Muhamad Ikhtiaruddin Md Hussin’s Post

Just finished the course “Google Gemini for Developers” by Lynn Langit! Check it out: https://lnkd.in/e4HKXPkZ #generativeai #googlegemini.

Just finished the course “Google Gemini for Developers” by Lynn Langit! Check it out: https://lnkd.in/eTjmMXmp #generativeai #googlegemini.

Just finished the course “Google Gemini for Developers” by Lynn Langit! Check it out: https://lnkd.in/ggfD55te #generativeai #googlegemini.

Just finished the course “Google Gemini for Developers” by Lynn Langit! Check it out: https://lnkd.in/eUXJXeiY #generativeai #googlegemini.

Just finished the course “Getting Started with the Google Gemini API” by Fikayo Adepoju! Check it out: https://lnkd.in/gV-8f9K6 #apidevelopment #generativeai #gemini #googlegemini.

Just finished Prompt Engineering with Gemini! The course provides excellent information on Gemini searching, Gemini extensions, including Google Drive elements in results upon request, multimodal searching, working with json formatted files, and providing insight on chain of thought reasoning and prompting. It is a great course highlighting the value of LLM integrated with the Google suite of products. I highly recommend this to anyone interested in learning more about artificial intelligence prompting using Gemini. https://lnkd.in/eA2A9cSc #gemini #promptengineering

Just finished the course “Building Skills with Semantic Kernel” by John Maeda! Check it out: https://lnkd.in/gGfBDHKk #generativeai #softwaredevelopment #artificialintelligence #largelanguagemodels.

War Begins!! - AI War Begins!. I guess many of you witnessed recent developments on Google I/O and Open AI GPT -4o.   Here are some snippets from Google I/O KeyNote Conference https://lnkd.in/dEZQyY9H AI Overviews: This is a revolutionary change for Google Search. It utilizes a custom-built Gemini AI model to generate summaries directly on the search result page. These summaries, called AI Overviews, aim to answer your questions in a comprehensive way, saving you time from jumping through multiple links. Enhanced Google Photos Search with AI: While details are scarce, it seems Google is leveraging AI to improve searching within Google Photos. This could involve features like recognizing objects, scenes, or even facial expressions in your photos, making them easier to find based on specific criteria. Google Workspace Labs: This is likely a platform for exploring experimental features within Google Workspace applications like Gmail, Docs, and Calendar. It allows Google to test new functionalities and gather user feedback before a wider rollout. NotebookLM: There isn't a lot of public information about NotebookLM yet. However, based on the name, it could be a tool that integrates AI capabilities into digital notebooks. Imagine being able to ask your notebook questions about your notes, summarize them automatically, or even generate different creative text formats based on your note content. Generative Media: Imagen 3: Dubbed Google's most sophisticated text-to-image model yet, Imagen 3 boasts superior quality and photorealism. Veo: This is Google's latest video generation model. It can create high-definition videos (1080p) in various cinematic styles based on text descriptions. Trillium: Computing Power 6th Generation CPU. Improving Compute Performance.

Excited to share my latest project: Generative AI Voice Bot This voice-based chatbot integrates Speech to Text (STT), a Large Language Model (LLM), and Text to Speech (TTS) to enable seamless conversations with users. It uses Gradio UI for user interface. ✨ Key Features: Speech to Text (STT): Converts spoken input into text using Whisper-Tiny English. Large Language Model (LLM): Delivers context-aware responses powered by TinyLlama-1.1B-Chat-v1.0. Text to Speech (TTS): Transforms text back into speech using Parler-TTS-Mini-v1. 💡 Hosted in: Google Colab, making it easy to run and experiment with. Next steps: GPU is obviously a bottleneck besides it is a very naïve implementation to get started so need to optimise the pipeline. Build a React frontend and deploy LLM backend with VLLM. Implement threading and queues for real-time streaming. Add Docker support for easy deployment. Inspiration drawn from: https://lnkd.in/dPQZKGt6 Check it out and feel free to collaborate or provide feedback! https://lnkd.in/dH3GJVmw