Robots Can Now Do Chores! A key takeaway from this year’s WAIC: Embodied AI is moving beyond just "looking human." The real competition has shifted to "can they actually do the work?" Everyone’s trying out different real-world uses, and it's much more practical this time around. #WAIC2026# #EmbodiedAI# #Robotics# #FutureTech# #AIInRealLife# Risk Disclaimer: Investment involves risk, including possible loss of principal. Any forecasts, projections, or opinions contained herein are for reference only and are not guaranteed to occur. The information in this material reflects prevailing market conditions and our judgment as of the release date, which are subject to change without further notice.

Encountering future tech at the BRICS New Industrial Revolution Exhibition At the BRICS New Industrial Revolution Exhibition running from May 27 to 29 in Xiamen, the future feels less like a concept and more like something already in motion. Humanoid robots make tanghulu and play tic-tac-toe. Driverless electric vertical takeoff and landing (eVTOL) aircraft, unmanned gyroplanes, AI diagnosis tools and smart farming equipment are all on show. Together, they offer a close-up look at how cutting-edge technologies are moving from labs into real-world scenarios: from low-altitude tourism and weather modification to hospitals, farms and factories. The new industrial revolution is not just on display here. It is already taking off.

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If you love fine-tuning open-source models (like me), then listen. > Start with 1B, 2B, 4B, and 8B models. (Don't start with a 27B model or bigger at first.) > Use WebGPU providers. I use Google Colab Pro for any model smaller than 9B. A single A100 80GB costs around $0.60/hr, which is cheap. Enough for small models. > Don’t buy GPUs unless you fine-tune 7 to 10 models. You'll understand the nitty-gritty in the process. > Use Codex 5.5 × DeepSeek v4 Pro to create datasets. Codex to plan, DeepSeek v4 Pro to generate rows. > Use Unsloth's instruct models as a base from Hugging Face. Yes, there are others too, but Unsloth also provides fast fine-tuning notebooks. > Use Unsloth's fine-tuning notebooks as a reference. Paste them into Codex, and Codex will write a custom notebook with the configs you need. > Spend 1 day learning about: - SFT (supervised fine-tuning) - RL training (GRPO, DPO, PPO, etc.) - LoRA / QLoRA training - Quantization and types - Local inference engines (llama.cpp) - KV cache and prompt cache > Just get started. Claude, Codex, and ChatGPT can design a step-by-step plan for how you can fine-tune your first AI model. Future tech is moving toward small 5B to 15B ELMs (Expert Language Models) rather than general 1T LLMs. So fine-tuning is an important skill that anyone can acquire today. Tune models, test them, use them. Then fine-tune for companies and make a career out of it. (Companies pay $50k+ to fine-tune models on their data so they can get personalized AI models.) Shoot your questions below. I'll be sharing in-depth raw findings about this topic in the coming days.

【Notice of Kiki Asakura Ending Her Entertainment Career】 #KikiAsakura# #IdolJourney# #PetGroomer# #FarewellToShowbiz# #FansSupport# #10YearsOfYouth# #NewBeginnings# #ForeverGrateful# #FutureChallenges# #AnimalLover#