Basic Input/Output System
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
Ahoy, DECmate II the little PDP-8 that could
Now, that's a lot of word processing. But under the hood it's still at least PDP-8 adjacent, even considering its oddities and incompatibilities, and you can make it do many of the things a full-size Eight can. We'll take this basic unit, convert the floppy drives to solid state, tap the video output, and put it through its paces.
Structural Decoupling: A Scaffold-Flow Theory of Generalization and Alignment
arXiv:2506.20699v2 Announce Type: replace Abstract: Learning in non-stationary and multi-context environments requires more than ordinary within-task generalization. A system must also discover which contexts exist, route inputs to the correct context, preserve old contexts, and revise the context library when the environment changes. This paper presents Structural Learning Theory (StrLT) as a framework of filling this missing structural gap.
Ask HN: What are tools you have made for yourself since the advent of AI?
I've made a number of ceramic molds for slumping fused glass into bowls. As well as wooden templates for ceramic mugs. I've devised a few carrying tools to move glass frit paintings from my studio down to my barn where the kilns sit without spilling the glass.
Anthropic/OpenAI may be spending more than $1000 for every $100 you pay them
For reasons that will remain hidden, we resume writing about Generative AI/LLM after a hiatus of 15 months (that one from October 2025, and the one from June 2025, don’t really count as serious pieces). Today, the first of two articles about “coding with Large ‘Language’ Models”, as coding with LLMs is positioned as the ‘killer app‘ for LLMs. We interrupt this program for a short digression on Anthropic’s recently released blog post When AI builds itself.
Wall Street needs a crash course in the token economy ahead of AI IPOs. SpaceX offers a preview
When OpenAI and Anthropic eventually exit the confidential IPO filing phase and make their prospectuses public, investors are going to be inundated with references to a term that remains unfamiliar to many on Wall Street: tokens. They're the new currency in artificial intelligence. They're how the big model companies get paid.
Whole-genome duplication shaped cell-type evolution in the vertebrate brain
Abstract The complex brains of vertebrates have more cell types than those of their closest relatives. Whole-genome duplications (WGDs) occurred during early vertebrate evolution1, but it is unclear whether the duplicated genes (ohnologues) facilitated cell-type evolution. Here using brain single-cell transcriptomes from five chordates—human2, mouse3, lizard4, lamprey5 and amphioxus—we report that many cell-type families with conserved core transcription factors in vertebrates do not show...
Human-Like Neural Nets by Catapulting
Human-like Neural Nets by Catapulting Speculative proposal to create artificial neural nets with human-like performance by high-learning-rate/regularization training of overparameterized NNs to trigger catapulting/grokking. Over-parameterization as a route to true generalization would resolve many outstanding mysteries of artificial versus natural intelligence. There are many mysteries about deep learning and human intelligence, but we could describe the biggest anomaly this way: why are...
Port React Compiler to Rust
[compiler] Port React Compiler to Rust#36173 This is an experimental, work-in-progress port of React Compiler to Rust. Key points: - Work-in-progress - we are sharing early, prior to testing internally at Meta, to get feedback from partners in parallel with continued development.
Deep learning four decades of human migration
Abstract Human migration is a fundamental driver of global demographic change, shaping population structure, labour markets and social policy across countries1,2,3. Although long-term migration patterns are often linked to economic development4, they can shift rapidly in response to shocks such as conflict, environmental crises and political change5. Despite its importance, migration remains difficult to measure consistently: existing data are sparse, concentrated in high-income settings and...
A thalamus–brainstem attractor network drives history-biased decisions
Abstract Natural environments often change gradually, making it adaptive to bias decisions on the basis of the recent past — a phenomenon known as serial dependence1,2,3. Large-scale recordings during behaviour have identified that serial dependence is a common motif for decision-making, with neural representations of past experiences found throughout the brain4,5,6,7,8,9,10,11. However, it remains unclear whether this bias arises from dedicated neural circuits with history-specific...