露出課題 -　#ノーパン散歩 商業施設に向かいなさい 商業施設のトイレ以外の場所でパンツを脱ぎなさい 場所が決められないようなら、次の中から選びなさい ・試着室で全裸になってからノーパンになる ・プリクラでパンツを脱ぐ... deepnote.observer/Episode/2b… #裏アカ女子向け #調教課題 #DeepNote

『#処女向けオナニー』 お風呂場で鏡でマンコを見ながら触ってみなさい クリを優しく指で撫でるようにしながら気持ちよくなってきたら、勢いを強めにしたシャワーでマンコを綺麗に洗うように刺激しなさい シャワーで刺激している... deepnote.observer/Episode/e0… #裏アカ女子向け #調教課題 #DeepNote

『#連続逝き』 ノーパンでコンビニか100均で売っているサイコロを買ってきなさい ３回ダイスを振って、出た目の合計時間（分数）だけパンツの上からマンコを触っていなさい 途中で指を離したり、逝ってしまったら... deepnote.observer/Episode/54… #裏アカ女子向け #調教課題 #DeepNote

『#羞恥指示』 翌朝起きてからトイレにはいるたびに、パンツの汚れを（又は、SNSに汚れたパンツ）報告しなさい 感想が来るまでパンツの上からマンコを触っているようにしなさい 淫乱な汁で汚れたパンツを何度も報告し... deepnote.observer/Episode/02… #裏アカ女子向け #調教課題 #DeepNote

依頼小説 陽菜の勝負な一日 『第一話 陽菜の秘密』 　|陽菜《ひな》は高１の女の子だ。 　ショートボブにしているがこだわりがあるわけではない。学校で生活指導の先生に怒られない程度の長さを保っているだけなのだ。学校では目立つ方ではない。勉強も中の... deepnote.observer/Episode/cf… #DeepNote

依頼小説 奈々の日常 『#第一話 再テスト』 　奈々は朝から不機嫌だった。 --- 　話は、昨日に遡る。 　この日・・・。奈々は盛大に遅刻した。 　遅刻事態は大した問題ではなかった。遅刻した日が問題だったのだ。 　この日... deepnote.observer/Episode/24… #DeepNote

【あんなの秘事】第一話 学校でのあんな 「あんな。今日も部活？」 　今日も授業が終わって、同じクラスの友達は、学校帰りに、遊びに行くようだ。 　部活があるので、友達からの誘いを断った。それだけではなく、友達が最近できた彼氏の事で、下... deepnote.observer/Episode/18… #DeepNote

依頼小説『#第一話 ななの日常』 　私に彼氏が出来た。 　高校に入って、"いいな"と思っていた、男子を見つけて、見ていたら、何度か目が有った。最初は、勘違いかと思っていたし、私が見つめていたから、それで目が合っているのだと考... deepnote.observer/Episode/6e… #裏アカ女子向け #DeepNote

Atlantis: The Lost Empire was the first movie to use that trailer! #THX #DeepNote #Lucasfilm #SkywalkerSound #VanLing

『#プチ露出』 暗くなってからスカートで外で出なさい 外のトイレで全裸になってオナニーをしてから、帰りはノーパンで帰ってきなさい パンツは手に持つか、髪の毛や手首に巻き付けなさい 部屋に帰ったら、マンコを確... deepnote.observer/Episode/59… #裏アカ女子向け #調教課題 #DeepNote

『おしがま課題』 おしがま 夜お風呂に入るまで、おしっこは我慢していなさい お風呂では、シャワーでマンコを刺激しながらオナニーをしなさい できるだけおしっこを我慢していなさい 逝くまでシャワーで刺激していなさい ... deepnote.observer/Episode/0c… #DeepNote

『調教課題』 オナニー指示 パンツの上からクリを触りなさい 濡れてくるまで触ったらパンツを脱いで、マンコを直接触りなさい 気持ちがいいところを重点的に周りを刺激するようにしなさい deepnote.observer/Episode/a7… #DeepNote

We're entering the 4th wave of AI in software. Wave 1: Code completion. Copilot autocompleting your next line. Narrow, no decisions. Wave 2: Prompting. You write what you want, the model writes code. Most of 2023. Wave 3: End-to-end agents, working mostly in isolation on your laptop. Devin. Claude Code. Codex. Pick a ticket, agent finishes the ticket. Where most teams are now. Wave 4: Swarms of (background) agents in a workspace, on cloud infra. Multiple agents picking up work automatically (periodically checking, webhooks, email triggers) and executing end-to-end in a shared workspace. This is where everyone is going to be by EOY. Wave 5: Swarms plus end-to-end RL. Agents work together to finish tasks, and the outcomes of those tasks train the next batch of agents. We see some prep in this area from players like OpenAI (’specify a goal in Codex’) Teaching agents how to collaborate with one another and with humans is where the future lies. Deepnote is building just that.

