Not all food is real food.
Many everyday staples are engineered with chemicals and fillers.
Here are 5 of the worst ultra-processed factory foods, and why they’re damaging your health:
1/ Mayonnaise
இன்றைய AI வகுப்பு.
தலைப்பு: மொழியும் இயந்திரங்களும்
Language and machines
சூம்: https://t.co/0j3zejKgvi
3 ஆவது அமர்வு:
ஏப்ரல் 4 2026
நேரம்: 6:30 மாலை – 8:00 IST
அனுமதி இலவசம்.
உரையாடல் களம் -
https://t.co/foT3Ye0hF3
Colab Notesbooks இங்கே. https://t.co/iSxqe0rfaz
🚀 Together, We Made #TechXConf2025 Truly Extraordinary! 🙏
As we look back on the phenomenal journey of #TechXConf2025 – The AI & Cloud Conference, held on November 01 at the Chennai Trade Centre, our hearts are filled with immense pride and gratitude.
With 3000+ passionate attendees - from ambitious newcomers to seasoned experts - the event celebrated the vibrant energy and limitless potential of our thriving tech community.
🎙️ To our esteemed speakers:
Your powerful sessions and thought-provoking discussions left a deep impression on everyone present. Thank you for sharing your wisdom so generously.
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Your hard work, precision, and passion behind the scenes made every detail shine. We couldn’t have done it without you.
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Your enthusiasm, curiosity, and participation were the true heartbeat of #TechXConf2025. You made this event unforgettable.
✨ This year’s conference once again proved the power of community, innovation, and collaboration. Together, we’re not just shaping the future- we’re building it.
See you next year at #TechXConf2026!
#TechXConf2025 #TechXConf #AI #Cloud #ChennaiTechEvents #Innovation #Community #Technology #Networking #Collaboration #Leadership #Community #Gratitude #Inspiration #TechnologyLeadership
🎤 AI Agent Lifecycle – Evaluation to Execution
Join @NavaneethhGopal from @IngramMicroIND for a deep dive into AgentOps, covering the complete lifecycle of AI agents from evaluation to real-world execution. This session will explore core principles, effective evaluation strategies, and best practices to successfully deploy and manage autonomous AI agents at scale.
🌟 Register Now: https://t.co/VhEsFYNMLf
#AI #AgentOps #AutonomousAgents #TechXConf2025 #TechXConf
🚀 Speaker Announcement: TechXConf 2025!
We’re thrilled to welcome Navaneethan Gopal from Ingram Micro to the stage at TechXConf 2025! 🎤
Join us to hear insights from one of the industry’s leading voices in AI and Cloud Computing.
Don’t miss this chance to hear from one of the best in the field!
👉 Secure your spot now: https://t.co/efWr1Hzt2V
#TechXConf2025 #AI #CloudComputing #Innovation #TechLeaders #TechXConf #ChennaiEvents #TechX
@mansukhmandviya@IndiaSports@PMOIndia@AllCBSENews This is the sad state of Nationals competition...forget about participating in international we will not even get a chance to watch international games with this kind of ineligible schools gets awarded for conducting Nationals competitions....
Someone asked, how do I invest in mutual funds for my child? Today @PosteAnil gives you the answer. Open a free account on MF Utilities & simply follow the process below. Update the child's KYC when he/she turns 18 & let them take over. https://t.co/eMPfQHcof1
Join us for @Microsoft@Azure & @elastic Skillup Tamilnadu–Session 6 on July 12th in Chennai, where passionate developers, cloud enthusiasts, and tech leaders come together to learn, share,and grow.
RSVP Link: https://t.co/QGVSo27SLv
@NavaneethhGopal#MVP#MVPBuzz@ErohsikK
Such an interesting question: "What jobs will be relevant in 10 years?"
Personally, I think the days of 4-year college courses are over, lifelong learning is the new norm, for everyone...
This might be the ONLY 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲𝘀 resource you need.
Here’s what's inside:
• Single vs. multi-agent systems
• Key patterns in multi-agent architectures
• 6 practical examples that you can start implementing immediately
Download your FREE copy of the complete guide: https://t.co/APMmURctzo
Here is how you break down 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗠𝗲𝗺𝗼𝗿𝘆 👇
In general, the memory for an agent is something that we provide via context in the prompt passed to LLM that helps the agent to better plan and react given past interactions or data not immediately available.
It is useful to group the memory into four types:
𝟭. Episodic - This type of memory contains past interactions and actions performed by the agent. After an action is taken, the application controlling the agent would store the action in some kind of persistent storage so that it can be retrieved later if needed. A good example would be using a vector Database to store semantic meaning of the interactions.
𝟮. Semantic - Any external information that is available to the agent and any knowledge the agent should have about itself. You can think of this as a context similar to one used in RAG applications. It can be internal knowledge only available to the agent or a grounding context to isolate part of the internet scale data for more accurate answers.
𝟯. Procedural - This is systemic information like the structure of the System Prompt, available tools, guardrails etc. It will usually be stored in Git, Prompt and Tool Registries.
𝟰. Occasionally, the agent application would pull information from long-term memory and store it locally if it is needed for the task at hand.
𝟱. All of the information pulled together from the long-term or stored in local memory is called short-term or working memory. Compiling all of it into a prompt will produce the prompt to be passed to the LLM and it will provide further actions to be taken by the system.
We usually label 1. - 3. as Long-Term memory and 5. as Short-Term memory.
A visual explanation of potential implementation details 👇
And that is it! The rest is all about how you architect the topology of your Agentic Systems.
What are your thoughts about memory in AI Agents?
#LLM #AI #MachineLearning
Stanford just uploaded a 1-hour webinar on "Agentic AI" covering:
> basics of LLMs and training
> prompting best practices
> reasoning and actions in agents
> agentic design patterns
> customer support example
the internet is filled with great resources on ai agents.
Just shared a new article on "The State of Reinforcement Learning for LLM Reasoning"!
If you are new to reinforcement learning, this article has a pretty generous intro section (PPO, GRPO, etc)
I addition, I cover 15 recent articles focused on RL and Reasoning Models,