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🚀New Case Study: How SV2 Increases Mining Profits by at least 7.4% improving: 📊Share Acceptance 🟩Block change latency 🧑‍🏭Job latency ⬛️Block propagation 🥷Hashrate hijacking A community research with many contributors led by @HashlabsMining @DEMAND_POOL and SRI. 🔗Link 👇

Stratum V2

3,494 subscribers

41,826 görüntüleme • 1 yıl önce •via X (Twitter)

Anya Rossi• Live Now

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Stratum V21 yıl önce

Read the full case-study on our @X blog⛏️

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Stratum V21 yıl önce

Big thanks to everyone who made this community-driven study possible. @Alenmakhmetov @bitentrepreneur @kenobigeneral5 @chicodurden21 @dev_sv2 @lorban6 @jmellerud @pavlenex @moneyball @gitgab19 @plebhash average_gary @JakubTrnka14 @JBeddict @TheBlueMatt @PortlandHODL @pavlenex Sjors Provoost Special shout out to @HashlabsMining!

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Stratum V21 yıl önce

Case-study is also available on our SV2 blog

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Stratum V21 yıl önce

Miners, we want your feedback. This study covers just a few KPIs, as our tools improve, more insights are coming. If you’re interested in validating results or contributing data, we’d love to hear from you. Hop onto our Discord!

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Hashlabs1 yıl önce

@DEMAND_POOL We look forward to using Stratum V2 and gaining higher miner revenue and profitability.

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Pavlenex1 yıl önce

@HashlabsMining @DEMAND_POOL What a great collaborative effort! Thanks everyone for helping shape this!

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DMND1 yıl önce

@HashlabsMining LFG! This is the way forward for the next 1.000 years of mining.

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Stratum V21 yıl önce

@HashlabsMining Thanks for participating and helping shape the research🤝

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Jaran Mellerud 🇳🇴⛏️1 yıl önce

@HashlabsMining @DEMAND_POOL Great case study. The mining protocol of the next 1,000 years.

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Stratum V21 yıl önce

@HashlabsMining @DEMAND_POOL Thanks for your help!

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Darknight Labs ⬛️

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learned a lot from this conversation with Simon Mo and Matt Bornstein. biggest takeaways for me: -there are a lot of reasons why we should like open-weight models. a lot of these arguments stop at handwavy things like "what if the labs stop releasing frontier models to the public" or "it's lower cost." but simon's position as lead maintainer of vLLM and CEO of Inferact give him authority to talk about some of the other, more interesting and concrete reasons to pay attention to open-weight models, namely that they allow end-users to calibrate latency / other performance metrics with way more customizability than what any of the frontier closed-source labs offer (and without the fear that your job might be met with a refusal at some random point where you're deep in a 2 hour job) -re: the above point...for this reason, a lot of US companies (inferact included!) choose to use open-weight models over their closed-source alternatives. this also isn't limited to internal workloads / research - on a recent a16z podcast the team at Decagon spoke about how something like 90% of their customer service ai agents run on open-weight models that they've fine-tuned. -we should really appreciate how many companies/teams came out researchers fascinated by the wave of very small open-weight models that were being distilled from e.g. gpt-3.5 and earlier models in 2022/2023 (prior to the release of chatGPT!). these small models motivated the development of pagedattention, which then led to vlmm/inferact (at other layers of the stack with similar origin stories, you can look at teams like openrouter or ollama). in other words, we have open-weight models to thank for a bunch of the orchestration infra we now rely on. i think yet another, indirect, way we can point to open-source/weight infra pushing the frontier forward. anyway, a lot more in this convo, it was a lot of fun!

learned a lot from this conversation with Simon Mo and Matt Bornstein. biggest takeaways for me: -there are a lot of reasons why we should like open-weight models. a lot of these arguments stop at handwavy things like "what if the labs stop releasing frontier models to the public" or "it's lower cost." but simon's position as lead maintainer of vLLM and CEO of Inferact give him authority to talk about some of the other, more interesting and concrete reasons to pay attention to open-weight models, namely that they allow end-users to calibrate latency / other performance metrics with way more customizability than what any of the frontier closed-source labs offer (and without the fear that your job might be met with a refusal at some random point where you're deep in a 2 hour job) -re: the above point...for this reason, a lot of US companies (inferact included!) choose to use open-weight models over their closed-source alternatives. this also isn't limited to internal workloads / research - on a recent a16z podcast the team at Decagon spoke about how something like 90% of their customer service ai agents run on open-weight models that they've fine-tuned. -we should really appreciate how many companies/teams came out researchers fascinated by the wave of very small open-weight models that were being distilled from e.g. gpt-3.5 and earlier models in 2022/2023 (prior to the release of chatGPT!). these small models motivated the development of pagedattention, which then led to vlmm/inferact (at other layers of the stack with similar origin stories, you can look at teams like openrouter or ollama). in other words, we have open-weight models to thank for a bunch of the orchestration infra we now rely on. i think yet another, indirect, way we can point to open-source/weight infra pushing the frontier forward. anyway, a lot more in this convo, it was a lot of fun!

