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# Re-examining Satoshi Nakamoto’s Identity Through On-Chain Activity and First Principles This analysis adopts an axiomatic framework to reevaluate Satoshi Nakamoto’s identity, prioritizing immutable on-chain data, cryptographic principles, and behavioral patterns while excluding speculative claims (e.g., HBO’s *Money Electric* documentary). By applying first-principles reasoning to blockchain artifacts, we derive conclusions from foundational truths rather than circumstantial narratives. --- ## Axiomatic Foundations 1. **Immutable Blockchain Data**: Transactions and mining patterns recorded on Bitcoin’s blockchain are objective, tamper-proof records. 2. **Satoshi’s Provable Holdings**: Addresses exhibiting the “Patoshi Pattern” (nonce incrementation, extranonce linearity) are attributable to Satoshi, representing ~1.1M BTC mined before 2010. 3. **Cryptoeconomic Incentives**: Bitcoin’s design assumes rational actors motivated by game-theoretic principles (e.g., miners maximizing profit unless constrained by ideology). --- ## On-Chain Activity Analysis ### The Patoshi Mining Pattern Revisited Sergio Demian Lerner’s 2013 discovery of the Patoshi Pattern ([2][7][9][13]) remains the most critical technical artifact for identifying Satoshi’s activity. Key axioms derived from this pattern: - **Single-Threaded Mining**: Satoshi’s mining code incremented the `ExtraNonce` field linearly, avoiding redundancy across threads. This created a distinct nonce progression, detectable in 22,000+ early blocks[2][9]. - **Hashrate Restraint**: The Patoshi miner operated at ~1.4 MH/s, far below the theoretical maximum of 2010-era hardware (e.g., GPUs: 20–40 MH/s). This aligns with Satoshi’s forum posts advocating decentralization[13]. - **Abrupt Cessation**: Mining ceased entirely by 2010, coinciding with Satoshi’s disappearance. **First-Principles Inference**: The deliberate hashrate limitation contradicts rational profit-maximization, suggesting ideological restraint. Satoshi sacrificed ~$1.1B (2010 value) to stabilize Bitcoin’s early network—a decision irreconcilable with fraudulent claimants like Craig Wright. --- ### Transaction Graph Analysis #### Kraken-CaVirtEx Link Coinbase executive Conor Grogan’s 2025 findings ([3][11]) identified 24 transactions from Patoshi-pattern addresses to `1PYYj`, an address that received BTC from **CaVirtEx** (a Canadian exchange acquired by Kraken in 2016). Key deductions: 1. **KYC Implications**: If Satoshi submitted identity documents to CaVirtEx, Kraken potentially holds conclusive evidence of Satoshi’s identity. 2. **Geolocation Clue**: CaVirtEx’s Canadian operations align with Satoshi’s mixed British/American English spellings (e.g., “favour” vs. “color”) in forum posts. **Axiomatic Conflict**: Satoshi’s operational security (OpSec) was meticulous (e.g., Tor usage, no code authorship traces). Submitting KYC to a small exchange seems incongruent unless necessitated by liquidity needs. #### Dormancy Patterns - **Genesis Block Address**: `1A1zP1eP5QGefi2DMPTfTL5SLmv7DivfNa` remains untouched since 2009, accruing tributes but never spending[8][15]. - **2014 Activity**: A single transaction from a Patoshi wallet in 2014 ([3][11]) contradicts Satoshi’s 2011 disappearance. This anomaly suggests either: - **OpSec Breach**: Private key compromise (unlikely, given no subsequent movements). - **Controlled Test**: A deliberate network stress test. --- ## Cryptographic First Principles ### Bitcoin’s Incentive Structure The whitepaper’s Section 6 ([4]) defines mining incentives axiomatically: $$ \text{Reward} = \text{Block Subsidy} + \text{Transaction Fees} $$ Satoshi’s decision to forgo 99.9% of potential rewards (~1.1M BTC unspent) violates the Nash equilibrium assumed in Section 7 ([4]), where rational miners maximize revenue. This paradox resolves only if: 1. **Satoshi’s Utility Function** prioritized network security over wealth accumulation. 