Skywork Super Agents is an AI-powered office suite designed to create various types of content. It leverages expert agents to generate documents, presentations, spreadsheets, and other formats like webpages and podcasts. Skywork aims to transform simple input into complex, multimodal content, making it ideal for analysts and professionals who need to produce different types of content. Its functionality is similar to DeepResearchAgent, a multi-agent system for deep research and general task solving. https://skywork.ai/ #Skywork #SkyworkAI #DeepResearchAgent #AIOfficeSuite #AICreator #MultimodalAI #ContentCreation #DocumentGeneration #PresentationMaker #SpreadsheetSoftware #WebpageBuilder #PodcastCreator #ProductivityTools #AItools

The Prompt Report: A Systematic Survey of Prompting Techniques "The Prompt Report," is the result of an extensive study analyzing over 1,500 academic papers on prompting conducted by a team of researchers from leading institutions. It introduces a structured taxonomy of 58 prompting techniques organized into six categories, highlighting effective strategies such as Few-Shot and Chain-of-Thought prompting. Additionally, the report discusses the importance of In-Context Learning and assesses the performance of various prompting techniques while offering insights into future challenges and developments in human-AI interactions. Key Points - A systematic analysis resulted in the creation of "The Prompt Report," detailing over 58 prompting techniques within a comprehensive 80-page document. - The report categorizes prompting techniques into six problem-solving areas, enabling users to identify and apply the best methods for their tasks. - In-Context Learning (ICL) allows language models to perform tasks based on examples within prompts, emphasizing the power of Few-Shot techniques. - Effective prompt design hinges on various factors including the quality, quantity, and format of examples used in prompts. - Benchmarking results reveal Few-Shot Chain-of-Thought techniques as superior for reasoning tasks, while Self-Consistency is less effective than anticipated. - Comparisons show that AI-driven prompt engineering tools can outperform manual efforts, highlighting advancements in automated prompting techniques. - The report addresses future challenges in prompting, including prompt drift, multilingual applications, and integrating multimodal inputs. https://learnprompting.org/blog/the_prompt_report https://huggingface.co/papers/2406.06608 https://www.researchgate.net/publication/381318099_The_Prompt_Report_A_Systematic_Survey_of_Prompting_Techniques #PromptReport #PromptEngineering #InContextLearning #FewShotLearning #ChainOfThought #PromptingTechniques #AI #NLP #LanguageModels #HumanAIInteraction #PromptDrift #MultilingualAI #LearnPrompting #AISurvey #PromptTaxonomy #SelfConsistency #PromptTools

BIG ANNOUNCEMENT TODAY !!! Sam Altman, Casey Chu, Isa Fulford, Yash Kumar, and Zhiqing Sun introduce and demo the new "unified agentic model" in ChatGPT. https://youtu.be/1jn_RpbPbEc #ChatGPT #SamAltman #CaseyChu #IsaFulford #YashKumar #ZhiqingSun #UnifiedAgenticModel #AIModel #AgenticAI #LargeLanguageModel #LLM #AIMultimodal #GenerativeAI #GPT #OpenAI #AIDemo #AIAnnouncement #AICapabilities

