Recent submissions

Comment · 9 days ago
Gettier actually criticized justified true belief (JTB) as insufficient for knowledge and provided counter examples known as Gettier problems
Comment · 9 days ago
Comment · 13 days ago
Related to the Bouba/Kiki effect is the Molyneux problem: https://en.wikipedia.org/wiki/Molyneux%27s_problem

The experimental evidence there, though limited, suggested no innate connection between touch and sight.

Comment · 4 months ago
From a brief reading of what Fusion does: https://openrouter.ai/docs/guides/features/plugins/fusion

Looks like Fusion calls a bunch of models and then uses an LLM to synthesize the results, and pass to another model for final output.

Fugu looks like it's doing something different? Using an LLM earlier on in the flow as an orchestrator to decide which other LLMs to call. More coordinator than simply synthesizing results, and more "agentic".

It's interesting because it's all exposed behind a single OpenAI compatible endpoint (Responses API?) and so then presumably someone could use this for one of their single agents. Now you have agent-of-agents, nested in some sense. The token usage increases accordingly!

Comment · 7 months ago
Comment · 9 months ago

  The jury found that Ding stole trade secrets relating to the hardware infrastructure and software platforms that allow Google’s supercomputing data center to train and serve large AI models. The trade secrets contained detailed information about the architecture and functionality of Google’s custom Tensor Processing Unit chips and systems and Google’s Graphics Processing Unit systems, the software that allows the chips to communicate and execute tasks, and the software that orchestrates thousands of chips into a supercomputer capable of training and executing cutting-edge AI workloads. The trade secrets also pertained to Google’s custom-designed SmartNIC, a type of network interface card used to facilitate high speed communication within Google’s AI supercomputers and cloud networking products.
Comment · 9 months ago
Neat experiment that gives a mechanistic interpretation of temperature. I liked the reference to the "anomalous" tokens being near the centroid, and thus having very little "meaning" to the LLM.
Comment · 1 year ago
That paper doesn’t seem to be about security vulnerabilities in MiG but rather using it to improve workload efficiency
Comment · 1 year ago
Wonder why they haven’t gotten an in house pizzeria yet to reduce the signal on this side channel leak
Comment · 1 year ago
From the article it appears to be something they invented:

> Gemma 3n leverages a Google DeepMind innovation called Per-Layer Embeddings (PLE) that delivers a significant reduction in RAM usage.

Like you I’m also interested in the architectural details. We can speculate but we’ll probably need to wait for some sort of paper to get the details.

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