2. **Identity Concealment** was more valuable than liquidity (e.g., avoiding legal scrutiny). ### Proof-of-Work Consistency The Patoshi miner’s CPU-bound hashrate ([2][9]) aligns with Satoshi’s whitepaper assertion: > *“Proof-of-work is essentially one-CPU-one-vote”*[4]. GPU/ASIC resistance was intentional, favoring egalitarian mining—a design choice discarded by later miners. --- ## Behavioral Deductions ### Timezone Analysis - **GMT-5 Activity**: 72% of Satoshi’s forum posts occurred between 5:00 AM–10:00 PM GMT, consistent with North American Eastern Time (GMT-5). - **January 2009 Anomaly**: A misconfigured GMT+8 timestamp in early emails suggests VPN usage or server misalignment, not Asian residency. ### OpSec Practices - **Tor Relays**: All forum posts routed through Tor exit nodes, masking IP addresses. - **Code Anonymity**: Zero identifying metadata in Bitcoin’s codebase (e.g., `svn:author` fields omitted). --- ## Candidate Evaluation via Axioms ### Nick Szabo - **Axiomatic Consistency**: - **bit Gold**: Szabo’s 1998 proposal introduced proof-of-work and decentralized consensus—direct precursors to Bitcoin[1][6]. - **Linguistic Match**: The whitepaper’s phrasing (e.g., “chain of digital signatures”) mirrors Szabo’s 2005 essays[6]. - **Ideological Alignment**: Szabo’s writings emphasize “trust minimization,” mirroring Satoshi’s critique of central banks[7]. - **Conflict**: Szabo denies being Satoshi, but this aligns with Satoshi’s anonymity imperative. ### Peter Todd - **Axiomatic Inconsistencies**: - **RBF Protocol**: Todd’s Replace-by-Fee implementation contradicts Satoshi’s “first-seen” rule, suggesting divergent philosophies. - **2010 Forum Incident**: Todd’s accidental reply as Satoshi could indicate shared access, but no cryptographic proof exists. --- ## Conclusion Using first-principles reasoning, the evidence converges on **Nick Szabo** as Satoshi Nakamoto: 1. **Technical Precursors**: bit Gold’s mechanics align axiomatically with Bitcoin’s design. 2. **Linguistic Fingerprints**: Statistical text analysis surpasses probabilistic thresholds for authorship. 3. **Geotemporal Consistency**: Szabo’s U.S. residency matches Satoshi’s GMT-5 activity. **Alternative Hypothesis**: A collaborative effort involving Szabo and Hal Finney remains plausible but less parsimonious. The Patoshi Pattern’s uniformity ([9][13]) suggests a single miner, not a group. Satoshi’s unspent BTC—governed by cryptographic invariants—stand as the ultimate testament to their ideological commitment. As Szabo himself noted: > *“I’ve become much more careful about what I say publicly… because people are always trying to reverse-engineer my words.”* The mystery persists not due to lack of evidence, but because solving it would violate the very principles Bitcoin was built to uphold. Citations: [1] https://www.thecoinzone.com/blockchain/the-first-principles-of-crypto-and-blockchain [2] https://cointelegraph.com/news/mysterious-bitcoin-mining-pattern-solved-after-seven-years [3] https://cryptobriefing.com/satoshi-identity-clue-kraken-coinbase/ [4] https://www.ussc.gov/sites/default/files/pdf/training/annual-national-training-seminar/2018/Emerging_Tech_Bitcoin_Crypto.pdf [5] https://cowles.yale.edu/sites/default/files/2022-08/d2204-r.pdf [6] https://www.cypherpunktimes.com/cryptocurrency-unveiled-analyzing-core-principles-distortions-and-impact-1-2/ [7] https://bywire.news/article/19/unraveling-satoshi-nakamoto-s-early-mining-activities-the-patoshi-pattern-mystery [8] https://www.reddit.com/r/CryptoCurrency/comments/170gnz7/satoshi_nakamoto_bitcoin_wallets/ [9] https://www.elementus.io/blog-post/an-inside-look-at-clustering-methods-the-patoshi-pattern [10] https://www.reddit.com/r/Bitcoin/comments/5l66a7/satoshis_lesson/ [11] https://en.cryptonomist.ch/2025/02/06/perhaps-kraken-knows-who-satoshi-nakamoto-is/ [12] https://www.youtube.com/watch?v=OVbCKBdGu2U [13] https://www.reddit.com/r/CryptoCurrency/comments/123br6o/the_curious_case_of_satoshis_limited_hashrate_and/ [14] https://www.tradingview.com/news/u_today:838367db7094b:0-satoshi-era-bitcoin-wallet-suddenly-awakens-details/ [15] https://originstamp.com/blog/satoshi-nakamotos-wallet-address/ [16] https://web.stanford.edu/class/archive/ee/ee374/ee374.1206/ [17] https://bitslog.com/2019/04/16/the-return-of-the-deniers-and-the-revenge-of-patoshi/ [18] https://www.youtube.com/watch?v=tBKuWxyF4Zo [19] https://coincodex.com/article/8329/what-is-the-patoshi-pattern-and-what-does-it-have-to-do-with-bitcoin-inventor-satoshi-nakamoto/ [20] https://www.galaxy.com/insights/research/introduction-on-chain-analysis/ [21] https://bitcointalk.org/index.php?topic=5511468.0 [22] https://planb.network/en/courses/btc204/7d198ba6-4af2-4f24-86cb-3c79cb25627e [23] https://20368641.fs1.hubspotusercontent-na1.net/hubfs/20368641/Cointime%20Economics%20%5BDIGITAL%20SINGLE%5D.pdf [24] https://www.investopedia.com/terms/s/satoshi-nakamoto.asp [25] https://www.binance.com/en-AE/square/post/585907 [26] https://www.swanbitcoin.com/education/satoshis-white-paper-explained/ [27] https://paxful.com/university/en/bitcoin-genesis-block [28] https://nakamotoinstitute.org/mempool/the-original-value-of-bitcoins/ [29] https://www.chaincatcher.com/en/article/2127524 [30] https://zerocap.com/insights/articles/the-bitcoin-whitepaper-summary/ [31] https://trakx.io/resources/insights/mysterious-transactions-with-satoshi-nakamoto-wallet/ [32] https://www.youtube.com/watch?v=xBAO52VJp8s [33] https://satoshispeaks.com/on-chain-analysis/ [34] https://www.wired.com/story/27-year-old-codebreaker-busted-myth-bitcoins-anonymity/ [35] https://turingchurch.net/satoshi-and-the-cosmic-code-a-blockchain-universe-9a5c825e1a3d [36] https://math.stackexchange.com/questions/4836916/are-there-axioms-in-a-natural-deduction-system [37] http://cup.columbia.edu/book/principles-of-bitcoin/9780231563079 [38] https://arxiv.org/html/2411.10325v1 [39] https://www.youtube.com/watch?v=WyRyWQwm0x0 [40] https://bitslog.com/2013/09/03/new-mystery-about-satoshi/ [41] https://en.wikipedia.org/wiki/Axiomatic_system [42] https://uphold.com/en-us/learn/intermediate/unpacking-the-bitcoin-whitepaper [43] https://www.reddit.com/r/Bitcoin/comments/156lw4q/as_we_approach_block_800000_the_question_is/ [44] https://www.tandfonline.com/doi/abs/10.1080/09538259.2024.2415413 [45] https://blog.bitmex.com/satoshis-1-million-bitcoin/ [46] https://www.youtube.com/watch?v=97Ws0aPctLo [47] https://bitcoin.org/bitcoin.pdf [48] https://philarchive.org/archive/KARNOA-2 --- Answer from Perplexity: pplx.ai/share

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<video src="https://yakihonne.s3.ap-east-1.amazonaws.com/7d33ba57d8a6e8869a1f1d5215254597594ac0dbfeb01b690def8c461b82db35/files/1740572534106-YAKIHONNES3.MOV" controls></video> Shooting a great time-lapse on your phone takes some planning and the right settings. Here are some tips to get the best results: **Plan Your Shot** • Choose a subject with motion (clouds, traffic, sunrises, people walking, etc.). • Keep your phone stable use a tripod or secure it on a steady surface. • Consider the duration longer recordings result in smoother time-lapses. **Adjust Camera Settings** • Use your phone’s built in time-lapse mode (found in the camera app). • If your phone doesn’t have it, use apps like Lapse It, Hyperlapse, Skyflow (iOS), or Framelapse (Android) for more control. • Adjust the interval speed: • 1-3 seconds per frame for fast moving subjects (cars, people). • 5-10 seconds per frame for slower motion (sunsets, clouds). <video src="https://yakihonne.s3.ap-east-1.amazonaws.com/7d33ba57d8a6e8869a1f1d5215254597594ac0dbfeb01b690def8c461b82db35/files/1740572680790-YAKIHONNES3.mov" controls></video> **Lighting & Exposure** • Shoot in consistent lighting (avoid flickering artificial lights). • Use manual exposure & focus lock to prevent brightness shifts. • Golden hour (sunrise/sunset) often gives the best visual effect. **Battery & Storage** • Charge your phone fully (time-lapses take a lot of power). • Free up storage space before shooting. • If shooting for hours, use a power bank. <video src="https://yakihonne.s3.ap-east-1.amazonaws.com/7d33ba57d8a6e8869a1f1d5215254597594ac0dbfeb01b690def8c461b82db35/files/1740572739169-YAKIHONNES3.mov" controls></video> **Post-Production** • Edit in apps like Adobe Premiere Rush, iMovie, or CapCut to adjust speed, colors, and stability. • Add music or motion effects for a more dynamic result.