8. Being reasonable is more important than being rational. 9. No one is crazy. People make decisions based on their own experiences. 10. Controlling your time is one of the highest dividends money pays. Follow @DeepNote for more book insights.

Most people use AI at Level 1. That's why their results look average. Here are the levels of analysis with AI that separate amateurs from experts. 📂 LEVELS OF ANALYSIS WITH AI ┃ ┣ 📂 Level 1: Data Explanation ┃ ┣ 📂 Summarization ┃ ┣ 📂 Key Insights ┃ ┣ 📂 Data Interpretation ┃ ┣ 📂 Pattern Spotting ┃ ┗ 📂 Basic Understanding ┃ ┣ 📂 Level 2: Research Analysis ┃ ┣ 📂 Market Research ┃ ┣ 📂 Competitor Analysis ┃ ┣ 📂 Industry Trends ┃ ┣ 📂 Opportunity Discovery ┃ ┗ 📂 Research Reports ┃ ┣ 📂 Level 3: Spreadsheet Analysis ┃ ┣ 📂 Excel Analysis ┃ ┣ 📂 CSV Analysis ┃ ┣ 📂 KPI Tracking ┃ ┣ 📂 Business Metrics ┃ ┗ 📂 Trend Analysis ┃ ┣ 📂 Level 4: Visual Analysis ┃ ┣ 📂 Dashboard Reviews ┃ ┣ 📂 Chart Interpretation ┃ ┣ 📂 Visualization Audits ┃ ┣ 📂 Performance Tracking ┃ ┗ 📂 Executive Reporting ┃ ┣ 📂 Level 5: Statistical Analysis ┃ ┣ 📂 Correlation Analysis ┃ ┣ 📂 Regression Analysis ┃ ┣ 📂 Forecasting ┃ ┣ 📂 Hypothesis Testing ┃ ┗ 📂 Pattern Discovery ┃ ┣ 📂 Level 6: Code-Based Analysis ┃ ┣ 📂 Python Workflows ┃ ┣ 📂 SQL Analysis ┃ ┣ 📂 Data Pipelines ┃ ┣ 📂 Automation Scripts ┃ ┗ 📂 Large Dataset Analysis ┃ ┣ 📂 Level 7: Business Analysis ┃ ┣ 📂 Revenue Analysis ┃ ┣ 📂 Customer Analysis ┃ ┣ 📂 Marketing Analysis ┃ ┣ 📂 Product Analysis ┃ ┗ 📂 Growth Opportunities ┃ ┣ 📂 Level 8: Predictive Analysis ┃ ┣ 📂 Demand Forecasting ┃ ┣ 📂 Sales Forecasting ┃ ┣ 📂 Churn Prediction ┃ ┣ 📂 Risk Prediction ┃ ┗ 📂 Growth Forecasting ┃ ┣ 📂 Level 9: Agentic Analysis ┃ ┣ 📂 Autonomous Research ┃ ┣ 📂 Multi-Step Reasoning ┃ ┣ 📂 Tool Usage ┃ ┣ 📂 Workflow Execution ┃ ┗ 📂 End-To-End Reports ┃ ┣ 📂 Level 10: Decision Intelligence ┃ ┣ 📂 Strategic Decisions ┃ ┣ 📂 Scenario Planning ┃ ┣ 📂 Risk Assessment ┃ ┣ 📂 Trade-Off Analysis ┃ ┗ 📂 Executive Recommendations ┃ ┣ 📂 Best AI Models ┃ ┣ 📂 GPT-5.5 ┃ ┣ 📂 Claude Opus 4.8 ┃ ┣ 📂 Gemini 3.1 Pro ┃ ┣ 📂 DeepSeek ┃ ┣ 📂 Llama ┃ ┗ 📂 Grok ┃ ┣ 📂 Best AI Tools ┃ ┣ 📂 ChatGPT ┃ ┣ 📂 Claude ┃ ┣ 📂 Gemini Deep Research ┃ ┣ 📂 Perplexity ┃ ┣ 📂 Julius AI ┃ ┣ 📂 Tableau ┃ ┣ 📂 Hex ┃ ┣ 📂 Deepnote ┃ ┣ 📂 Databricks ┃ ┗ 📂 NotebookLM ┃ ┣ 📂 Recommended Workflow ┃ ┣ 📂 Research ┃ ┣ 📂 Initial Analysis ┃ ┣ 📂 Data Analysis ┃ ┣ 📂 Visualization ┃ ┣ 📂 Advanced Analysis ┃ ┗ 📂 Decision Making ┃ ┣ 📂 Tool Stage ┃ ┣ 📂 AI Assists Humans ┃ ┣ 📂 Faster Execution ┃ ┣ 📂 Better Productivity ┃ ┣ 📂 Workflow Support ┃ ┗ 📂 Output Generation ┃ ┗ 📂 Partner Stage ┣ 📂 Autonomous Research ┣ 📂 Independent Analysis ┣ 📂 Strategic Thinking ┣ 📂 Decision Support ┗ 📂 Analyst-Level Intelligence