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Boomer News Network Presents: "Onboard A Boomer!" 🚀 Boomers have been the cornerstone of our society, and many are curious about crypto but unsure where to begin. Let’s make it easier—and more rewarding—for them to take that first step! Together, we can welcome Moms, Dads, Aunts, Uncles, Colleagues and Peers onchain via Base. How it Works: When the Boomer you onboard purchases $BOOMER on Base and holds it for 30 days, both of you are rewarded. You'll earn a total of 5% back on their purchase, with 2.5% going to you and 2.5% to the Boomer. The combined reward for both of you is capped at $100. For example, if the Boomer you bring into the community purchases $2,000 in $BOOMER, you both would receive $50 each. To Participate: 1️⃣ Onboard a new Boomer into the community by having them buy at least $100 worth of $BOOMER (must hold for 30+ days). 2️⃣ Share a fresh post (photo or video) proudly showcasing the Boomer you onboarded—bonus points for creativity! 3️⃣ Submit your post, your wallet, and the transaction ID link in the comments below. 4️⃣ Follow BOOMER and retweet this post to spread the word. Important Details: 🏆 Rewards go to the wallet you submit and the address in the transaction. 💫 This offer is only available to the next 100 newly onboarded Boomers! 💬 Remember: This isn't financial advice; we're all about memes and community here! As a special bonus, the top 10 largest new holders and the top 10 most successful onboarders will each receive an exclusive OK Boomer. Let’s join forces to make crypto accessible to everyone and build a movement together!

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$AMD $MSFT Partnership is MASSIVE in 2026 🚀 If you were excited about my thread on $AMD $AMZN AWS long time partnership, you will be even more excited about what Microsoft gonna do with 2026 AMD EPYC "Venice". Historical Context: The relationship between AMD and Microsoft began in the early 2000s, with Microsoft initially focusing on Intel's x86 architecture for its Windows operating system and server products. However, AMD's entry into the server market with its Opteron processors in 2003 marked the beginning of a competitive dynamic that eventually led to collaboration. The partnership intensified with the launch of 3rd Generation EPYC "Milan" in 2021, powering Azure's N2D and C2D VM families. By 2025, Microsoft had integrated 5th Generation EPYC "Turin" into new compute-optimized instances, reflecting a strategic shift towards AMD for cost and performance benefits. This "Secret Weapon" breakthrough will mark another inflection point for AMD Microsoft Azure relationship, will probably be more aggressive than EPYC "Milan" moment in 2021. We can call it EPYC "Venice" moment 2026" 1. Technical performance of AMD EPYC "Venice" (2026) AMD's 6th Gen EPYC "Venice" processors, slated for 2026, introduce New Chiplet design breakthrough. a revolutionary chiplet interconnect fabric that redefines server scalability for AI. This isn't just faster silicon; it's a paradigm shift for Microsoft Azure , enabling hyper-efficient, rack-scale AI inference that slashes costs and latency while boosting throughput. ~Up to 256 Zen 6 cores, a 70% performance increase over "Turin," optimized for AI and HPC. ~Memory and Bandwidth: 1.6 TB/s per socket, doubling "Turin's" capability, with support for MR-DIMM/MCR-DIMM. ~Efficiency: 1,500-1,700W power draw, a 50% reduction, aligning with Microsoft's sustainability initiatives. ~Interconnect: PCIe 6.0 and a new chiplet fabric for rack-scale AI, reducing latency and enhancing scalability. 2. Why $MSFT will adopt $AMD YPYC Share to 50%+ in 2026. AMD EPYC Share: ~30-35% of Azure's x86 CPU-based business while Intel Xeon share is 65% Microsoft's Azure has been progressively integrating AMD EPYC, with "Venice" expected to expand this footprint: A. Dominance of AI Inference Workloads ~AI inference constitutes 80% of AI workloads in cloud environments, with latency-sensitive applications like chatbots, recommendation engines, and fraud detection requiring sub-second response times. ~"Venice's" 35x inference performance uplift directly addresses these requirements, outperforming Intel's offerings and custom Arm solutions in multi-threaded scenarios. B. Cost Efficiency and Operational Savings ~Azure's 2025 capex of $118B is under pressure to deliver returns. "Venice" can reduce operational expenses by $20-30B annually due to its power efficiency and performance gains, improving Azure's margins to 35-40%. ~The cost per inference operation is significantly lower with "Venice," estimated at 24-31% less than Intel-based alternatives, enhancing Azure's competitiveness against AWS and GCP. C. Scalability for Enterprise AI: ~"Venice" supports rack-scale AI deployments, enabling Azure to scale AI services for enterprise customers. For example, a 1,000-node cluster can process 700,000+ tokens per second, crucial for large-scale AI applications like personalized marketing and predictive analytics. ~This scalability is particularly important as Azure aims to capture the $100B+ AI opportunity by 2026, as stated by Microsoft CEO Satya Nadella. D. Reduction of Nvidia Dependency ~While Nvidia ( $NVDA) dominates AI accelerators, AMD's integrated EPYC-GPU solutions (MI450 with "Venice") offer a balanced approach, reducing Azure's reliance on Nvidia's high-cost GPUs. ~"Venice" enables hybrid inference models, where CPU-based inference handles 80% of workloads, and GPU acceleration is reserved for training and complex tasks, optimizing resource allocation. 3. Financial Implication: ~Revenue from Azure could reach $15-18B annually by 2026, part of a total revenue projection of $70-100B ~Profit margins could improve to 55-60%, boosting net income to $20-25B, supported by scale economies and reduced production costs. Intel could respond by giving more aggressive discounts, but this breakthrough has been a decade long of $AMD R&D, or rethinking chiplet design, a complete new approach. "Venice's" lead in AI inference and efficiency is challenging to match. Broader Industry: Other hyperscalers ( Amazon Web Services , GCP) and enterprises will follow Azure's lead, standardizing EPYC technology and pressuring Intel further. This could lead to a broader industry shift towards AMD, enhancing its ecosystem and bargaining power. Conclusion: The strategic adoption of AMD's 6th Generation EPYC "Venice" processors by Microsoft Azure in 2026 marks a pivotal moment in the evolution of cloud computing, particularly for AI inference capabilities. "Venice's" groundbreaking chiplet design, offering a 35x performance uplift for AI inference tasks, a 50% reduction in power consumption, and unparalleled scalability, positions Azure to leapfrog its competitors in the race for AI dominance. This technical superiority, combined with significant cost savings potentially $20-30B annually in operational expenses; aligns perfectly with Microsoft's ambitions to capture the $100B+ Revenue AI opportunity by 2026. The shift to 50% x86 market share for AMD within Azure is not merely a technical transition but a strategic realignment that redefines the competitive landscape. Historically, Microsoft's partnership with AMD has evolved from niche deployments to a core component of Azure's infrastructure, and "Venice" accelerates this trend. The 30-35% AMD EPYC share in 2025 is expected to double, driven by new VM families like C4D and H4D, which will dominate AI-intensive and HPC workloads. This migration is incentivized by "Venice's" efficiency gains, reducing dependency on Intel and Nvidia, and enhancing Azure's sustainability profile. Not Financial Advice!

