According to Sundar Pichai, EmbeddingGemma 2 is a 740M multimodal embedding model for offline RAG, outperforming larger specialists, per Google’s announcement.

According to @_avichawla, SIE served 4 small models on one GPU with LRU loading, cutting concurrent workload latency from 18.58s to 1.47s.

According to OpenAI... GPT-6 Astra adds tools and context for law firms, promising faster research, drafting, and review with controllable settings.

According to @godofprompt, a prompt flags documentation lines an AI agent should no longer follow, enabling automated policy and spec drift detection.

According to DeepLearningAI, a new context tool helps agents reduce memory bloat and API spend for production retrieval, as reported by The Batch.

According to The Rundown AI, a 75-page study maps 491 papers on five AI self-improvement levels; under 6% hit Level 5, where AI rewrites its R&D.

According to @emollick, GPT-6 autonomously built a multi-GB personal wiki from emails and files in 5 days and now delivers twice-daily briefings.

According to @openclaw, v2026.9.1 adds Mermaid chat, faster setup, smarter update halt, lighter long chats, and drawing, with 1,186 PRs from 281 contributors.

According to @godofprompt, Stanford's Storm reads the web and delivers multi-perspective, cited reports, free to try in browser, per Stanford HAI.

According to @DeepLearningAI, Andrew Ng outlines Pillar 1 with LLM basics, data grounding, agents, eval loops, and ops for reliable AI delivery.

According to @_avichawla, agentic retrieval with indexing, routing, query construction, retrieval, and generation outperforms linear RAG for multi-source data.

According to @CNBC, client chatbots now rival human advisors, pushing firms to add AI planning tools, audits, and compliance workflows.

According to @bcherny, engineers see 10x output with Claude as orgs progress through four repeatable AI adoption steps.

According to @NotebookLM, Ethan Mollick contrasts ChatGPT Work with NotebookLM on 70+ files, highlighting process and sources centric answers.

According to @claudeai, Anthropic details Claude Code’s origins, early user feedback, and product milestones in a new behind the scenes video.

According to @claudeai, Claude Science links artifacts to code, spins up managed environments, and connects 60+ scientific databases in beta.

According to @_avichawla, moving transforms to GPU cuts CPU GPU transfer 4x; binary quantization shrinks embeddings 32x for fast RAG search.

According to @_avichawla, BM25 still powers Elasticsearch and OpenSearch, excels at exact matches, and pairs best with vectors for hybrid RAG.

According to @_avichawla, 8 RAG patterns from Naive to Agentic boost accuracy, reduce tokens 3x, and cut corpus 40x via better indexing.

According to AndrewYNg, a new deeplearning.ai course with VocalBridge teaches building low latency, reliable voice agents and outbound call bots.