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Machine Learning

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05:34
2026-10-05
dev.to
machine-learning

I Built an AI Assistant for My Dad’s Wholesale Business

A developer built Collection Radar, a local AI tool that ingests a wholesale business's existing Excel invoice spreadsheet and converts it into a prioritized collections list. The tool uses TabPFN, a tabular-data model, …

12:04
2026-10-04
graphite.io
large-language-models

AI Tells: Opus 5.5 Update

Anthropic's Claude Opus 5.5, released September 22, 2026, shows a 19% lower word-distribution divergence from human writing than Opus 5, while OpenAI's GPT-6 Astra's divergence is 8% higher than GPT-5.6 Sol's, according …

02:48
2026-10-04
arxiv.org
machine-learning

Decoding Looped Transformers Better for Almost Free

Researchers posted a paper on arXiv on 1 October 2026 introducing LoopCD, a training-free contrastive decoding framework for looped Transformers that contrasts the final prediction with an earlier recurrent pass. LoopCD-…

21:47
2026-10-03
varsity.co.uk
ai-policy

The University of Cambridge opposes Turnitin AI training plans

The University of Cambridge became the first university to refuse to sign Turnitin's new licence agreement in July 2026, according to the Cambridge Students' Union, after the proposed Terms of Use indicated student work …

20:03
2026-10-03
developer.arm.com
developer-tools

What is new in LLVM 23?

LLVM 23.1.0 was released on August 26, 2026, with almost 1300 patches contributed by Arm teams across architecture support, libraries, tools, performance and ML workloads. The release adds support for the Arm AGI CPU, Ar…

15:52
2026-10-03
twitter.com
ai-agents

What we learned running an agentic hackathon with 30k+ hackers

HackerRank's fourth Orchestrate hackathon, which concluded September 12, drew 35,700 registrations and 3,062 participants, up from 12,871 registrations and 1,349 participants in the first May edition. HackerRank reported…

04:00
2026-10-03
arxiv.org
machine-learning

Uncertainty-Aware Learning from Multi-Expert Interval Targets

A new arXiv paper (2610.00102v1) proposes an uncertainty-aware learning method that preserves individual expert intervals instead of collapsing them to a consensus, separating within-label imprecision from between-expert…

21:38
2026-10-02
justine.lol
large-language-models

LLaMA Now Goes Faster on CPUs

Justine Tunney wrote 84 new matrix multiplication kernels for llamafile that make prompt evaluation 30% to 500% faster than llama.cpp on CPU with F16 and Q8_0 weights, according to benchmarks published March 31, 2024. On…

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