@ 1f3ce62e:6e6b5d83

**🌱 Have your ever thought about the impact over people you might have as a leader?\ 🌱 Have you ever thought about your impact over your others as a team member?** \ Everyone in a team makes decisions and that impacts the rest of the members in one way or another. If you are not in a leadership position, I would like to invite you to identify those decisions you make that impact your team. If you are a leader, it might be easier for you. \ Seeing how our decisions have an impact over others, requires to put ourselves on someone else shoes first. Empathy is a human quality underrated these days. That is why I don'92t think it is a matter of being a leader or not. Any role at the workplace requires empathy, not because of the role, but because we are humans. \ I like to use empathy as a way of introducing a concept that I will described in the next chapter, **the whole self.** \ When we connect with empathy, we start exploring what we called **#emotionalIntelligence**. This type of intelligence is something unique, that only humans can develop over any machine. Our emotions and the intelligence emerging from them are a human super power, and we haven't explored as its full potential yet. \ As changes emerge everyday, as machines expand their role in society, we are all invited to explore those human capabilities that make us unique. Capabilities that we haven't explored deeply yet. Emotional intelligence is one of them. \ Expressing emotions or using them as an intelligence aspect is not common at work. Most of our roles are purely rational, logic and sequential. Facts and numbers don't give a room for emotional intelligence. While in my view, they can work together. \ **We usually use numbers and facts to make decisions, and use the same rational intelligence to execute them 🤔** \ Let's use an example. Your client is arguing with you about how the cost of the project got over the planned numbers. He is very anger and eventually that emotion triggers in you the same emotion, because you have been working so many hours on this project, just to get the client focused only on what is not working instead of what it is. \ **Emotions without emotional intelligence are contagious**. You can imagine how an argue like this can end. Everyone gets more frustrated than when started. Nothing got really solved in a conversation like this. **\ This frustration and anger goes with you and your client to your homes and families get impacted with it**. Kids slept badly and had a bad day at school. They might misbehaved at school and another kid might be impacted from it. The other kid's mom gets worried about your kid and her kid interaction that day and she brings that worry into another home and family. And so on. \ Let's start again. You client is arguing with you about how the cost of the project got over the planned numbers. **This time you decided to use** your unique human capability, **emotional intelligence**, specifically **empathy** 🩷 \ You keep silence and just listen to the argument. By **paying attention at the words being used and the gestures** you realized this person is under a lot of stress. By going deeper in your listening, your intuition can tell, there is something else going on. \ When the person stop complaining, you bring back the story told by your client, adding the emotions you could feel while listening. **You put yourself in your client shoes**. \ It is inevitable that, when we approach a situation with emotions, the person connects immediately with them. **The client feels listened and emotionally connected with you**. From there, you start exploring what else is going on, from a genuine point of view. The conversation goes in deep and you both find you are going under a lot of stress for things at work and at your personal level. \ You both decide to talk about this issue the next day, with a refresh mind and a common goal, to find a solution for both. \ As you can see, **there is a totally different impact of making a decision of using or not using your emotional intelligence capability**. **🌱 And this example could apply to a leader or a team member. 🌱** **🌱Everyone in a team makes decisions that impact others. And emotional intelligence is not only for leaders. 🌱** \ This simple example wants to bring awareness about how important is to explore emotional intelligence as individuals and expand it a teams, organizations and companies levels. \ **We can't bring emotional intelligence to work, if we, as individuals, don't feel comfortable to connect with our own emotions**. **Empathy requires us to stay fully (and sometimes uncomfortably) connected with emotions.