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Google's #gemini 1.5 is here! Just two months after launching #gemini 1.0, Google continues to show its speed of innovation by adding value to various areas and edge use cases using Generative AI. With the ability to process 1M tokens, including multimodality in seconds, this technology is truly groundbreaking. This means we can now process 1 hour of video, 11 hours of audio, codebases with over 30,000 lines of code, or over 700,000 words in just seconds! Check out the link below to learn more about this next-generation model. https://lnkd.in/em2S2Z3r

"An AI model’s 'context window' is made up of tokens, which are the building blocks used for processing information. Tokens can be entire parts or subsections of words, images, videos, audio or code. The bigger a model’s context window, the more information it can take in and process in a given prompt — making its output more consistent, relevant and useful. Through a series of machine learning innovations, we’ve increased 1.5 Pro’s context window capacity far beyond the original 32,000 tokens for Gemini 1.0. We can now run up to 1 million tokens in production. This means 1.5 Pro can process vast amounts of information in one go — including 1 hour of video, 11 hours of audio, codebases with over 30,000 lines of code or over 700,000 words. In our research, we’ve also successfully tested up to 10 million tokens." https://lnkd.in/dmTqUvWS

Hey everyone! Exciting news in AI this week! 🤖 Google has just released the preview of their groundbreaking Gemini 1.5 model, and it's making waves! 🚀 Key Features that caught my attention: 1. MULTIMODALITY: Process text, image, audio, and video (sans audio) seamlessly. 2. ENHANCED REASONING: Better reasoning capabilities setting new benchmarks. 3. EXTENDED CONTEXT UNDERSTANDING: With a context limit of 1 million tokens, it's pushing the boundaries. 4. NIAH EVALUATION: Achieving a remarkable 99% accuracy in finding embedded text within long blocks of data. 5. MoE ARCHITECTURE: Similar to GPT-4, used in Mixtral, it's backed by proven success. 6. MASSIVE INFORMATION PROCESSING: Handles 1 hour of video, 11 hours of audio, and much more. Tested successfully up to 10 million tokens! Again: It comes with a context limit of 1 million tokens! Just imagine the impact of a context window this large! If the token cost and processing time align, this could reshape our approach to many AI solutions, such as: * RAG Solutions: Sending entire documents as context, discarding vector databases, and enhancing performance. * Code Test Automation: Processing entire codebases in one go, revolutionizing automation, unit tests, and documentation generation. The possibilities are vast, and the impact on current solutions is tremendous! Let's keep an eye on this, while the future of AI is being reshaped. 🌐✨ You can read Google's announcement in the link bellow and sign up for the waitlist: https://lnkd.in/eu-3bCtq #AIInnovation #Gemini1.5 #AI #LLM

Gemini 1.5 Pro has been announced a week after we released Gemini 1.0 Ultra. The new model is a breakthrough in long-context understanding. What does that mean? As the blogpost explains...... "An AI model’s “context window” is made up of tokens, which are the building blocks used for processing information. Tokens can be entire parts or subsections of words, images, videos, audio or code. The bigger a model’s context window, the more information it can take in and process in a given prompt — making its output more consistent, relevant and useful. Through a series of machine learning innovations, we’ve increased 1.5 Pro’s context window capacity far beyond the original 32,000 tokens for Gemini 1.0. We can now run up to 1 million tokens in production. This means 1.5 Pro can process vast amounts of information in one go — including 1 hour of video, 11 hours of audio, codebases with over 30,000 lines of code or over 700,000 words. In our research, we’ve also successfully tested up to 10 million tokens." https://lnkd.in/gHUVn457

Generative AI is writing a major new chapter in the story of IT. If applications and digital services become dependent on complex AI engines, it will become even harder than it already is to observe, monitor, debug, and predict the behavior of the software that powers modern workloads. Here's why, and what AI could mean for observability and modern applications, from IT Pro Today. https://bit.ly/47PgiTw

#custom #chatgpt #ai #business #gpt Mastering Custom GPTs: A Business Optimization Guide https://lnkd.in/ehnKifku

Amazing!! Google's leap in AI innovation with Gemini 1.5! It sets new benchmarks in efficiency and long-context understanding, promising to revolutionize how we interact with technology. Excited for the endless possibilities this brings to developers and enterprises! - Gemini 1.5 Pro comes with a standard 128,000 token context window up to 1 million tokens - Gemini1.5 Pro can process vast amounts of information in one go — including 1 hour of video, 11 hours of audio, codebases with over 30,000 lines of code or over 700,000 words. - Gemini 1.5 Pro can perform more relevant problem-solving tasks across longer blocks of code. When given a prompt with more than 100,000 lines of code, it can better reason across examples, suggest helpful modifications and give explanations about how different parts of the code works. #AI #Innovation #GoogleGemini"

Create AI agents with Semantic Kernel #SharpCoding #SemanticKernet #AI

Generative AI is awesome. It's even better if you can do it yourself. If your company has the means to build an AI service for internal use, it will pay off in the long run. Keep your data in-house and train open source models to learn your business and ONLY your business. Red Hat's OpenShift AI and other technologies give you a great platform to do this, but you don't have to use our stuff. Go grab GPT4All and LangChain and start building on your local laptop. Play around, figure out some ways to work with models. The open-source LLM world is getting VERY good, very quickly.

Meet Gemini 1.5, Google's next-generation AI model | All you need to know https://lnkd.in/gh2EemWM #meet #Gemini #google #Next #generations #AI #model #need #technology #technologynews #artificialintelligence #technologysolutions #BreakingNews