“Lot of interesting stuff about China vs US, paths to AGI, compute, marketing etc.”

“PC-class small language models (SLMs) improved accuracy by nearly 2x over 2024, dramatically closing the gap with frontier cloud-based large language models (LLMs).”

“The resulting acceptor layer achieves a striking Δn response time as short as 9 fs, approaching a single optical cycle, and is further tunable to sub-cycle timescales.”

“HY-MT1.5-1.8B demonstrates remarkable parameter efficiency, comprehensively outperforming significantly larger open-source baselines and mainstream commercial APIs.”

“LRH reduces Max/Avg load from 1.2785 to 1.0947 and achieves 60.05 Mkeys/s, about 6.8x faster than multi-probe consistent hashing with 8 probes (8.80 Mkeys/s) while approaching its balance (Max/Avg 1.0697).”

“The method achieves up to 99.6% safety rate--exceeding full fine-tuning by 7.4 percentage points and approaching RLHF-based methods--while updating only 0.19-0.24% of parameters.”

“AI agents are approaching a level where they can handle 'memory, calculation, and prediction.'”

“The optimal code capacity of the checkerboard code is $p_{th} \simeq 0.108(2)$, the highest among known three-dimensional codes.”

“WeDLM preserves the quality of strong AR backbones while delivering substantial speedups, approaching 3x on challenging reasoning benchmarks and up to 10x in low-entropy generation regimes; critically, our comparisons are against AR baselines served by vLLM under matched deployment settings, demonstrating that diffusion-style decoding can outperform an optimized AR engine in practice.”

“NOAM significantly improves prediction accuracy and approaches human-level results, highlighting best practices for deploying cognitively capable agents in domestic environments.”

“Which return gift has the best cost performance? It's difficult to compare because the donation amount and quantity are different even for the same crab. I don't have time to research the large number of return gifts even though the end of the year is approaching.”

“The paper examines learning dynamics.”

“"AIの棒読み感」はもはや過去の話。ここまで自然な会話が作れるようになりました。”

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“We’re working to prevent abuse, provide transparency on AI-generated content, and improve access to accurate voting information.”

“The core idea is to use some pre-existing classifier \(F_{pl}\) (referred to as the “pseudo-labeler”) to make predictions (referred to as “pseudo-labels”) on a large unlabeled dataset, and then retrain a new model with the pseudo-labels.”

“We talk through the goals of the project, the primary problem domain, and how the results of AutoNLP compare with those from hand-crafted models.”

“We explore the target user for the MLPerf benchmarks, the need for benchmarks in the ethics, bias, fairness space, and how they’re approaching this through the "People’s Speech" datasets.”

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