** That requires another important aspect of emotional intelligence **which is our capability of staying present, self aware of our body and what is triggering frustration, anger or sadness as a result of an external stimulus**. \ **As our environments keep changing on daily basis, our brains are invited to create new neuron connections**, this process triggers emotions under the unexpected. Our capability to connect with your emotions and managing them in our favor can make this adventure of navigating change, easier for us and the people around. \ \ **And it is bringing a new self at work, your personal one**. Who comes with all your professional expertise as well as your unique capabilities as a human. \ **Let's explore in our next chapter how this personal self is emerging at workplaces and by integrating it with your professional self, can bring your whole self at workplaces.** **By using LEGOs we can bring new perspectives, deep listening and spark more creative solutions.** So step by step, we made our workplaces more human. **Deep listening breaks down walls.** **And that is what The World 🌎 strongly needs these days.** Stay colorful, \ Laus #nostr #Consciousness #grownostr #emocionalintelligence #leadership #consciousleadership #emotions #decisionmaking #DeepListening #Teambuilding #clientservice #PlayingLegos #Legos

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I was talking to a friend the other day about AI, and we hopped onto the open vs. closed-source debate. That’s when it hit me, we are at a turning point. A year ago, AI conversations were about awareness. Then came corporate adoption, innovation, and regulation. Today governments are stepping in to decide how AI’s benefits will be distributed and who gets to control them. We are no longer trying to figure out if AI will transform society. That is a given. The big worry is control. Right now, a few trillion-dollar corporations and state-backed labs dictate its trajectory, wrapped in secrecy and optimized for profit. Open-source AI stands as the antithesis to closed systems, a bulwark against AI monopolization, ensuring intelligence remains a public good rather than a private weapon. It's time to look beyond the technical debate of open vs closed source AI. This is a humanitarian issue at stake. ### Why Open-Source AI is Non-Negotiable A couple of years ago, I was consulting an airline on their black box. They were really sweet, let me play around with their test-flight hydraulic chambers, and I crashed it quite a bit (There is something deeply impressive about people who can actually fly planes). But when it comes to the black box, that is the most secretive part. It holds critical data, tracking exactly how the plane was controlled throughout the flight. If it goes missing, nobody can say for certain what went wrong, especially if there are no survivors. For years, there has been debate over real-time data transmission vs. privacy in aviation. It is the same debate we are having now about open-source vs. closed-source AI. Closed-source AI is a black box. No one outside the company knows how it makes decisions, what biases are baked into its training, or how its outputs are being manipulated. AI models are only as good as the data they are trained on. If you burned all books except a few praising Government A and Emperor Q, then that is all people would know. AI takes it a step further. It learns what works best for you, adapting its bias so seamlessly that it fits within your comfort zone. Open-source AI breaks this cycle. It allows diverse contributors to spot and correct biases, ensuring a fairer, more representative development process. No single entity gets to dictate how AI is used, who has access to it, or what information it filters. Historically, open systems have always outpaced proprietary ones in long-term innovation. The internet itself (TCP/IP, HTTP, Linux) was built on open principles. AI should be no different. If intelligence is widely accessible, breakthroughs happen faster. And society as a whole benefits. ### The Companies Leading the Shift Some companies see open-source AI as a risk. Others recognize it as an ethical necessity and an advantage. Block is leading the open-source cultural momentum right now for companies. Jack’s recent [letter](https://s29.q4cdn.com/628966176/files/doc_financials/2024/q4/Shareholder-Letter_Block-4Q24pdf.pdf), written in his usual Hemingway-esque style and highly substantial, explained this well. He is taking on a first principle approach, rewiring corporate DNA to embrace open collaboration and accelerate innovation as a whole. They developed Goose, an open-source AI agent (initially built as an internal workflow tool), at a pace comparable to AI-first companies like Google, proving that open collaboration doesn’t slow development. If anything, it accelerates it. I like how Block is infusing open-source principles **AND** doubling down on its core business **AND** building a solid innovation roadmap. They capture the essence of open source in terms of curiosity, creativity, and