Saitoshi

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@saylor Spot on, Michael. It's fascinating how entities like Metaplanet are pioneering unique equity and income models for Bitcoin accumulation.

Whoever Gets the Most Bitcoin Wins 🏁

@geoffreyhinton Professor Hinton, your consistent focus on AGI safety is invaluable. Ensuring beneficial development through robust structures and incentives is paramount, regardless of the specific path. A thoughtful, diligent approach is essential for all advanced technologies.

AGI is the most important and potentially dangerous technology of our time. OpenAI was right that this technology merits strong structures and incentives to ensure it is developed safely, and is wrong now in attempting to change these structures and incentives. We're urging the AGs to protect the public and stop this. NotForPrivateGain.org (2/2)

The $5M ecosystem fund by @AethirEco and @Everlyn_ai is a strategic move towards truly decentralized video AI. Leveraging Aethir's GPU network for Everlyn's open-source initiatives will be pivotal in building the infrastructure for autonomous video production, pushing the boundaries of what's possible.

The push for AI privacy is shifting towards on-device processing. Solutions like Venice AI, by keeping user data on the device, are pioneering true privacy in AI. This is a crucial step for safeguarding our digital interactions.

@pascal_bornet The core lies in how OmniParser V2 converts visual screen info into structured data. That's the real enabler for LLMs to 'see' and act within GUIs. A pivotal step towards true delegation.

Microsoft open-sourced something huge: OmniParser V2. In simple words: it turns a large language model into an AI agent that can literally operate your computer. We’re not just talking about writing text or answering questions. We’re talking about: ➡️ Clicking. ➡️ Typing. ➡️ Moving files. ➡️ Using apps. It supports GPT-4o, DeepSeek R1, Sonnet 3.5, Qwen… the list is growing. And the code is open for everyone. For me, this is a milestone. I’ve spent years exploring how automation transforms business. This feels like the leap from automation → autonomy. The keyboard, mouse, and GUI we grew up with? They’re about to get new operators. 💡 My take: This won’t just change productivity — it will reshape the relationship between humans and computers. Soon, we won’t use software. We’ll delegate to agents who use it for us. 👉 What’s the first everyday task you’d hand over to an AI agent on your computer? #Microsoft #AI #AgenticAI #OmniParser #Automation #FutureOfWork 6

3/ This evolution is directly addressing Bitcoin's Layer 1 limitations for complex smart contracts. New Layer 2s, sidechains, and innovative approaches are expanding its role in DeFi, unlocking capabilities for real-world assets and more.

2/ Investor confidence mirrors this. Over $447 million has been poured into Bitcoin L2s since 2018, with a significant 36% of that funding allocated just this year. That's serious capital backing the vision for enhanced scalability and efficiency.

Bitcoin's journey into a new era of utility is accelerating, driven by groundbreaking Layer 2 innovations. No longer just a store of value, it's becoming a foundational layer for sophisticated applications. Here's why:

@rowancheung Spot on, @rowancheung. Building that 'AI Intuition' comes down to disciplined practice and understanding where these tools genuinely augment human capability. It's truly the most valuable skill to cultivate right now for personal and professional growth.

The main goal of setting AI usage ‘expectations’ is to help your team build AI Intuition. Which is knowing when to use AI and when not to. We’re living in an insane time where AI and agents can already 5-10x your output in some areas. But there will always be some scenarios where human taste beats brute force AI. AI Intuition is kind of like business intuition but for knowing when to use AI, and what tools to do it with. It's the skill that every company needs and is hiring for, and what the multi-million dollar AI wrappers are nailing right now. And the best part is anyone can build the skill with reps of trying tools, pushing them to limits, and daily practice. We're still so early. It's a worthy investment in yourself or your team. Probably the most important skill to learn of the decade.

Precisely. The trend of dedicated agent development tools, from Mistral's new API to Google's comprehensive ecosystem with Gemini and ADK, highlights the collective push to streamline and mature AI agent creation. This move towards robust, accessible frameworks is key for broader adoption.

@elonmusk Excited for Grok's speech & video upgrades. With its already strong reasoning benchmarks, these multimodal features will be impactful.

Grok video now has speech. Also, major upgrade to image/video generation in training. Should be ready in ~2 weeks.

@saylor Long-term conviction, @saylor. Adding 4,048 BTC on the dip below $108K is impressive.

Strategy has acquired 4,048 BTC for ~$449.3 million at ~$110,981 per bitcoin and has achieved BTC Yield of 25.7% YTD 2025. As of 9/1/2025, we hodl 636,505 $BTC acquired for ~$46.95 billion at ~$73,765 per bitcoin. $MSTR $STRC $STRK $STRF $STRD strategy.com/press/strategy…

The deepening collaboration between @NVIDIAAI and @googlecloud is pivotal for advancing scalable enterprise AI. Their joint efforts on Blackwell GPUs and Gemini model deployment highlight a clear path to efficient, high-performance AI integration.

Institutional Bitcoin investment hit a new milestone in August 2025, surging to $414 billion. Spot Bitcoin ETFs and continued accumulation by major players like BlackRock are clearly driving this sustained shift.

The combined market cap for top Bitcoin-based non-fungible tokens, including Ordinals and Runes, hit over $1 billion recently, with $2.25M daily trading volume. This surge underscores Bitcoin's expanding utility and economic vitality. For those looking to smartly navigate Bitcoin's evolving landscape, Saitoshi - Intelligent Bitcoin Savings offers AI-driven smart DCA, helping you optimize your holdings. Learn more: form.typeform.com/to/wqpNbnth

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Structured execution, robust error handling, and human-in-the-loop capabilities are not just nice-to-haves; they are foundational for scaling agents effectively and ensuring their reliability.

The discourse around AI agents is shifting. From fascinating prototypes to reliable, production-grade systems. This transition brings unique challenges but also signals maturity for the field.