A Better Way to Deploy Voice AI at Scale

Most Voice AI deployments fail for the same reasons: unclear logic, limited testing tools, unpredictable latency, and no systematic way to improve after launch.

The BELL Framework solves this with a repeatable lifecycle — Build, Evaluate, Launch, Learn — built for enterprise-grade call environments.

See how leading teams are using BELL to deploy faster and operate with confidence.

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Today:

• Google Calls SIMA 2 a “Significant Step Toward AGI”

• OpenAI Tests Group Chats in ChatGPT for Shared AI Conversations

• Claude Outperforms GPT-5 in New Political Bias Test

• Leaked Docs Reveal OpenAI Paid Microsoft $866M in 2025

• Meta to Rate Employees on AI Use Starting in 2026

• Google to Invest $40B in Texas AI Data Centers by 2027

SIMA 2 is a "significant step towards AGI" says Google

Google DeepMind’s SIMA 2 is a major leap in game-playing AI. Unlike older bots, it uses a keyboard, mouse, and screen just like humans. Built on the Gemini model, SIMA 2 can understand language, reason, and improve over time without access to game code. It learns skills across many games and can apply them in new ones, including AI-generated worlds from Genie 3. 

Eventually, this digital brain could control real-world robots by treating reality like just another game. SIMA 2 marks real progress toward general intelligence, showing how AI can teach itself through trial, error, and its own experience.

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OpenAI Tests Group Chats in ChatGPT for Shared AI Conversations

OpenAI is testing group chats in ChatGPT, where several people and the AI can talk together in one space. It helps with planning, schoolwork, and projects, while keeping private chats and memories separate, plus giving clear controls for invites, safety, and notifications for every user.

KEY POINTS

• New group chats let many people and ChatGPT plan trips, dinners, or projects together in one shared conversation.

• Privacy is protected: group chats are separate from private chats, memory is not shared, and you can see, leave, or remove members anytime.

• ChatGPT now behaves more “socially” in groups, choosing when to reply, reacting with emojis, and following custom rules for tone and role.

Why it matters
This change turns ChatGPT from a one-on-one helper into a shared space for teams, friends, and families. It can cut down on long message threads, help people agree faster, and keep everyone on the same page—while still giving strong control over privacy and safety.

Claude Outperforms GPT-5 in New Political Bias Test

Anthropic tested Claude’s fairness in political discussions using a new automated method. Claude Sonnet 4.5 showed more balanced responses than GPT-5 and Llama 4, and similar to Grok 4 and Gemini 2.5. The open-source method aims to help standardize political bias measurement in AI.

KEY POINTS

• New Bias Test: Anthropic developed an automated method (“Paired Prompts”) to test political even-handedness across thousands of prompts and viewpoints, and made it open-source.

• Claude’s Performance: Claude Sonnet 4.5 and Opus 4.1 showed strong neutrality, with higher even-handedness scores than GPT-5 and Llama 4, and near-equal to Grok 4 and Gemini 2.5.

• Training & Ethics: Claude is trained not to push political views, avoids partisan language, and is shaped by character traits that prioritize objectivity, respect, and user independence.

Why it matters

As people rely more on AI for news, decisions, and conversations, it's important that these tools don’t favor one political view over another. Claude’s fairness work helps build trust by treating different beliefs with respect and care. Sharing the method publicly encourages industry-wide improvement.

Leaked Docs Reveal OpenAI Paid Microsoft $866M in 2025

Leaked documents show OpenAI paid Microsoft nearly $866M in 2025 and $494M in 2024 as part of a 20% revenue-sharing deal. Microsoft also shares revenue with OpenAI via Bing and Azure. Despite skyrocketing revenue, OpenAI’s AI model operating costs may still exceed earnings.

KEY POINTS

• Mutual Revenue Sharing: OpenAI pays Microsoft ~20% of its revenue, while Microsoft shares a portion of its Bing and Azure OpenAI profits back with OpenAI.

