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@Rippling AI is a multi-agent system of Deep Agents. Under each supervisor agent, 3 specialized Deep Agents are placed below them. Reading agents: Query structured data across Rippling product domains + connected platforms
SYSTEMS
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Deep Agents multi-agent system with reading agents
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Seamless AI Integration Barrier: Modular Infrastructure for Warehouses
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The biggest adoption barrier today is often the seamless integration of AI systems with existing warehouse operations. Organizations must focus on creating a modular and adaptive infrastructure that can evolve as AI capabilities mature. Achieving this will unlock significant
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GoalOS-native α‑AGI Ascension using AGIALPHA GitHub repository
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GoalOS-native α‑AGI Ascension using AGIALPHA GitHub : https://
github.com/MontrealAI/goa
los-agialpha-ascension
… #AGIALPHA #AGIAscension -
Prompt and loop prevent Fable 5 token waste
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prompt sets goal, context, boundaries, and verification. loop handles time: effort level, checkpoints, verifier subagents, and stop rules so Fable 5 does not burn 500k to 1M tokens unchecked.
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Modern AI helpdesk acts, not just answers
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A modern AI helpdesk doesn't just answer. It acts. → Checks live store data
→ Follows your brand policies
→ Recommends products
→ Handles returns and order updates
→ Knows when to hand off to a human, with full context Across email, chat, SMS, WhatsApp, Instagram, and -
Runtime Managed Deep Agents: durable threads, streaming, checkpoints, human intervention
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The Managed Deep Agents runtime supports:
— LangChain (@LangChain) 11 juin 2026
✅ Durable threads
✅ Streaming runs
✅ Checkpointing
✅ Human-in-the-loop workflows
You can also use the API to create agents, update their configuration, create threads, and stream runs from your own product or platform workflow. pic.twitter.com/mkLRDcJK2xThe Managed Deep Agents runtime supports: Durable threads Streaming executions Checkpoints Workflows with human intervention You can also use the API to create agents, update their configuration,
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Agentic AI lacks standard protocol for sharing assets across platforms
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The agentic AI stack has standards for connecting tools and defining skills, but it still has no standard protocol to share assets across organizations and platforms. Today that means copying files, custom point-to-point integrations, and fragmented vendor-specific
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Reinforcement Learning and Neural Networks for Big Data & AI
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#ReinforcementLearning and Neural Networks. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
geni.us/RL-Neural-Netw
orks
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Mastering NLP From Foundations to Agents by Lior Gazit and Meysam Ghaffari
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“Mastering NLP From Foundations to Agents” by Lior Gazit and Meysam Ghaffari, from @PacktPublishing @PacktDataML http://
amzn.to/4nJrLw4 Learn this:
•Engineer NLP systems from ML foundations to LLM architectures
•Implement RAG pipelines, routing layers, and agent -
AI leaves screens to enter real world at Bosch event
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AI is leaving the screen and moving into the real world.
— Bernard Marr (@BernardMarr) 11 juin 2026
That was my biggest takeaway from day one at Bosch Connected World 2026 in Berlin.
In this summary video, I share some of the key themes from the first day and what they tell us about the next phase of AI.
The big shift… pic.twitter.com/nDMQVsqo8rAI is leaving the screen and moving into the real world. That was my biggest takeaway from day one at Bosch Connected World 2026 in Berlin. In this summary video, I share some of the key themes from the first day and what they tell us about the next phase of AI. The big shift