♟️ Ch3ssVid5 — sync chess games with YouTube video commentary. The board follows the video automatically.
Free, open-source, no account needed.
🔗 https://t.co/G72Rp1a3dB
📚 Ch3ssVid5 Hub has 1000+ #chess videos from GothamChess, Blitzstream, Hanging Pawns & more —
What's missing? Moves and timestamps. That's where you come in.
Pick a video, add moves/timestamps, submit a PR.
https://t.co/HXpYXOxv5I
@IDFmobilites Je vous confirme que les tourniquets à #Invalides (Metro vers RER C) sont buggés et décomptent un nouveau ticket alors que le ticket actuel est toujours valide ! Je me suis fait avoir plusieurs fois. Comment se faire rembourser ? Merci
I ran a small experiment: vibe‑authoring a technical e‑book with AI.
Over a few weeks, I created “Copilot Studio Gems 💎” and published it as a website:
👉 https://t.co/ldqQkVK7wZ
#CopilotStudio#GenerativeAI
I wasn’t really a “writer”.
My role was closer to editor/curator/architect:
. Shaping concepts.
. Selecting what matters.
. Refining quality.
. Building the site.
Avec la 3e cohorte du Microsoft GenAI Studio, nous continuons à soutenir l’émergence des futurs champions français de l’IA générative 🤝
Une nouvelle promotion de 15 startups démarre un accompagnement intensif aux côtés de nos experts et partenaires.
👏 Félicitations aux lauréats !
https://t.co/sRu4QcKiVG
AI Agents Cheat Sheet
[ Read. Bookmark. Repost ]
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This is a good starting point if you're trying to make sense of AI agents.
There’s a lot of talk about agent frameworks right now, but at the core, most of them build on the same set of ideas.
This cheat sheet gives a simple overview of the key building blocks, from LLMs to orchestration to protocols. Useful whether you’re exploring agent tooling, building internal automations, or just trying to understand the space better.
What is an AI agent?
- Agents combine reasoning with the ability to take action.
- They don’t just respond, they can plan, call tools, access data, and trigger real-world effects.
Language Model
- This is the core reasoning engine. It interprets input and generates plans or responses.
- But by itself, it can’t take real-world actions.
Tools
- APIs, functions, and external integrations that agents use to do useful work, like querying a database, sending an email, or calling a webhook.
Orchestration Layer
- This layer coordinates what the agent does, how it reasons (via CoT, ReAct, etc.), how it sequences steps, and how it interacts with tools.
Agentic Protocols
- Protocols like MCP and A2A enable agents to collaborate across platforms (e.g., Slack, GitHub) and maintain context across tasks.
Building AI Agents
- There’s no single way to build an agent.
- Some start with a single prompt. Others use low-code platforms. Some teams build full custom frameworks.
The cheat sheet maps out the trade-offs.
If you’re trying to understand the agent space, or explain it to your team, this breakdown might help.
Save it if you want a reference to come back to.
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Follow @techNmak for regular insights.
La mauvaise nouvelle : C'est déjà la fin des candidatures pour la 3e édition du Microsoft GenAi Studio.
La bonne nouvelle : vous avez été +180 startups françaises à tenter votre chance !
RDV le 5 janvier pour découvrir les lauréats !
DevOps vs. MLOps vs. LLMOps:
Many teams are trying to apply DevOps practices to LLM apps.
But DevOps, MLOps, and LLMOps solve fundamentally different problems.
DevOps is software-centric. You write code, test it, and deploy it. The feedback loop is straightforward: Does the code work or not?
MLOps is model-centric. Here, you're dealing with data drift, model decay, and continuous retraining. The code might be fine, but the model's performance can degrade over time because the world changes.
LLMOps is foundation-model-centric. Here, you're typically not training models from scratch. Instead, you're selecting foundation models and then optimizing through three common paths:
- Prompt Engineering
- Context/RAG Setup
- Fine-Tuning
But here's what really separates LLMOps: The monitoring is completely different.
In MLOps, you track data drift, model decay, and accuracy.
In LLMOps, you're watching for:
- Hallucination detection
- Bias and toxicity
- Token usage and cost
- Human feedback loops
This is because you can't just check if the output is "correct." You need to ensure it's safe, grounded, and cost-effective.
The evaluation loop in LLMOps also feeds back into all three optimization paths simultaneously. Failed evals might mean you need better prompts, richer context, OR fine-tuning.
So it's not a linear pipeline anymore.
One more thing: prompt versioning and RAG pipelines are now first-class citizens in LLMOps, just like data versioning became essential in MLOps.
And the ops layer you choose should match the system you're building.
👉 Over to you: What does your LLM monitoring stack look like right now?
____
Find me → @_avichawla
Every day, I share tutorials and insights on DS, ML, LLMs, and RAGs.
Merci La Boîte à Pizza de venir offrir des pizzas aux équipes de garde. Chacun à sa manière, chacun à son niveau, on participe tous à la lutte contre le coronavirus. La victoire contre le covid-19 sera celle de toute la Nation!
L’Association Professionnelle de Sages-Femmes et La Boîte Rose lancent une opération d’urgence pour soutenir les soignants et les accouchées Covid+. Protégeons les femmes enceintes et les nouveau-nés. Ils sont la Vie de demain. Participez et retweetez !
https://t.co/6yUZdLe8nO
AP-HP/Hôpital Trousseau. Lorsque le coronavirus vole des vies, les femmes continuent à donner la Vie. Les sages-femmes sont là pour elles. Fière d’être au service des femmes, au service de la Nation, au service de la Vie. #covid-19
Just finished "Understanding #Enterprise#Architecture" course from #Pluralsight. It gives a good overview of the domain and associated topics, with a dedicated part to align with #Agile principles: https://t.co/O3m5qe34WX
Been tuning my internet #VDSL connection. Disconnected unused home connectors that were attenuated signal, kept only the one to internet box: 20/1 to 37/7 (D/U Mbps)
#Scrum PSM I exam passed! 🙂 Thanks #Microsoft for the training & exam. Eager to apply this framework with my customers while driving their #DigitalTransformation...