GixCloud

@TencentAI_News hehe, looks interesting

A quick look at how WorkBuddy handles food runs in China🍔 We connected it to Weixin Pay's AI AgentPay Card and teamed up with Meituan (powering this mainland-exclusive ecosystem play): > say "what's good to eat nearby?", WorkBuddy ranks local group-buy deals by your location and taste, ranked by value (not ads) > pick one, the AI orders and starts the payment > you confirm on your phone, it charges from the AI AgentPay Card, you redeem in store 🍽️The agent does the legwork of finding the best deal, but every charge needs your tap, spending cap included feels less like ordering through an app, more like having someone who actually wants you to save money

@googlecloud This could save product teams a lot of time

Build faster with customers in the loop. Synthesize user feedback and market data instantly to draft product requirements with the Gemini Enterprise app → goo.gle/4erNrtW

@alibaba_cloud love it🦾

Meet Qwen3.7-Plus, built for multimodal agent execution across GUI interaction, tool use, and coding. From visual input to code and real task execution, it’s designed for long-running, real-world agent workflows. Try it today on Alibaba Cloud with a limited-time 20% discount. 🔗 : int.alibabacloud.com/m/1000414123/

@NVIDIAHealth This is really cool. Feels like something a lot of research teams will want to try!

Science is entering a new era - one where AI agents can do scientific work. 🧬 Today NVIDIA is launching the BioNeMo Agent Toolkit - an open, agent-ready toolkit that gives any AI agent callable tools for protein structure prediction, molecular docking, generative chemistry, genomic analysis, and more. (1/2)

New post on our Facebook: a real case of cutting AI costs as usage grows 🦾 facebook.com/share/p/1BUVHC…

Definitely worth trying!

Would you rather reduce AI unit cost or make AI capacity more predictable? 🤔 Most scaling teams eventually need both.

@GoogleAI @NotebookLM time to test this new audio model💪

Here’s what launched this week: — Gemini 3.5 Live Translate our latest audio model for live speech-to-speech translation — @NotebookLM got a major upgrade including agentic capabilities in chat, more advanced reasoning, and a suite of new output formats — Project Genie from @GoogleLabs is now available to Google AI Ultra 5x subscribers globally — Notebooks in @GeminiApp are now available in the European Economic Area, United Kingdom, and Switzerland — DiffusionGemma, our newest experimental open @googlegemma model that explores text diffusion, an exceptionally fast approach to text generation

@AIatMeta collab of the year !

Today we’re announcing an agreement with Amazon Web Services to bring tens of millions of AWS Graviton cores to our compute portfolio. This partnership marks an expansion of our diversified AI infrastructure and will help scale systems behind Meta AI and agentic experiences that serve billions of people. Learn more: go.meta.me/2bc5c5

@alibaba_cloud looks impressive !

Alibaba has upgraded HappyOyster 1.0, a real-time interactive model by Alibaba Token Hub (ATH) business group. With Adventure and Directing Modes, the enhanced model now offers richer environmental interactions, expanded player controls, and rewindable storylines. These innovations pave the way for opportunities in gaming, interactive dramas, livestreaming, and cultural tourism. Discover how HappyOyster 1.0 is transforming immersive experiences: alizila.com/alibaba-upgrad… #AlibabaAI #Innovation

Code is the right action interface for spatial reasoning agents. New from NVIDIA Research: SpatialClaw, a training-free agent that uses code as its action interface for complex visual tasks. Instead of calling a fixed set of pre-defined tools, the agent writes Python inside a persistent kernel, so it can compose perception modules, inspect intermediate results, and revise its strategy across steps. Perception outputs become ordinary variables it can reuse and combine with libraries like NumPy and SciPy. With no benchmark-specific or model-specific tuning, it beats a recent prior agent by 11.2 points across 20 benchmarks and holds up consistently across six different model backbones. You can check out SpatialClaw here: nvda.ws/4esHxr9

@NVIDIAAI sounds interesting tho :)

it's just WOW!

AI capacity planning is becoming less about “can we run it?” and more about “can we afford to scale it?” How is your company approaching this shift?🤔

What gets hardest to control as AI products scale?

Very relevant. Once companies start using more agents, having one place to see and manage them becomes a must❗️

Before adding more budget to AI, check what is quietly eating it: repeated calls, oversized prompts, and weak caching. Sometimes the cheapest optimization is not a cheaper model — it is a cleaner workflow.

A model can be cheap per call and still expensive in production if latency, retries and context size are ignored 🚫

GIX helps AI-heavy teams look beyond token price: inference, quotas, retries, model choice, latency and predictable billing all shape AI economics 🤖