How l switched back to Augment Code from Claude Code ! Tried new Claude Code ... verdict: Worth every penny love the little to-do lists but hell lot expensive ! So what do l do l head back home to the loving arms of Augment Code ... still the best and always will be ! (For now 🤫 ... you know relationships nowadays) So this article exaplins why they are nota big fan of Model Pickers ... makes sense though would be great to have the ooption still !). Here is a low done on Augment code and its recent updates: Augment Code is considered a top AI coding agent due to its advanced context engine, which enables personalized and efficient code generation, and its seamless integration with popular IDEs. It also boasts features like memory persistence, which allows it to adapt to individual coding styles, and Multi-Context Programming (MCP) for connecting to various tools and systems, enhancing its utility in the development workflow. Here's a more detailed breakdown of why Augment Code stands out: 1. Contextual Awareness and Memory: Context Engine: Augment's Context Engine is a key differentiator. It analyzes the entire codebase in real-time, providing context-aware suggestions and code completions, leading to more accurate and relevant AI-driven code generation. Memory Persistence: The platform remembers your coding style and project patterns, ensuring that its suggestions are tailored to your preferences and codebase over time, improving efficiency and reducing errors. MCP (Multi-Context Programming): Augment Code goes beyond just the code by integrating with various tools and systems, such as Vercel, Cloudflare, and more, allowing it to gather more information, automate tasks, and even fix issues in live systems. 2. IDE Integration and Workflow: Seamless Integration: Unlike some AI coding tools that require a separate editor, Augment Code integrates directly with popular IDEs like VS Code, JetBrains, Vim, and GitHub, allowing developers to leverage its AI capabilities within their familiar environment. Code Checkpoints: Augment Code automatically tracks changes and creates checkpoints, enabling easy rollback and providing peace of mind when the agent tackles complex tasks. Remote Agent Functionality: Augment Code can operate in a separate container, allowing developers to work on code even when their main machine is off or unavailable, and even run multiple agents in parallel. 3. Advanced Features and Capabilities: Multi-Modal Support: Augment Code can handle various inputs, including screenshots and Figma files, making it helpful for implementing UI elements and debugging visual issues. Terminal Interaction: Beyond code editing, Augment Code can run terminal commands, streamlining tasks like installing dependencies or running dev servers. Auto Mode: For a more streamlined experience, Augment Code offers an Auto Mode, where it automatically applies suggested changes without requiring explicit confirmation for each action. 4. Focus on Collaboration and Productivity: Developer-Centric: Augment Code is designed to work alongside developers, enhancing their existing workflow rather than replacing it, making it a collaborative rather than a replacement tool. Time Savings: By automating tasks, providing accurate suggestions, and handling repetitive coding tasks, Augment Code frees up developers' time to focus on more complex and creative aspects of their work. Continuous Improvement: Through feedback loops and learning from user interactions, Augment Code continuously improves its performance and adapts to the evolving needs of developers. https://www.augmentcode.com/blog/ai-model-pickers-are-a-design-failure-not-a-feature #augmentcode #claude #aicodingagent #aicode #vscode #jetbrains #vim #github #ideintegration #codingtools #productivitytools #memorypersistence #contextengine #multicontextprogramming #vercel #cloudflare #codecheckpoints #remotework #multimodal #figma #terminalinteraction #automode #developercentric #aitools #aidesign #coding #softwaredevelopment #aitool

NVIDIA's Nemotron family delivers enterprise-grade multimodal AI models designed for complex reasoning tasks across scientific research, advanced mathematics, coding, and visual analysis. The lineup includes three variants optimized for different deployment scenarios: Nano for edge computing and cost-sensitive applications, Super for single-GPU workloads balancing performance and efficiency, and Ultra for maximum accuracy in data center environments. Unlike many AI models with restrictive licensing, Nemotron offers commercial viability with an open license that allows organizations to customize the models while maintaining control over their data and deployments. #Nemotron #NVIDIANemotron #NVIDIA #MultimodalAI #EnterpriseAI #AICoding #AIScience #AIReasoning #OpenSourceAI #EdgeAI #ComputerVision #AIModels #MachineLearning #ArtificialIntelligence #TechInnovation https://build.nvidia.com/nvidia/llama-3_1-nemotron-ultra-253b-v1 https://github.com/NVIDIA/GenerativeAIExamples

Project Astra demonstrates a universal AI assistant's capabilities in helping with bike repairs. It assists in finding user manuals, YouTube tutorials, email details, and making phone calls to bike shops. The assistant also provides information on brake pads and suggests dog baskets for the bike, showcasing its multifunctional support. #ProjectAstra #GeminiAI #AIassistant #MultimodalAI #GoogleAI #BikeRepair #AIsupport #GenerativeAI #VisionAI #ContextAwareAI #RealTimeAI #DogBasket #MaintenanceAI #LLM #Chatbot https://youtu.be/JcDBFAm9PPI?si=8NjCKhOF81GDG4k1

