Advocates doing initial experiments and outline generation on local hardware, then switching to cloud services (burning tokens) for heavy output and f...Show more

Observes that companies like Google view AI compute tokens as a form of ad inventory and will flood the market because their primary business is monet...Show more

Preference for running audio and agent workloads entirely locally for privacy, latency, and control, rather than relying on external cloud APIs.

Argues it’s more cost-effective and flexible to rent H100 GPUs on platforms like SF Compute, paying ~$45/hr, than to buy expensive DGX hardware.

Focusing on low-energy, high-importance data plus quantization (e.g., 4-bit weights on a 70B-parameter model) enables running large language models of...Show more

Modern CV tools and platforms have democratized custom detection solutions, making it affordable for developers to build targeted applications (e.g., ...Show more

World model architectures are often assumed to be limited to robotics or purely video-based tasks, but they can be applied to real-world domains like ...Show more

Unlike traditional chain-of-thought reasoning tokens, advanced models propose an internal reflection step that functions more like a human mental simu...Show more

Moving from predicting tokens or pixels to true reasoning—where a model “thinks” through alternatives before answering—represents a shift toward human...Show more

We vastly underappreciate how much ambient audio and visual context contribute to human cognition; world models could benefit from ingesting environme...Show more

Whether text LLMs, image diffusion models, or video predictors, every model’s core objective is to forecast the next token, pixel arrangement, or fram...Show more

For tasks with high dimensionality (e.g., climate modeling or real-time AR), pure brute-force compute is impractical. Energy-based frameworks that foc...Show more

By encoding objects, motion, and scene context into high-level latent spaces, models can reason and predict in a more human-like fashion, abstracting ...Show more

Yann LeCun argues that true AGI requires moving beyond next-token language prediction. Instead, models must learn joint embeddings of multimodal conce...Show more

Humans process low-bandwidth sensory inputs over time and build world models enhanced by reinforcement and emotion. AI must emulate this continuous, c...Show more

OpenAI’s donation of a Markdown file is seen as a token gesture compared to full-blown codebases.

Public MCP servers are numerous but poorly maintained, requiring extensive cleanup to find reliable instances.

Ultimately, all interfaces will run agentic logic in the background—even if they present as simple APIs.

Deep-research capabilities have historically been offered as product experiences rather than raw API endpoints.

There’s confusion around what constitutes an “agentic tool” versus an LLM endpoint—definitions remain fluid.