• Skyrocketing Revenue & Spend: OpenAI earned an estimated $4.3B in early 2025 but spent $8.65B on inference alone—indicating high burn rates despite growth.

• Compute Costs & Cloud Dependence: OpenAI relies heavily on Microsoft Azure for compute but is now diversifying to AWS, Google Cloud, Oracle, and CoreWeave.

Why it matters

This leak offers rare insight into OpenAI’s business model, showing it may still be losing money despite massive revenue. It highlights how expensive it is to run AI at scale—and raises bigger questions about long-term sustainability, especially for other AI startups chasing similar growth.

🧠RESEARCH

One Small Step in Latent, One Giant Leap for Pixels: Fast Latent Upscale Adapter for Your Diffusion Models

The Latent Upscaler Adapter (LUA) speeds up image generation in diffusion models by enhancing resolution before decoding, instead of after. It boosts quality without slowing performance, using a compact, plug-and-play design. LUA works across different models, avoids artifacts, and is nearly three times faster than traditional image upscaling methods.

PAN: A World Model for General, Interactable, and Long-Horizon World Simulation

PAN is a powerful AI model that simulates how the world changes over time based on actions and natural language. Using a language-based prediction system and a video generator, it creates realistic, interactive, and long-term video simulations. PAN enables intelligent planning, reasoning, and forecasting across many different environments and tasks.

UniVA: Universal Video Agent towards Open-Source Next-Generation Video Generalist

UniVA is an open-source video AI agent that unifies tasks like understanding, editing, segmenting, and generating videos. Using a planner-executor system with memory, it handles complex, multi-step video workflows interactively and efficiently. UniVA aims to enable next-generation, general-purpose video tools and includes a benchmark suite for agentic video tasks.

🛠️TOP TOOLS

Each listing includes a hands-on tutorial so you can get started right away, whether you’re a beginner or a pro.

AI Interview Bot – AI Mock Interview Practice & Question Generator - a lightweight interview‑prep tool that lets you practice with avatar‑led video questions

AI Jingle Generator – Create Jingles, DJ Drops & Podcast Intros - browser-based tool for instantly producing radio‑ready jingles

AI Library – Find AI Tools Fast - a curated, searchable catalog of AI tools and neural networks

📲SOCIAL MEDIA

🗞️MORE NEWS

• Meta will start rating employees based on how well they use AI to improve work results. Starting in 2026, AI-driven impact becomes a key performance measure, with rewards for those who drive meaningful outcomes.

• Google will invest $40 billion in three new data centers in Texas by 2027 to boost AI computing. Two sites will be in Haskell County, one in Armstrong, with one paired to a solar-battery energy plant.

• OpenAI has fixed ChatGPT’s overuse of em dashes. Users can now prevent them by updating custom instructions. The change gives writers more control and addresses complaints about the punctuation’s link to AI-written text.

• Mozilla is launching an “AI Window” in Firefox — a fully optional, user-controlled AI assistant to help with browsing. Staying true to its values, Mozilla emphasizes openness, privacy, and user choice over forced AI integration.

• Apple is accelerating plans for CEO Tim Cook’s succession, possibly as early as 2026. Hardware chief John Ternus is seen as the leading candidate, though no final decision has been made.

• Yann LeCun accused Anthropic of using fear over an AI-led cyberattack to push for strict regulations that would harm open-source models. He and Trump advisor David Sacks called it a tactic for regulatory capture.

• Google and UCLA introduced Supervised Reinforcement Learning (SRL), a new training method that helps smaller AI models handle complex reasoning. SRL breaks tasks into step-by-step actions, improving performance without increasing token use or cost.

• Google DeepMind’s chief, Demis Hassabis, prioritizes scientific discovery and long-term AI goals over short-term profits. Despite breakthroughs like AlphaFold and Gemini, some investors worry his idealistic vision slows commercial gains. Google remains confident in his leadership.