Building complex, production-ready AI agents, especially multi-modal or multi-agent systems, can be challenging. Introducing the Agent Development Kit (ADK), a new open-source project from Google designed to simplify this process based on Google's internal experience. ADK provides a powerful, open foundation (model-agnostic, deployment-agnostic, interoperable) that makes agent development feel like software development, complete with native multi-modal streaming and easy local debugging via a built-in UI. Watch Product Manager Anand Iyer, Tech Lead Bo Yang, and Developer Advocate, Ivan Nardini introduce ADK and demo building a multi-agent, multi-modal travel planner quickly using the SDK. Learn about the core design principles and see how you can get started building your own sophisticated AI agents today. Resources: Get Started → https://google.github.io/adk-docs Sample Agents → https://goo.gle/3Rbdo4s Subscribe to Google for Developers → https://goo.gle/developers #ADK #AgentDevelopmentKit #GoogleAI #OpenSource #AIAgents #MultiModal #MultiAgentSystems #AIDevelopment #AIWorkflow #GenAI #LangChain #AutoGen #AIInfrastructure #SoftwareDevelopment #DebuggingUI #TravelPlanner #Python #AICommunity #ModelAgnostic #DeploymentAgnostic

Building complex, production-ready AI agents, especially multi-modal or multi-agent systems, can be challenging. Introducing the Agent Development Kit (ADK), a new open-source project from Google designed to simplify this process based on Google's internal experience. ADK provides a powerful, open foundation (model-agnostic, deployment-agnostic, interoperable) that makes agent development feel like software development, complete with native multi-modal streaming and easy local debugging via a built-in UI. Watch Product Manager Anand Iyer, Tech Lead Bo Yang, and Developer Advocate, Ivan Nardini introduce ADK and demo building a multi-agent, multi-modal travel planner quickly using the SDK. Learn about the core design principles and see how you can get started building your own sophisticated AI agents today. #ADK #AgentDevelopmentKit #GoogleAI #AIAgents #MultiModal #MultiAgentSystems #OpenSource #SoftwareDevelopment #AIDevelopment #AIWorkflow #AItools #AutoGen #LangChain #AIPlanning #Debugging #BuiltInUI #TravelPlanner #AgentFramework #ModelAgnostic #DeploymentAgnostic https://youtu.be/zgrOwow_uTQ

🚀 Exciting News! 🚀 Dive into the world of AI with this fantastic interactive tutorial on prompt engineering by Anthropic! Whether you're a curious beginner or a seasoned tech enthusiast, this course is designed to spark your creativity and enhance your understanding of AI-driven solutions. Don't miss out on the opportunity to learn from the best and elevate your skills! Check it out here: https://github.com/anthropics/courses/tree/master/prompt_engineering_interactive_tutorial/Anthropic%201P Welcome to Anthropic's educational courses. This repository currently contains five courses. We suggest completing the courses in the following order: Anthropic API fundamentals - teaches the essentials of working with the Claude SDK: getting an API key, working with model parameters, writing multimodal prompts, streaming responses, etc. Prompt engineering interactive tutorial - a comprehensive step-by-step guide to key prompting techniques. [AWS Workshop version] Real world prompting - learn how to incorporate prompting techniques into complex, real world prompts. [Google Vertex version] Prompt evaluations - learn how to write production prompt evaluations to measure the quality of your prompts. Tool use - teaches everything you need to know to implement tool use successfully in your workflows with Claude. #AI #MachineLearning #ArtificialIntelligence #TechTrends #Innovation #FutureTech #AICommunity #LearnAI #TechEducation #DigitalSkills #AIRevolution #TechLovers #CodingLife #InteractiveLearning #AnthropicAI #PromptEngineering #ExploreAI #TechSavvy #AIInsights #SkillUp

BAGEL is a multimodal foundation model developed by ByteDance. It's an open-source model with 7 billion active parameters (14 billion total). BAGEL was trained on extensive interleaved multimodal data. It's designed for unified generation and understanding, building upon large language models. The model was introduced in May 2025. https://github.com/ByteDance-Seed/Bagel

Google I/O 2025 is scheduled for May 20-21, 2025. The conference will feature announcements and launches from Google, including updates on their latest AI models with a focus on accessibility, flexibility, privacy, and expanded multimodal capabilities on mobile devices. Additionally, the conference will likely include interactive elements, such as the 'I/O puzzle' that involves guiding light beams to solve challenges. https://io.google/2025 #GoogleIO2025 #TechInnovation #FutureOfAI #MobileRevolution #AccessibilityMatters #PrivacyFirst #TechUpdates #AIForEveryone #DigitalTransformation #InnovationUnveiled #TechCommunity #MobileTech #AIUpdates #CuttingEdgeTech #StayCurious