João Gabriel Lima | AI Tech Leader @ Integritas

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João Gabriel Lima | AI Tech Leader @ Integritas banner
João Gabriel Lima | AI Tech Leader @ Integritas

João Gabriel Lima | AI Tech Leader @ Integritas

@joaogabrieltech

Sr Software Engineer, Tech Leader - Helping companies to integrate AI into their apps and services.

Florianópolis - SC Katılım Mayıs 2022
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João Gabriel Lima | AI Tech Leader @ Integritas retweetledi
Andrés Matte
Andrés Matte@andresmatte·
Today we are launching the Kapso CLI: WhatsApp numbers for agents. 1️⃣ npm install -g @kapso/cli 2️⃣ kapso setup Done, your agent has a WhatsApp number.
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Nikhil Thorat
Nikhil Thorat@nsthorat·
🖐️ micro-handpose: browser hand tracking faster than MediaPipe, pure WebGPU compute shaders. 15 WGSL shaders run palm detection + landmark inference on GPU. 74KB JS (17KB gzip) + 7.7MB weights vs MediaPipe's 34MB package. Zero dependencies. M4 Pro Chrome / iPhone Safari: • micro-handpose — 2.2ms / 72ms (WebGPU) • MediaPipe GPU — 4.0ms / 97ms (WASM+WebGL) • MediaPipe CPU — 4.5ms / 136ms (WASM) npm install @svenflow/micro-handpose const handpose = await createHandpose() const hands = await handpose.detect(video) console.log(hands[0].keypoints.thumb_tip)
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ZARA
ZARA@HeyZaraKhan·
Become a Claude Certified Architect Here is the complete resource list in one place: Link to join: anthropic.skilljar.com/claude-certifi… Training courses: anthropic.skilljar.com (13 free courses) Cookbook: github.com/anthropics/ant… Exam Guide: share.google/0eqIbebzRMUt8K… Practice questions: claudecertifications.com (free) MCP documentation: modelcontextprotocol.io (free) API documentation: docs.anthropic.com (free) Partner Network: anthropic.com/partners (free to join) Personal Playbook someone created after the exam: drive.google.com/file/d/1luC0rn…
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ZARA@HeyZaraKhan

🚨BREAKING: Anthropic just open-sourced a powerful new framework for building AI agents and made it publicly available in a GitHub directory. It’s called “Skills” and it redefines how we work with Claude. Instead of repeating prompts, developers can now create reusable “skills” that package instructions, workflows, and logic into a single unit. A Skill = a structured capability an AI can reliably execute. For example: • Analyze datasets and generate reports • Create structured documents • Automate multi-step workflows • Execute internal business processes Each skill is: • Modular, reusable across projects • Versioned, continuously improvable • Dynamically loaded, used only when needed This solves key problems in today’s AI systems: → Repetitive prompting → Inconsistent outputs → Limited scalability The bigger shift: From: “Prompt engineering” To: “Programmable, reusable AI systems” This is a foundational step toward more reliable, production-ready AI agents. If you're building with AI, this is worth your attention.

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João Gabriel Lima | AI Tech Leader @ Integritas retweetledi
Victor M
Victor M@victormustar·
NVIDIA's Kimodo is the release of the week 🔥 Prompt the timeline whatever your want like: "a person walks forward" → "a person starts jumping", hit Generate, and watch a 3D character do it in seconds (700hrs of pro mocap training. Works on human + robot skeletons. Super fast + free to use on HF)
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João Gabriel Lima | AI Tech Leader @ Integritas retweetledi
SkalskiP
SkalskiP@skalskip92·
we just released RF-DETR 1.6, making fine-tuning 30% faster without losing any accuracy. what started as humble research code is now starting to look a lot more serious. that's not the end of performance optimizations, so stay tuned. link: github.com/roboflow/rf-de…
SkalskiP@skalskip92

we just released RF-DETR segmentation SOTA real-time segmentation + Apache 2.0 license six model sizes with performance spanning from 40.3 mAP at 3.4 ms/image (Nano) to 49.9 mAP at 21.8 ms/image (2XLarge) link: github.com/roboflow/rf-de…

