THE BIGGER PICTURE
A five-layer kind of world. A map for understanding what connects a new model to a chip, a data center, and the power grid.
05 Applications 04 Models 03 Infrastructure 02 Chips 01 Energy LAYER 04 Models Learned patterns that turn inputs into predictions.
Language · vision · biology · multimodal
A framework from Jensen Huang, NVIDIA, March 10, 2026. Useful context from an industry participant, not a universal scientific taxonomy. Read the original explanation
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Anthropic expands frontier-risk testing beyond cyber and biology Anthropic’s Frontier Red Team introduced evaluations for tactical geolocation and conventional-weapons tasks, including drone control under simulated feedback. The company says frontier models completed some work historically limited to scarce experts and uses the results to justify stronger misuse controls. These are Anthropic-designed risk evaluations, not evidence of real-world weapon performance.
GPT-Live-1 can listen while it speaks OpenAI launched GPT-Live-1 as a full-duplex voice API that can listen and speak simultaneously, handle interruptions, and delegate deeper reasoning or tool calls to a backend model. It adds telephony and configurable voices. Performance numbers and customer outcomes on the page are OpenAI and partner-reported, not independent comparisons.
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning DeepSeek-R1 investigates reinforcement learning for reasoning and distillation into smaller models.
DeepSeek-V3 Technical Report DeepSeek-V3 describes a mixture-of-experts language model and techniques for efficient large-scale training.
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters This paper examines scaling inference-time computation, exploring how additional test-time resources can improve language-model problem solving.
Mamba: Linear-Time Sequence Modeling with Selective State Spaces Mamba investigates selective state-space models as an alternative approach to sequence modeling with efficient scaling.
Open X-Embodiment: Robotic Learning Datasets and RT-X Models Open X-Embodiment combines robotic data across embodiments to study generalization and reusable robot policies.
Toolformer: Language Models Can Teach Themselves to Use Tools Toolformer explores teaching language models to invoke external tools with a self-supervised training approach.
The Artificial Post A little wiser, a little at a time.