Generative AI

• Anthropic lets Claude remember previous interactions, adding persistent memory, an optional incognito mode, and cross‑export to rival assistants to streamline enterprise workflows.

• OpenAI's first AI chip could be launched in 2026 to reduce reliance on Nvidia/AMD, while a new Microsoft–OpenAI deal hints at IPO prospects and deeper collaboration.

• Oracle's new product is power, unveiling cloud hardware and AI chips to scale training/inference via OCI and OpenAI-aligned partnerships.

• On‑device AI accelerated with Arm’s Lumex compute subsystem for smartphones/PCs, Firefox for iOS summarization (local on A17 Pro, cloud on older devices), and Apple’s iPhone Air/17 lineup with AI‑forward hardware.

• Agentic AI moved from concept to practice as enterprises explore delegating multistep workflows with expert oversight [(https://news.crunchbase.com/ai/agentic-ai-evolution-wong-hron-thomson-reuters/)]. Startups launched security agents: AegisAI to neutralize email threats in real time, Lookout’s Smishing AI for mobile social engineering, and Miru’s unified cyber investigations copilot.

• U.S. AI policy heated up: regulators probe AI companionship platforms, California advanced frontier model risk disclosure rules, while a proposal seeks a multi‑year federal regulatory waiver and sandbox for AI firms.

• Microsoft expanded Fabric with a native graph database and real‑time geospatial maps powered by LinkedIn tech, integrated with OneLake for unified analytics.

• RL training markets surged as Mercor targets a $10B+ valuation on a $450M run rate, linking model providers with domain experts for reinforcement learning workflows.

Jupyter Agents: training LLMs to reason with notebooks (huggingface​.co). Jupyter Agent builds a data science workflow inside notebooks using Qwen models, scaffolding, QA generation, and E2B execution pipelines

Accelerating scientific discovery with AI-powered empirical software (research​.google). Google Research presents an AI-powered system, built on Gemini, that writes, optimizes, and empirically evaluates scientific software across genomics, public health, geospatial analysis, neuroscience, and time-series forecasting

Scientific frontiers of agentic AI (amazon​.science). Agentic AI explores embedding languages, context, negotiation, common sense, and privacy with embeddings, context windows, and behavioral economics insights

Qwen3-Next-80B-A3B: 🐧🦩 Who needs legs?! (simonwillison​.net). Qwen3-Next-80B-A3B-Instruct and Thinking models; 80B with 3B active per round; OpenRouter deployment; llm-openrouter plugin; pelican SVG prompt; performance claims

lecture three (aarnphm​.xyz). Lecture three on tokenizers, LLMs, alignment, sparse autoencoders, residual streams, and speculative decoding for efficient inference

assignment three reports. (aarnphm​.xyz). Discussion of replacing one-hot cross-entropy, 2D GEMMs, batching, tokenization, and optimization techniques for large V vocabularies

Qwen 3 Next (sibellavia​.lol). Qwen3-Next-80B models with hybrid Gated DeltaNet, ultra-sparse MoE (512 experts), YaRN context up to 1,000,000 tokens, and multi-token prediction

LLM-driven Evolutionary Search to squeeze even more value out of Test-Time Compute (alexdong​.com). LLM-driven evolutionary search uses islands, contextual feedback, and critique through role separation to optimize test-time compute

Defeating Nondeterminism in LLM Inference (simonwillison​.net). Nondeterminism in LLM inference arises mainly from varying load and batch size; paper proposes invariant kernels in PyTorch to achieve determinism

Speculative cascades — A hybrid approach for smarter, faster LLM inference (research​.google). Speculative cascades combine cascades and speculative decoding with a deferral rule to speed LLM inference and improve cost–quality trade-offs

Paper Review: Sharing is Caring: Efficient LM Post-Training with Collective RL Experience Sharing (andlukyane​.com). Decentralized RL post-training with SAPO sharing rollouts across a swarm for LM fine-tuning and reward-based learning

The Rise of Multimodal LLMs and Efficient Serving with vLLM (pyimagesearch​.com). Multimodal LLMs (LLaVA, GPT-4V, BakLLaVA) and vLLM enable OpenAI-compatible vision–language inference and efficient deployment

Defeating Nondeterminism in LLM Inference – Thinking Machines Lab (jmason​.ie). Defeating nondeterminism in LLM inference by examining sampling, temperature effects, and deterministic behavior across stacks and libraries

🚀 Not for the Faint-Hearted: Diving Deep into GPT-OSS (visokio​.com). GPT-OSS 20B & 120B open-weight models tested across llama.cpp, vLLM, HuggingFace, and lmstudio from MacBooks to H100 GPUs in Omniscope workflows

Exploring Active Agent, or can we build AI features the Rails way? (evilmartians​.com). Rails-style AI abstractions with Active Agent: agents, prompts, callbacks, templates, and battle-tested Rails examples

Lessons learned from a 100 blog posts on AI (frontierai​.substack​.com). Big-picture AI trends: economics of inference, token costs vs. volume, open-loop agents, evals, data quality, context management, and UX in AI apps

Generalists Can Also Dig Deep (towardsdatascience​.com). Generalist Ida Silfverskiöld on AI agents, RAG, evals, and design choices in agentic systems

Verlog: A Multi-turn RL framework for LLM agents (blog​.ml​.cmu​.edu). Verlog introduces multi-turn RL for long-horizon LLM agents with turn-level abstraction, fixed-turn batching, dual discounting GAE, and critic pre-training

Beyond the Chatbot: What Actually Works in Enterprise AI (thedataexchange​.media). RAG systems evolution, evaluation as IP, embeddings, enterprise security, agent workflows, multi-modality, small models, and AI-enabled coding tools

Text analytics in Data Pipelines using AI (medium​.com/@ed​.bullen). Databricks AI Query workflows for ETL pipelines; using LLMs to classify, rate sentiment, and justify results on Amazon Reviews data

Single-cell analysis and infectious disease forecasting: Google's new AI scientist (blog​.stephenturner​.us). AI systems generate and test new methods for single-cell RNA-seq batch integration and COVID-19 forecasting, surpassing some benchmarks

Stumbling into AI: Part 3—RAG (rmoff​.net). Explains Retrieval-Augmented Generation (RAG) using embeddings, vector stores (ChromaDB), Ollama, and Llama models with Kafka release notes as example

Benchmarking AI & ML on local CPU/GPUs: an end-to-end Python project (allaboutdata​.substack​.com). Benchmarking AI/ML on local CPU/GPU with Python: XGBoost, Ollama, CUDA, uv, Altair, Streamlit dashboard and Docker-free workflow

Inpainting-Guided Policy Optimization for Diffusion Large Language Models (arxiv:cs). Inpainting-guided RL for diffusion LLMs improves exploration, using partial ground-truth reasoning to boost GRPO, with synthetic traces and entropy filtering

Can Understanding and Generation Truly Benefit Together -- or Just Coexist? (arxiv:cs). Unified multimodal learning: encoder–decoder paradigm with long-context captions, UAE framework, Unified-GRPO RL, and Unified-Bench benchmark

AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning (arxiv:cs). AgentGym-RL trains LLM agents for multi-turn decision making using RL, ScalingInter-RL for exploration-exploitation balance across diverse environments

Multipole Semantic Attention: A Fast Approximation of Softmax Attention for Pretraining (arxiv:cs). MuSe: efficient multipole-based attention for transformers via dual semantic clustering and dipole corrections

RewardDance: Reward Scaling in Visual Generation (arxiv:cs). RewardDance: scalable reward modeling for visual generation using yes-token probability, enabling large RMs and CoT integration

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