How queries are answered on GRID: Every question runs through a multagent workflow models, datasets, and apps collaborate in real time to deliver the most accurate response. The SENT economy: 1:Users pay to access intelligence 2:Builders earn by contributing @SentientAGI

Have you looked into the multagent "eigencode" abilities that you can use to run 4 ( no limit ) instances of Claude similarly to the Grok 4 Heavy has multiple agents? Or the Claude Code / Gemini bridge systems? I'm considering switching to Grok 4 Heavy, but not sure yet.

🤖🚗⚙ 𝘼𝙄 𝘼𝙜𝙚𝙣𝙩𝙨 𝙞𝙣 𝙀𝙣𝙜𝙞𝙣𝙚𝙚𝙧𝙞𝙣𝙜 𝘿𝙚𝙨𝙞𝙜𝙣: 𝘼 𝙈𝙪𝙡𝙩𝙞-𝘼𝙜𝙚𝙣𝙩 𝙁𝙧𝙖𝙢𝙚𝙬𝙤𝙧𝙠 𝙛𝙤𝙧 𝘼𝙚𝙨𝙩𝙝𝙚𝙩𝙞𝙘 & 𝘼𝙚𝙧𝙤𝙙𝙮𝙣𝙖𝙢𝙞𝙘 𝘾𝙖𝙧 𝘿𝙚𝙨𝙞𝙜𝙣 ⚙🚗🤖 #for_ai_scientists #for_ai_researchers #for_ai_architects #did_you_know_that researchers from @MIT and Technical University of Munich have developed an AI multi-agent framework that revolutionizes car design by seamlessly integrating aesthetic appeal with aerodynamic efficiency? 💡 𝙏𝙝𝙚 𝙄𝙙𝙚𝙖: • Collaborative Design Intelligence: The framework deploys multiple AI agents that simulate distinct engineering roles, generating innovative car design alternatives that balance form and function. • Aesthetic & Aerodynamic Optimization: By evaluating design proposals on both aesthetic criteria and aerodynamic performance, the system ensures that each design not only looks striking but also performs efficiently. • Iterative Multi-Agent Process: Agents interact and negotiate design parameters in a continuous loop, refining proposals based on real-time feedback and simulation results to achieve optimal design outcomes. • Enhanced Decision Support: This multi-agent approach empowers designers with data-driven insights, streamlining the traditionally complex and subjective car design process. 🔥 𝙆𝙚𝙮 𝙁𝙞𝙣𝙙𝙞𝙣𝙜𝙨: • Synergistic Agent Collaboration: The integration of specialized AI agents leads to richer design exploration, uncovering innovative solutions that might be overlooked by conventional methods. • Dual-Focus Evaluation: Simultaneously addressing aesthetics and aerodynamics ensures that the final car designs meet both visual and performance standards. • Iterative Refinement: Continuous feedback and simulation allow the system to dynamically adapt and improve design proposals, significantly reducing development time. Special thanks to Mohamed Elrefaie, Janet Qian, Raina Wu, Qian Chen, Angela Dai and Faez Ahmed for their pioneering work: AI Agents in Engineering Design: A Multi-Agent Framework for Aesthetic and Aerodynamic Car Design 🔗 lnkd.in/dxQ9K7A7 ⭐ Star the latest Agentic AI Research repo: 🔗 lnkd.in/gc78FSAH 🔔 Stay tuned and subscribe: 🔗 lnkd.in/dxt7fYJk #favikon #cloud #cloudcomputing #ai #artificialintelligence #automotivedesign #engineeringdesign #multagent #framework #aerodynamics #aesthetics #carinnovation #automotive #designoptimization #optimization #collaboration #innovation #research #machinelearning #deeplearning #autonomousdesign #techtrends #futureofcars #industry40 #sustainability #simulation #virtualdesign #computationaldesign #engineering #agenticai #digitaltransformation

Prompt engineering, memory (retrieval augmented generation), agents, multagent frameworks, AI models from scratch, finetuning, etc.: deeplearning.ai/courses/

#Learn how to #develop a #MultAgent #System #communication using #wcf. Practical #ArtificialIntelligence: #machinelearning, #bots and agent solutions using C# (700 pages,17 chapters, Apress, 2018)@GoogleAI @DeepMindAI @MachineLearnDC #DeepLearning #BigData amazon.com/Practical-Artific…