🚀 Featured Keynote Speaker & OCM Announcement | ICMLAI-2027

We are pleased to announce Dr. Jolanta Tancula from the University of Opole, Poland, as a Keynote Speaker and OCM at the ICMLAI-2027, taking place on May 24–25, 2027, in Berlin, Germany.

🌐 Website: https://artificialintelligence2027.pagesconferences.org/

#ICMLAI2027 #MachineLearning #ArtificialIntelligence #DataScience #CyberSecurity #ThreatDetection #VulnerabilityAssessment #AIResearch #MLResearch #KeynoteSpeaker #AcademicConference

Google deploys Gemini 3.5 Flash to Search, Spark, and enterprise as Pro delays to June. Meta cuts 8,000 roles while shifting 7,000 to AI work. Anthropic hires Andrej Karpathy for pretraining research. The infrastructure shift is underway—compute becoming the constraint, not capability.

#AI #LaborMarkets #MLResearch

https://www.implicator.ai/google-ships-agents-meta-cuts-people-anthropic-buys-brains/

Gemini 3.5 Flash; Meta 8K Layoffs; Karpathy to Anthropic

Google ships Gemini 3.5 Flash across Search and Spark; Meta starts 8,000 layoffs; Karpathy joins Anthropic's pretraining team.

Implicator.ai
Research shows adding more features to ML regression models can introduce hidden structural risks. Every additional feature creates dependencies on upstream data pipelines, and low-signal variables may appear important due to noise, leading to models that behave inconsistently when deployed. https://www.marktechpost.com/2026/03/08/beyond-accuracy-quantifying-the-production-fragility-caused-by-excessive-redundant-and-low-signal-features-in-regression/ #AIagent #AI #GenAI #MLResearch #MarkTechPost
Beyond Accuracy: Quantifying the Production Fragility Caused by Excessive, Redundant, and Low-Signal Features in Regression

Beyond Accuracy: Quantifying the Production Fragility Caused by Excessive, Redundant, and Low-Signal Features in Regression

MarkTechPost

Discover 7 practical scikit‑learn tricks that let you weave preprocessing pipelines directly into hyperparameter searches. Save time, avoid data leakage, and boost model reliability—all with clean, reusable code. Perfect for open‑source projects and reproducible research. Dive in to level up your ML workflow! #scikitlearn #pipeline #hyperparamtuning #mlresearch

🔗 https://aidailypost.com/news/7-scikit-learn-tricks-embed-preprocessing-pipelines-hyperparameter

Dự án WaveHelix đang thử nghiệm xây dựng "mô hình thế giới" không dùng gradient descent. Hệ thống dự đoán chuyển động (vd: bóng nảy) bằng cách chạy kịch bản ứng cử viên, chấm điểm & pha trộn mô hình chính. Sử dụng "rungs" (ô nhớ), "spirals" (định tuyến) & "curl" để khám phá. Một cách tiếp cận ML mới lạ!

#WaveHelix #MachineLearning #AI #NoGradientDescent #WorldModel #SideProject #MLResearch
#HọcMáy #TríTuệNhânTạo #MôHìnhThếGiới #DựÁnPhụ #NghiênCứuML

https://www.reddit.com/r/LocalLLaMA/comments/

Our new series explains how a language model is built from the ground up. Part 1 covers the tokenizer and reveals how vocabulary size, merge rules, and byte mapping influence every downstream component.

Start with Part 1 and stay with the series as each chapter is released. https://www.tag1.com/white-paper/part1-tokenization-building-an-llm-from-scratch-in-rust/

#OpenSource #FOSS #MachineLearning #MLResearch #DeepLearning #LLM

Part 1: Tokenization, Building an LLM From Scratch in Rust

Learn how to build a language model from scratch in Rust, starting with part 1 of 6: tokenization, BPE, and vocabulary trade-offs.

Tag1

Part 1 of our six part series on building a language model is now published. We begin with tokenization and show how text is converted into numerical sequences that the model can process.

Read Part 1 and follow the full series as we move from the tokenizer to tensors and training. https://www.tag1.com/white-paper/part1-tokenization-building-an-llm-from-scratch-in-rust/

#FOSS #MLResearch #MachineLearning #DeepLearning #NLP #LanguageModels

Part 1: Tokenization, Building an LLM From Scratch in Rust

Learn how to build a language model from scratch in Rust, starting with part 1 of 6: tokenization, BPE, and vocabulary trade-offs.

Tag1

European researchers report that poetic prompts can bypass safety guardrails in multiple LLMs, exposing gaps in classifier-based moderation.

A good reminder that safety systems must evolve alongside generative models - especially as adversarial creativity becomes easier to automate.

What direction should improvements take?

Source: https://www.wired.com/story/poems-can-trick-ai-into-helping-you-make-a-nuclear-weapon/

Follow us for more neutral and security-focused AI updates.

#AISafety #LLMSecurity #AdversarialML #CyberSecurity #MLResearch #TechNadu

#Reproducibility #OpenScience #ComputationalSocialScience #WebData #DigitalBehavior #MLResearch #NLPResearch #SocialMediaData

#CallForPapers: Our full-day workshop at The Web Conference 2026 #TheWebConf2026 invites submissions on reproducible and reusable computational approaches for social and web data.
👉 https://easychair.org/cfp/r2cass2026

Deadline: Dec 18th, 2025