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João Gabriel Lima | AI Tech Leader @ Integritas retweetledi
Muhammad Rizwan Munawar
Muhammad Rizwan Munawar@muhammdrizwanmr·
Mediapipe is cool, but @ultralytics YOLO26 Pose is on another level 🔥🔥🔥 I ran a quick comparison between mediapipe and YOLO pose, and while both have their strengths, YOLO26 blew me away. My findings👇 Raw video credit: NVIDIA Team 😀 #AI #PoseEstimation #People
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João Gabriel Lima | AI Tech Leader @ Integritas retweetledi
General Reasoning
General Reasoning@GenReasoning·
Introducing OpenReward. 🌍 330+ RL environments through one API ⚡ Autoscaled sandbox compute 🍒 4.5M+ unique RL tasks 🚂 Works like magic with Tinker, Miles, Slime Link and thread below.
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João Gabriel Lima | AI Tech Leader @ Integritas retweetledi
Hasan Toor
Hasan Toor@hasantoxr·
Best GitHub repos for Claude code that will 10x your next project: 1. Superpowers github.com/obra/superpowe… 2. Awesome Claude Code github.com/hesreallyhim/a… 3. GSD (Get Shit Done) github.com/gsd-build/get-… 4. Claude Mem github.com/thedotmack/cla… 5. UI UX Pro Max github.com/nextlevelbuild… 6. n8n-MCP github.com/czlonkowski/n8… 7. Obsidian Skills github.com/kepano/obsidia… 8. LightRAG github.com/hkuds/lightrag 9. Everything Claude Code github.com/affaan-m/every…
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João Gabriel Lima | AI Tech Leader @ Integritas retweetledi
Ksenia_TuringPost
Ksenia_TuringPost@TheTuringPost·
16 Reinforcement Learning approaches you should know about (classic + modern) ▪️ RLHF – RL from Human Feedback ▪️ RLAIF – RL from AI Feedback ▪️ RLVR – RL with Verifiable Rewards ▪️ RLCF – RL from Community Feedback (2 different variants) ▪️ RLCF – RL from Checklist Feedback ▪️ CM2 ▪️ Critique-RL ▪️ CRL – Critique RL ▪️ ICRL – In-Context RL ▪️ RLBF – RL with Backtracking Feedback ▪️ TriPlay-RL ▪️ SPIRAL ▪️ Co-rewarding ▪️ RESTRAIN ▪️ PRL – Process Reward Learning ▪️ RLSF – RL from Self-Feedback Save this list and check it out for links and explanations: turingpost.com/p/rlapproaches
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João Gabriel Lima | AI Tech Leader @ Integritas retweetledi
Somi AI
Somi AI@somi_ai·
@bindureddy more of a win for cursor's training pipeline than for open source. if most of the value comes from the proprietary RL layer on top, the base model provider kinda stops mattering
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João Gabriel Lima | AI Tech Leader @ Integritas retweetledi
Bindu Reddy
Bindu Reddy@bindureddy·
A huge win for Kimi 2.5 Cursor made a fine tune using their model and is claiming that it’s as good as Opus 4.6! If true, the next version of Kimi - Kimi 3.0 should beat Opus 4.6 comfortably Has open source decimated closed source? 😂😂
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João Gabriel Lima | AI Tech Leader @ Integritas retweetledi
Muhammad Rizwan Munawar
Muhammad Rizwan Munawar@muhammdrizwanmr·
Pothole detection on the road in real time using @ultralytics YOLO26! 🕳️ Manual road inspections are slow, costly, and hard to scale. With object detection, potholes can be identified directly from street-level images or video feeds, enabling faster and more consistent road condition monitoring. How I built this demo: ✅ Trained a segmentation model on a custom dataset. ✅ Generated mask contours for each pothole. ✅ Leveraged the onnx-exported model for faster processing. #Pothole #RoadDamage #AI
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João Gabriel Lima | AI Tech Leader @ Integritas retweetledi
Lin Qiao
Lin Qiao@lqiao·
🔥 Cursor Composer2 launched on Fireworks 🔥 This time it's not just inference but also RL powered by @FireworksAI_HQ. So much hard work and sleepless nights to get this gift out. Congrats @cursor_ai team on launching this SOTA model beating Opus 4.6 on terminal bench! 🚀 x.com/cursor_ai/stat…
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João Gabriel Lima | AI Tech Leader @ Integritas retweetledi
Pau Labarta Bajo
Pau Labarta Bajo@paulabartabajo_·
60-minute deep dive on how to fine-tune a Small Language Model for browser control Enjoy ↓ youtube.com/watch?v=gKQ08y…
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João Gabriel Lima | AI Tech Leader @ Integritas retweetledi
Chao Huang
Chao Huang@huang_chao4969·
Introducing ClawTeam: Agent Swarm Intelligence 🚀 ( github.com/HKUDS/ClawTeam ). The Evolution of AI Agents: Solo 🤖 → Swarm 🦞🤖🤖🤖 AI assistants like OpenClaw and nanobot have made it incredibly easy for everyone to have their own personal agents. They're everywhere now — coding, writing, analyzing. But here's the thing: they're all working in isolation. It's like having a bunch of brilliant interns who never talk to each other. We think it's time for the next leap. ClawTeam transforms those isolated agents into collaborative swarms that actually think and work as a team. No more babysitting multiple agents or juggling contexts. Just tell the leader agent your goal — it spawns the right specialists, divides work intelligently, and orchestrates everything until completion. It's like upgrading from solo freelancers to a synchronized dev team that never sleeps. ⚡ From Hours to Minutes, From Complex to Simple Here's where it gets interesting: whether you're running ML experiments across 8 GPUs, building full-stack applications, or analyzing market data, ClawTeam turns complex multi-day projects into single-command operations. We're not just making agents faster — we're unlocking collective intelligence to tackle something big. #ClawTeam #OpenClaw #nanobot #AIAgents
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João Gabriel Lima | AI Tech Leader @ Integritas retweetledi
SkalskiP
SkalskiP@skalskip92·
smart parking demo - RF-DETR - license plate detection - OC-SORT - multi-object tracking - GLM-OCR - reading license plates on Monday I showed you trackers, yesterday GLM-OCR, today I'm putting everything together
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João Gabriel Lima | AI Tech Leader @ Integritas retweetledi
Unsloth AI
Unsloth AI@UnslothAI·
Introducing Unsloth Studio ✨ A new open-source web UI to train and run LLMs. • Run models locally on Mac, Windows, Linux • Train 500+ models 2x faster with 70% less VRAM • Supports GGUF, vision, audio, embedding models • Auto-create datasets from PDF, CSV, DOCX • Self-healing tool calling and code execution • Compare models side by side + export to GGUF GitHub: github.com/unslothai/unsl… Blog and Guide: unsloth.ai/docs/new/studio Available now on Hugging Face, NVIDIA, Docker and Colab.
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