You can now train FLUX Kontext loras on Replicate. https://
replicate.com/replicate/fast
-flux-kontext-trainer/train
… – A 1,000 step training takes about 4 minutes
– Train with image pairs, a start and end image
– Write a short prompt instruction that takes you from the start to the end
– Use about 10 image pairs
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Train FLUX Kontext LoRAs on Replicate in Minutes
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Kimi K2: Agentic AI for coding and reasoning
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Unlike most LLMs, Kimi K2 was trained for agentic behavior: Calls APIs Executes chains Understands tools Writes complex apps Supports structured thinking This isn't a chatbot. It's a full-on coding + reasoning machine.
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Kimi K2: Open AI Rivaling Claude 4
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Kimi K2 specs are wild: → 1T total / 32B active MoE
→ SOTA on SWE Bench, Tau2, AceBench
→ Strong in code + multi-step tasks
→ $0.15–2.50 per million tokens via API
→ Open weights + GitHub + playground It rivals Claude 4 in coding but it's free + open. -
Kimi K2: Open-Source LLM Dominates Code & Agents
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Kimi k2 is a terrifyingly good open-source model. Its really good at code, agents, and real-world tasks. It’s open, fast, and beats most LLMs in key benchmarks. I built 3 working apps with it in a day:
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ChatGPT Agent for Excel and PowerPoint Automation
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ChatGPT agent for working with Excel, Powerpoint, etc.:
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Build Real-World Intelligent Agents with NVIDIA NeMo Toolkit
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On August 1st and 22nd, learn how to build real-world intelligent agents using the NVIDIA NeMo Agent toolkit. Perfect for developers, data scientists, and ML engineers with basic Python knowledge. This session will walk you through building and deploying #AIAgents using simple
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AtCoder Heuristics World Finals: Global Optimization Programming Competition
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The AtCoder Heuristics World Finals is a global programming competition focused on optimization problems: tasks where you don't just solve a problem but actively search for the best possible solution. It tests creativity, strategy, and persistence under strict time and resource
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Ailker releases impressive Kontext LoRAs for AI models
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Dang, @ailker is on fire . So many fantastic kontext loras.
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Reducing Page Weight: Ditching Unoptimized Speaker Photos
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In a beautiful cautionary tale about the dangers of vibe-coding on a phone, it turns out the page was 130MB because it included unoptimized photos of all 170+ speakers! I've ditched those now, reducing the page weight to a much less horrifying 93.58KB
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Bad dataset quality impacts AI model performance outcomes
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The dataset I gave the AI was bad, it worked with that data.