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🔍 ML Language
Pattern Matching, Type Inference, Functional Programming, OCaml
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80293
posts in
575.6
ms
Discovering Interpretable Algorithms by
Decompiling
Transformers to
RASP
arxiv.org
·
10h
🪜
Recursive Descent
Language
Modeling
and Understanding Through
Paraphrase
Generation and Detection
arxiv.org
·
10h
📊
LR Parsing
Redefining
Go
Functions
pboyd.io
·
1h
·
Discuss:
Lobsters
,
Hacker News
🐹
Minimal Go
25W06
. Learning a language with the machine
z1nz0l1n.com
·
2d
🌱
Minimal ML
Towards a Standard for
JSON
Document
Databases
muratbuffalo.blogspot.com
·
16h
·
Discuss:
Blogger
📊
Query Optimizers
Show HN: Deterministic
linguistic
enrichment
pipeline for Node.js
npmjs.com
·
4h
·
Discuss:
Hacker News
🔤
Language Tokenizers
Python's Dynamic
Typing
Problem
whileforloop.com
·
3h
·
Discuss:
r/programming
🌊
Gradual Typing
Differential
Logic
• 4
inquiryintoinquiry.com
·
2d
∫
Mathematical DSLs
Show HN:
AetherLang
– A
DSL
for building AI workflows with visual debugging
github.com
·
14h
·
Discuss:
Hacker News
✨
Gleam
Colab
marketplace.visualstudio.com
·
1h
🔍
Comby
Domain
Knowledge Is the New
Syntax
blog.melashri.net
·
1d
·
Discuss:
Hacker News
🎮
Language Ergonomics
A
lightweight
OpenClaw-inspired
AI assistant in Go
reddit.com
·
8h
·
Discuss:
r/golang
🐹
Go Internals
The
Prospero
Challenge
mattkeeter.com
·
1d
🔬
Nanopasses
An
attempt
at a
First-Proof
AI challenge
abhvio.us
·
2d
·
Discuss:
Hacker News
λ
Lambda Calculus
The
Illusion
of
AGI
, or What Language Models Can Do Without Thought
techpolicy.press
·
1d
🎯
Finite Automata
5 LLM
Workflow
Patterns for Building Scalable AI Applications: A Complete Guide (With
Examples
)
pub.towardsai.net
·
10h
🎭
Program Synthesis
Revisiting
Regular
Types
abseil.io
·
2d
🚀
Hindley-Milner+
Building a Semantic Search Engine with
Hugging
Face Transformers and
MongoDB
Atlas Vector Search
dev.to
·
26m
·
Discuss:
DEV
🔍
Search Algorithms
Import AI 444: LLM
societies
; Huawei makes kernels with AI;
ChipBench
importai.substack.com
·
1d
·
Discuss:
Substack
🪜
Recursive Descent
Some Open Problems in Probability that are Relevant to Applied Statistics (my talk this Wed
noon
at the Columbia statistics department student
seminar
)
statmodeling.stat.columbia.edu
·
1h
🔗
Category Theory
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