World models generate, reconstruct, and simulate any possible world. They understand how worlds appear, behave, and evolve so that we can render imagined worlds for creative users, simulate the real world in high fidelity, and help robots plan actions. At World Labs, we build these general purpose world models in pursuit of spatial intelligence.
Today we are introducing Atlas, our next-generation world model. Atlas is an omni model that we pretrained from scratch to natively operate on text, images, video, and 3D. It is a multimodal autoregressive diffusion transformer: all inputs are combined into a shared spatial context. Atlas uses that context to generate what comes next, staying consistent in 3D with everything it has seen and imagining what lies beyond it. — Read More
Recent Updates
The Pentagon now has its own version of ChatGPT and Grok
The Pentagon has launched versions of OpenAI’s ChatGPT and xAI’s Grok, giving 3 million civilian and military personnel access to generative AI tools that have been tailored to “warfighter needs.”
… These latest additions are part of the Pentagon’s broader effort to use AI tools to accelerate work and give the Department of Defense an edge without sacrificing security. They also highlight the absence of Anthropic’s Claude model and the Pentagon’s effort to work with other companies following its dispute with the frontier lab. — Read More
Who gets to decide? The CIO and the new architecture of enterprise authority
For most of my career, technology governance began with a familiar set of questions: Is the system secure? Is it resilient? Does it meet the architecture standard? Can we afford it? Those questions still matter. But they are no longer enough.
AI is moving rapidly from producing content and recommendations to initiating actions. It can route work, change code, approve exceptions, communicate with customers, trigger transactions and coordinate other systems. In that environment, the most important question may not be what the technology can do. It is who, or what, has the authority to do it. — Read More
AI token prices are hitting new record lows
A closely followed measure of artificial intelligence token prices touched fresh lows this week, the latest sign of deflating prices in an increasingly competitive landscape.
The LLM Token Expenditure Index, a key gauge of daily prices from intelligence firm Silicon Data, fell to 97 cents on Monday. That marked the index’s lowest reading since its creation late last year and has fallen by more than half from the high recorded earlier this summer.
….The recent drop is driven in part by the rise of open-source Chinese models like Moonshot’s Kimi K3 that can fetch lower prices than alternatives from leading frontier labs, according to a Tuesday post from Charles-Henry Monchau, investing chief at Syz Group. — Read More
The Five Horses of Bandwidth
Over the last two weeks, a series of events like Hot Chips have laid out the roadmap for the AI industry for the remainder of the decade.
And the conclusion is pretty straightforward: Bandwidth is king.
Investors love magic solutions, so here’s one: success in AI progress over the next five years at least will be proportional to how much bandwidth-pilled your bets are. Bandwidth constrains progress, and most hardware decisions today are moving toward increasing bandwidth. — Read More
When the Source Attacks Back: Prompt Injection Is Coming for OSINT
If you let an AI read untrusted internet content for you, you are no longer just investigating a source.
You are giving that source a chance to investigate you back.
We already know the open web lies. It lies through fake personas, recycled images, synthetic media, planted narratives, scraped junk, and dashboards that look smarter than the people using them.
Prompt injection is different.
It is not content trying to convince you.
It is content trying to tell your AI what to do. — Read More
On-Premise AI for the Newsroom: Evaluating Small Language Models for Investigative Document Search
Investigative journalists routinely confront large document collections. Large language models (LLMs) with retrieval-augmented generation (RAG) capabilities promise to accelerate the process of document discovery, but newsroom adoption remains limited due to hallucination risks, verification burden, and data privacy concerns. We present a journalist-centered approach to LLM-powered document search that prioritizes transparency and editorial control through a five-stage pipeline—corpus summarization, search planning, parallel thread execution, quality evaluation, and synthesis—using small, locally-deployable language models that preserve data security and maintain complete auditability through explicit citation chains. Evaluating three quantized models (Gemma 3 12B, Qwen 3 14B, and GPT-OSS 20B) on two corpora, we find substantial variation in reliability. All models achieved high citation validity and ran effectively on standard desktop hardware (e.g., 24 GB of memory), demonstrating feasibility for resource-constrained newsrooms. However, systematic challenges emerged, including error propagation through multi-stage synthesis and dramatic performance variation based on training data overlap with corpus content. These findings suggest that effective newsroom AI deployment requires careful model selection and system design, alongside human oversight for maintaining standards of accuracy and accountability. — Read More
Runway News: Introducing Solaris
Today, we’re sharing Solaris: the first model in a new family of AI systems we call Interface World Models. Solaris starts with a question: what happens when an operating system generates apps and websites as you use them?
Every operating system, from early terminals to Linux and macOS, has dictated what’s rendered on screen and what happens when a person or program acts on it. Applications get built on top, and stay fixed until someone pushes an update. Solaris instead renders that layer directly. It’s a real-time interactive model that generates the interface itself, frame by frame. Every frame is synthesized as you interact, allowing the interface to respond continuously to your actions. — Read More
Andrew Ng: The Biggest Opportunities in AI Aren’t Where You Think
Just Another Transformation
Have you ever seen any transformation working?
If you have, please share what made it successful because more people need to learn from it. Most transformations fail. And they fail for predictable reasons.
… Today, we hear about AI transformation. How does that differ from the transformations we’ve been experiencing for decades now?
If I had to bet, I’d say 90%+ of “AI Transformations” will create no different results from the poor digital transformations or failed agile ones. And the reason they will fail is the same as always: Lack of courage to address the foundations that enable any transformation to succeed. — Read More
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