AGI Advance: Weekly AI & AGI Insights (Nov 25, 2025)

This week, we explored a foundational shift: as agents and models become the new computing infrastructure, enterprise‑scale intelligence will mostly depend on shared AI memory systems rather than isolated models or silos. These memory systems don’t just store data; they act like living systems, preserving institutional knowledge across model updates and agent resets.

Here’s what we’re seeing:

• Models evolve; memory persists: While model architectures change every 6–12 months, the underlying data such as meeting transcripts, user profiles, and process workflows represents a longer‑term asset for the enterprise.
• Memory systems must support multiple agents and models: Unlike closed RAG pipelines or model‑tied memories, real enterprise memory should be owned by the user and usable across diverse agents and platforms.
• Retrieval efficiency is key: With terabytes of data, the challenge is selecting the right few hundred tokens of context for a query, not dumping thousands of irrelevant tokens and degrading accuracy.

In the era of AI agents, the true value isn’t what they compute, it’s what they remember.

🗣️ Jonathan Siddharth, Founder & CEO:

“Models are evolving in three dimensions: depth (reasoning, STEM), breadth (multimodality, multilinguality), and autonomy (tool use, agents).“

To push them forward, you need interdisciplinary teams generating deeply targeted data: a physicist to break the model, an engineer to build a simulator, a data scientist to verify. In the last episode of Decoding AI, Jonathan shared how Turing evolved from a global developer platform into a research accelerator, powering smarter models with smarter data, from interdisciplinary teams working on RL environments to post-training pipelines built for ASI.”

→ Watch the full conversation 

• Introducing Nano Banana Pro
  Google DeepMind introduces Nano Banana Pro, its most advanced image generation and editing model, built on Gemini 3 Pro. It blends multimodal reasoning with real-world knowledge to create high-fidelity visuals, infographics, storyboards, and multilingual text, all rendered natively in images. Nano Banana Pro improves legibility of text, supports 14-image consistency, and enables studio-grade creative control (e.g., lighting, camera angles, aspect ratio, 3D realism).
• Verbalized Sampling: How To Mitigate Mode Collapse and Unlock LLM Diversity
  This paper introduces verbalized sampling, a simple prompting strategy where LLMs are asked to generate multiple responses, each with an explicit probability. Unlike temperature tuning or decoding tricks, this method directly prompts the model to surface diverse outputs by making the sampling process part of the task. Tested on creative generation (jokes, poems), data generation (synthetic QA), and reasoning (math), verbalized sampling recovers up to 66.8% of base model diversity lost through alignment, and increases response variety by 1.6–2.1× without retraining. Crucially, it preserves accuracy and safety, and scales best on stronger models. For labs building aligned models or synthetic data pipelines, this is a zero-cost, inference-time strategy to mitigate mode collapse without touching weights.
• Introducing Google Antigravity, a New Era in AI-Assisted Software Development
  Google launches Antigravity, a new agent-first development platform designed to operationalize Gemini 3’s agentic coding abilities. Unlike conventional AI-powered IDEs, Antigravity introduces autonomous agent orchestration across editors, browsers, and terminals, enabling background research, feature implementation, and UI testing in parallel. Its novel “Artifact”-based interface surfaces tangible outputs like walkthroughs, screenshots, and plans, allowing asynchronous validation and feedback. With embedded learning, agents build persistent knowledge from every task. Antigravity shifts the software dev stack toward a world where agents don’t just autocomplete; they self-direct, verify, and improve.

Turing will be at this major AI conference in the coming month—join us to discuss the future of AGI:

• NeurIPS 2025
  [Mexico City | Nov 30 – Dec 5]
  [San Diego Convention Center | Dec 2 – 7]
  The Neural Information Processing Systems Foundation is a non-profit that promotes research in AI and ML by organizing a leading annual conference focused on ethical, diverse, and interdisciplinary collaboration.

If you’re attending, reach out—we’d love to connect and exchange insights!

Turing is leading the charge in bridging AI research with real-world applications. Subscribe to AGI Advance for weekly insights into breakthroughs, research, and industry shifts that matter.

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