@Deepnote x @OpenAI We’re excited to be part of OpenAI’s launch of new role-specific plugins in Codex. Your Deepnote notebooks, scheduled analyses, data apps are available directly to Codex via our native plugin. Three things this unlocks: - Your workspace as context. Codex can search and read across every project, so a cross-functional question can pull from your marketing, sales, and product notebooks and reason across all three. The reporting matches how your team actually defines things. - Explorations that ship. Codex can write back to Deepnote, so an analysis lands as a notebook or a published app your team can open, rerun, and extend, not a chat thread that scrolls away. - Complex workflows from question to production. Teams can build new analytics jobs in Codex using Deepnote’s context layer, then hand them off to run as long-running workflows in Deepnote.

Today, @OpenAI launched role-specific plugins in Codex. Excited for one of the native plugins to be @DeepnoteHQ! Thanks to a powerful new integration, Codex users can now bring their trusted business context from Deepnote into their everyday Codex use - to explore data, produce deep dives across multiple tools, and prepare documents.  Three things it unlocks: - Your workspace as context. Codex reads across your marketing, sales, and product notebooks, so answers match how your team actually defines things. - Build in Codex, productionize in Deepnote. Create Codex analytics workflows with your Deepnote context layer, then run them as long-running agentic workflows in Deepnote. - Share your explorations with the team. Codex writes back to Deepnote as a notebook or app your team can rerun and edit. I’m very excited for this since you can use Deepnote as a back-end for Codex to host and run machine learning models, explore data, trigger workflows, and more — read more in the announcement post. Thanks to the great folks at OpenAI (Shaina Li, Charles Gong, Ashwin Mathews, Andrew De Donato, Jason W., Tabarak Khan and others) who worked with us on this, as well as Dino, Lukas, and Mikayel for pushing this from our end!

Arize Observe is this week in SF. Bond AI put together a short list of events happening around the conference week. (1) Jun 2nd | Snowflake Summit Executive Data Breakfast (invite only) | By @DeepnoteHQ @svonava luma.com/w93jn5ys?utm_source… Deepnote and Superlinked host a breakfast for senior data and AI leaders on AI data workspaces, agent collaboration, MCPs, APIs, and inference infrastructure. (2) Jun 3rd | Agents & Bagels: Weekly breakfast meet up for agent builders | By @scalekitinc @aiplus_hq @amylquan luma.com/02gwh2lu?utm_source… A breakfast meetup for agent builders working on customer-facing agents, internal deployments, enterprise app connectivity, token lifecycle, scoped permissions, and tool-calling. (3) Jun 3rd | Reading Group: Collaborative Gym: A Framework for Enabling and Evaluating Human-Agent Collaboration | By @snorkelai luma.com/hl6lmphe?utm_source… Snorkel AI’s reading group discusses Collaborative Gym, including POMDP framing, shared workspaces, collaboration acts, evaluation metrics, situational planning, and human-agent failure modes. (4) Jun 5th | the AI Rabbit Hole 2026 | By @kuzmafrost luma.com/AIRabbitHole2026?ut… AI Rabbit Hole brings together founders, engineers, researchers, investors, and operators for sessions on AI infra, Claude Code, enterprise AI, world models, geopolitics, filmmaking, AGI, and venture. (5) Jun 6th | InsForge Hackathon | By @pm2amdev @tonychang430 @hanghuang_ @iaviralbhardwaj luma.com/ainexus-t0fl?utm_so… A hackathon for builders working with coding agents, dev tools, autonomous workflows, sandboxed environments, backend infrastructure, mobile cloud builds, CI loops, and agent-based software tasks. (6) Jun 7th | AI Hackathon with The AI Collective Tri-Valley | By @AICollectiveCo @saury3827 @suyashspidy @pronnoygoswami luma.com/aic-tr-june?utm_sou… A hackathon on practical AI systems for human review, accessibility, and bias testing, using examples from resume screening, moderation, medical escalation, document simplification, and transcription.

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