrester Wave™: AI Foundation Models For Language, Q2 2024 receiving the highest scores of all vendors evaluated in the Current Offering and Strategy categories. “Gemini is uniquely differentiated in the market especially in multimodality and context length while also ensuring interconnectivity with the broader ecosystem of complementary cloud services.” In this report, you will learn: 🟧 Why Google is named a Leader in AI Foundation Models for Language. 🟩 Where the AI Foundation Models for Language market stands today, and where it is going. 🟦 How Google Cloud’s capabilities compare with other vendors in the market. https://lnkd.in/e9WwM_ZG #ai #LLM #googleAI #googlepartner Cloudbench Arhasi, AI with Integrity Tom R. Chiru B Sam Ibrahim Lee Anne Forbes

What is trust in the context of #AI language solutions? Why is it important? Amazon Web Services (AWS) , Cisco and Lionbridge will explore the topic and arm you with strategies for an AI trust framework. Join our webinar: https://brnw.ch/21wGtD7 #GenerativeAI #Trust

Evaluating the output of large language models (LLMs) is crucial for ensuring desired results and selecting the most suitable model for your specific use case. With Google Cloud's Vertex AI Gen AI Evaluation Service, you have the power to evaluate any model using our diverse collection of meticulously curated and transparent evaluators. Choose between an interactive mode for real-time evaluation or an asynchronous mode for more extensive analysis. Check out the below blog to understand how it works: https://lnkd.in/gXD_aYuW #LLMevaluation #GenerativeAI #NaturalLanguageProcessing #GoogleCloud #VertexAI

Today, we are excited to announce that Google is a Leader in The 2024 Forrester Wave™: AI Foundation Models for Language, Q2 2024, receiving the highest scores of all vendors evaluated in the Current Offering and Strategy categories. “Gemini is uniquely differentiated in the market especially in multimodality and context length while also ensuring interconnectivity with the broader ecosystem of complementary cloud services.” - The Forrester Wave™: AI Foundation Models for Language, Q2 2024 Download the complimentary copy of The Forrester Wave™: AI Foundation Models for Language, Q2 2024. https://lnkd.in/e4Q29JRW #googlecloud #gcp #ai #llm #foundationmodels #machinelearning

Yes. You heard it right. In 11 more days customers will be able to significantly scale their AI on the improved Gemini 1.5 Flash with ~ 85% reduced input costs and output costs by up to ~80%. More details on Warren Barkley's blog below. Check it out! #google #genai #googlecloud

Scale your AI, not your costs: We've improved Gemini 1.5 Flash to reduce the input costs by up to ~85% and output costs by up to ~80%, starting August 12th, 2024. This, coupled with capabilities like context caching can significantly reduce the cost and latency of your long context queries. Using Batch API instead of standard requests can further optimize costs for latency intensive tasks. With these advantages combined, you can handle massive workloads and take advantage of our 1 million token context window.