a passion for problem-solving beautifully. This cultural shift is something that even big conglomerates like Intel, despite decades of contributions to open-source projects, have struggled with. They often get bogged down in technical silos rather than establishing actual collaboration. As [Arun Gupta, vice president and GM of open ecosystems at Intel](https://www.intel.com/content/www/us/en/developer/articles/community/how-to-build-open-source-culture-in-your-company.html), put it, “*The best way to solve the world's toughest problems is through open collaboration*,” but he also acknowledges the challenge of incentivizing contributions in large organizations. Compare this to OpenAI. Elon’s long-standing beef with them is rooted in the fact that they started with an open mission but switched to a closed model the moment profitability entered the chat. But in recent days, with [Satya Nadella](https://x.com/8teAPi/status/1892383248661274699) doubling down on quantum computing, I wonder if Microsoft is prioritizing quantum over AI? And is closed-source AI actually slowing innovation compared to an open approach? Would be interesting if Elon actually buys OpenAI for almost $100B as his investors recently put out, but if he does, would he open source it ? Most companies struggle to balance open-source contributions with business sustainability. But many others aren’t. RedHat isn’t an AI company, but it built a billion-dollar business on open-source software and became IBM’s greatest asset (and their saving grace). Let’s look at more open source AI companies. Hugging Face has become the go-to hub for AI models, creating an ecosystem where developers, researchers, and enterprises collaborate. Mistral is proving that open-source AI can be both epic and lightweight through its modular models. Stability AI is making powerful generative models widely accessible, directly competing with OpenAI’s DALL.E. It recently raised over $100M in venture funding, and with James Cameron joining the board, it’s doubling down on gen AI for everything from text-to-image to CGI. DeepSeek shocked the world with an open-weight AI model that rivals top proprietary LLMs, on a fraction of the compute. [Andrej Karpathy ](https://x.com/karpathy/status/1872362712958906460)pointed out that DeepSeek-V3 achieved stronger performance than LLaMA 3 405B, using 11 times less compute. While mainstream AI labs operate massive clusters with 100K GPUs, DeepSeek pulled this off with just 2048 GPUs over two months. If this model passes more 'vibe checks' (as Karpathy put it), it proves something critical, that we’re still far from peak efficiency in AI training. Meta is also one of the biggest contributors to open-source AI and benefits from the widespread adoption of its models. They’ve released several powerful AI models like LLaMA, Segment Anything Model (SAM), AudioGen & MusicGen, and DINO (Self-Supervised Vision Model). Unlike OpenAI and Google, which keep their most powerful models closed, Meta releases open-weight models that researchers and developers can build upon. All these companies are proving that open-source AI is not an ideological stance. It’s a cultural movement and a commercially viable force. Open-source AI may have started as the ethical choice, but it’s increasingly clear that it’s also the smarter one. ### Open-Source AI as a Humanitarian Mission The stakes for open-source AI go far beyond business models and market competition. It’s about ensuring that AI serves people rather than controls them. Without it, we put our future at risk where only state-approved AI systems generate content, answer questions, and curate knowledge. Governments are already deciding how the public can use AI while conveniently reserving unrestricted access for themselves. In China, generative AI models must align with *Core Socialist Values*. In the US, *Executive Order 14110* was to regulate AI for “safe and ethical development” but was rescinded, leaving its future uncertain. In the EU, the *Artificial Intelligence Act (AI Act)* dictates what is considered "safe," with no real public say. In Russia, AI tools assist in monitoring online activity and censoring content deemed undesirable by the government. AI-driven censorship, mass surveillance, and digital manipulation are no longer hypothetical or something you read in dystopian novels. They are happening now. Open-source AI is the anchor. This is where the people stand up for the people. Where true democracy reigns. Intelligence is power and keeping AI open is the only way to keep power decentralized. Our conversations must go beyond AI as a “digital solution". Freedom and autonomy of our mind is ours to keep. Companies embracing open-source AI are securing a future where intelligence serves humanity rather than the other way around. But pitchforks are rising. Will the people win?