Marco Zuliani’s Post

Apple’s Technical Paper on AI Advances Apple’s recent technical paper introduces their new foundation language models, designed to power the Apple Intelligence features across iOS, iPadOS, and macOS. These models include a 3-billion parameter model optimized for on-device use and a larger server-based model for more intensive tasks. Key highlights include: * Model Architecture: The models are designed to be efficient, accurate, and responsible, with a focus on user privacy and on-device processing. * Training Process: The models are trained using diverse datasets to ensure broad applicability and robustness. * Responsible AI: Apple emphasizes reducing bias, protecting privacy, and preventing misuse throughout the development process. * User Experience: These models enhance everyday tasks such as text writing, notification summarization, and in-app actions, making interactions more seamless and intuitive. 5 Daily Tools for Technology Professionals Leveraging Apple’s AI Advances i. Enhanced Siri: With improved language understanding and personal context awareness, Siri can now provide more accurate and helpful responses, making it a powerful assistant for managing daily tasks and schedules. ii. Writing Assistant: Integrated into apps like Notes and Mail, this tool helps professionals draft, proofread, and refine their texts, ensuring clear and effective communication. iii. Live Audio Transcription: This feature allows users to record meetings or lectures and get real-time transcriptions, which can be searched and referenced later, enhancing productivity and information retention. iv. Smart Reminders: This tool uses AI to prioritize and remind you of important tasks based on your habits and schedule, ensuring you never miss a crucial deadline. v. Visual Lookup: Leveraging advanced image recognition, this feature helps you identify objects, landmarks, and even plants in your photos, making it a handy tool for research and presentations. These tools, powered by Apple’s advanced AI models, are set to revolutionize the way technology professionals work, making daily tasks more efficient and enjoyable. Feel free to share your thoughts or ask questions about these exciting updates! Set the 🔔 notification on my page, don’t miss a post! #genai #technology #artificialintelligence Apple Intelligence Foundation Language Models https://lnkd.in/eMe_8svD iOS gets an AI upgrade: Inside Apple’s new ‘Intelligence’ system https://lnkd.in/euG7C-7V

Cohere latest LLMs are now available on Azure AI Model Catalog. The catalog now offers more than 1,600 foundation models. #AzureAI #modelcatalog #Cohere

For those of you who want to learn more on prompt engineering on #GenAI with #Bedrock, watch this amazing video at #ReInvent

Effective prompting is essential to get the best performance out of LLMs. Here are some tips from an Anthropic prompt engineer on how to optimally construct prompts and build for complex business use cases.

Get the most out of generative AI with prompt engineering and Anthropic's Claude LLM in Amazon Bedrock. ☁️⚡🤖 https://go.aws/4bqhOgE Watch the session and learn how to choose the most appropriate formats, phrases, words, and symbols to maximize generative AI solutions while improving accuracy and performance. #AmazonBedrock #GenerativeAI #Anthropic

You can learn about what Neo4j is doing with Amazon Web Services (AWS) #Bedrock, Microsoft #Azure OpenAI service and Google #Gemini with these examples. They show how to parse data to populate a graph database with LLMs. Then they walk through using a RAG model to ground an LLM. Check it out here:

Effective prompting is essential to get the best performance out of LLMs. Here are some tips from an Anthropic #prompt engineer on how to optimally construct prompts and build for complex business use cases. #promptengineering #prompting #llms #generativeai #amazonbedrock

There are a lot of good prompt engineering guides out there but I believe this is one of the best, especially when it comes to Anthropic's Claude in Amazon Bedrock. My favorite part is how assigning roles to Claude (aka role prompting) results in improved accuracy- simple and effective! Great, easy-to-follow overview of a wide range of prompt engineering best practices by Nicholas Marwell. #GenerativeAI

Knowledge Graphs can provide rich context to ground LLMs for enabling GenAI applications using Graph RAG (Retrieval Augmented Generation) The real-world data captured in the graph avoids hallucination and provides a rich source of information for the LLMs to generate answers, summaries and suggestions from.

What does state of the early web have in common with the state of AI today? Find out in this talk from Dan from the SD AWS meetup! https://lnkd.in/gw3SxbnS