#GenAI #AI #MachineLearning #Automation #ArtificialIntelligence #AIagents
#GenAI #AI #MachineLearning #Automation #ArtificialIntelligence #AIagents
📊 As the complexity of your tasks grows, so does the capability of your AI solutions. Understand the progression and choose the right system for your needs!
Credit:- Rakesh Gohel
💬 𝐖𝐡𝐢𝐜𝐡 𝐆𝐞𝐧𝐀𝐈 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 𝐟𝐢𝐭𝐬 𝐲𝐨𝐮𝐫 𝐜𝐮𝐫𝐫𝐞𝐧𝐭 𝐧𝐞𝐞𝐝𝐬?
📊 As the complexity of your tasks grows, so does the capability of your AI solutions. Understand the progression and choose the right system for your needs!
Credit:- Rakesh Gohel
💬 𝐖𝐡𝐢𝐜𝐡 𝐆𝐞𝐧𝐀𝐈 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 𝐟𝐢𝐭𝐬 𝐲𝐨𝐮𝐫 𝐜𝐮𝐫𝐫𝐞𝐧𝐭 𝐧𝐞𝐞𝐝𝐬?
📌 Use-Cases
LLM: Text generation or answering simple questions.
RAG: Retrieving and summarizing up-to-date knowledge.
AI Agent: Automating single-user tasks that need planning and tool use.
Agentic AI: Handling complex, multi-step tasks where agents collaborate and coordinate.
📌 Use-Cases
LLM: Text generation or answering simple questions.
RAG: Retrieving and summarizing up-to-date knowledge.
AI Agent: Automating single-user tasks that need planning and tool use.
Agentic AI: Handling complex, multi-step tasks where agents collaborate and coordinate.
Multi-Agent Collaboration: A system where multiple agents work together, divide tasks, and adapt over time.
Adaptive & Persistent: Provides memory, feedback, and reasoning across agents to tackle large-scale tasks.
Multi-Agent Collaboration: A system where multiple agents work together, divide tasks, and adapt over time.
Adaptive & Persistent: Provides memory, feedback, and reasoning across agents to tackle large-scale tasks.
Autonomous Task Execution: Integrates planning, reasoning, and memory to execute workflows.
Goal-Oriented Automation: Ideal for multi-step tasks requiring structured plans.
📌 4.
Autonomous Task Execution: Integrates planning, reasoning, and memory to execute workflows.
Goal-Oriented Automation: Ideal for multi-step tasks requiring structured plans.
📌 4.
Knowledge-Enhanced: Combines LLM output with real-time retrieval for more accurate and up-to-date responses.
Data-Dependent Precision: Perfect for Q&A and knowledge-based tasks.
📌 3.
Knowledge-Enhanced: Combines LLM output with real-time retrieval for more accurate and up-to-date responses.
Data-Dependent Precision: Perfect for Q&A and knowledge-based tasks.
📌 3.
Context-Free Generation: Ideal for simple text generation and basic chatbots.
Fast & Simple: Low complexity but limited context understanding.
📌 2.
Context-Free Generation: Ideal for simple text generation and basic chatbots.
Fast & Simple: Low complexity but limited context understanding.
📌 2.
📌 1.
📌 1.
Credit:- Generative AI
💬 𝐖𝐡𝐢𝐜𝐡 𝐭𝐨𝐨𝐥𝐬 𝐚𝐫𝐞 𝐲𝐨𝐮 𝐮𝐬𝐢𝐧𝐠, 𝐨𝐫 𝐰𝐡𝐢𝐜𝐡 𝐨𝐧𝐞𝐬 𝐝𝐨 𝐲𝐨𝐮 𝐰𝐚𝐧𝐭 𝐭𝐨 𝐭𝐫𝐲? 𝐋𝐞𝐭’𝐬 𝐝𝐢𝐬𝐜𝐮𝐬𝐬!
#AI #Productivity #Automation #DataScience #TechInnovation #AItools
Credit:- Generative AI
💬 𝐖𝐡𝐢𝐜𝐡 𝐭𝐨𝐨𝐥𝐬 𝐚𝐫𝐞 𝐲𝐨𝐮 𝐮𝐬𝐢𝐧𝐠, 𝐨𝐫 𝐰𝐡𝐢𝐜𝐡 𝐨𝐧𝐞𝐬 𝐝𝐨 𝐲𝐨𝐮 𝐰𝐚𝐧𝐭 𝐭𝐨 𝐭𝐫𝐲? 𝐋𝐞𝐭’𝐬 𝐝𝐢𝐬𝐜𝐮𝐬𝐬!
#AI #Productivity #Automation #DataScience #TechInnovation #AItools
Credit:- artificialintelligencenews.in
𝐖𝐡𝐚𝐭’𝐬 𝐧𝐞𝐱𝐭 𝐟𝐨𝐫 𝐀𝐈 𝐚𝐬 𝐢𝐭 𝐤𝐞𝐞𝐩𝐬 𝐫𝐚𝐢𝐬𝐢𝐧𝐠 𝐭𝐡𝐞 𝐛𝐚𝐫? 𝐋𝐞𝐭’𝐬 𝐝𝐢𝐬𝐜𝐮𝐬𝐬!
Credit:- artificialintelligencenews.in
𝐖𝐡𝐚𝐭’𝐬 𝐧𝐞𝐱𝐭 𝐟𝐨𝐫 𝐀𝐈 𝐚𝐬 𝐢𝐭 𝐤𝐞𝐞𝐩𝐬 𝐫𝐚𝐢𝐬𝐢𝐧𝐠 𝐭𝐡𝐞 𝐛𝐚𝐫? 𝐋𝐞𝐭’𝐬 𝐝𝐢𝐬𝐜𝐮𝐬𝐬!
Credit:- Adam Biddlecombe
𝐖𝐢𝐥𝐥 𝐲𝐨𝐮 𝐛𝐞 𝐜𝐫𝐞𝐚𝐭𝐢𝐧𝐠 𝐯𝐢𝐝𝐞𝐨𝐬 𝐰𝐢𝐭𝐡 𝐀𝐈 𝐧𝐨𝐰? 𝐋𝐞𝐭 𝐦𝐞 𝐤𝐧𝐨𝐰 𝐛𝐞𝐥𝐨𝐰 👇
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Credit:- Adam Biddlecombe
𝐖𝐢𝐥𝐥 𝐲𝐨𝐮 𝐛𝐞 𝐜𝐫𝐞𝐚𝐭𝐢𝐧𝐠 𝐯𝐢𝐝𝐞𝐨𝐬 𝐰𝐢𝐭𝐡 𝐀𝐈 𝐧𝐨𝐰? 𝐋𝐞𝐭 𝐦𝐞 𝐤𝐧𝐨𝐰 𝐛𝐞𝐥𝐨𝐰 👇
♻️ Don’t forget to share this with others who want to create viral content quickly!