Mike

141,018 görüntüleme • 11 ay önce

I want to clarify something about posting about the statues or figures. I don't sell the Resident Evil products, statues, or figures that I post. I only share information and links about new pre-orders that might interest the community, as I'm also a collector. Many large Resident Evil community accounts also share them, both licensed and unlicensed. I also help inform the community on how to get official Resident Evil merchandise from Japan by translating for them. is one of the largest statue shops out there (they're a shop, they don't manufacture the figures), and I've also bought from their site before and received the figure. If people are curious, they can just check out the studio's other statues/busts on the Orzgk website or at other reputable retailers that also sell the SAME figure. You can also wait for the first photos and/or videos of the statues in person; many studios provide these to retailers after pre-orders close. In case they cancel the project, they'll refund your money in full. So, to everyone who insults me, do your research before accusing me of sharing potential "scams" or creating the "conceptual" images that the studio shares of its products. I don't use AI in my posts or in the edits I make (posters, collages, etc.). Besides, X has an AI detector and flags posts if you created something with AI (it can't be disabled even if you have a verified account). • Here's a video of the finished Requiem replica. You can see more on the official IG account:

I want to clarify something about posting about the statues or figures. I don't sell the Resident Evil products, statues, or figures that I post. I only share information and links about new pre-orders that might interest the community, as I'm also a collector. Many large Resident Evil community accounts also share them, both licensed and unlicensed. I also help inform the community on how to get official Resident Evil merchandise from Japan by translating for them. is one of the largest statue shops out there (they're a shop, they don't manufacture the figures), and I've also bought from their site before and received the figure. If people are curious, they can just check out the studio's other statues/busts on the Orzgk website or at other reputable retailers that also sell the SAME figure. You can also wait for the first photos and/or videos of the statues in person; many studios provide these to retailers after pre-orders close. In case they cancel the project, they'll refund your money in full. So, to everyone who insults me, do your research before accusing me of sharing potential "scams" or creating the "conceptual" images that the studio shares of its products. I don't use AI in my posts or in the edits I make (posters, collages, etc.). Besides, X has an AI detector and flags posts if you created something with AI (it can't be disabled even if you have a verified account). • Here's a video of the finished Requiem replica. You can see more on the official IG account:

ᴋᴛʏɴʏ | ᴋᴀᴛʜʏᴀɴʜʏ 🌿

14,714 görüntüleme • 6 ay önce

$NVDA $GFS NVIDIA’s reported agreement to acquire Groq for $20B in cash (per CNBC, amplified via Reuters and other wire coverage) represents a materially different strategic posture than NVIDIA’s prior M&A pattern, given both the headline size (largest reported NVIDIA acquisition to date) and the unusual carve-out that Groq’s early-stage cloud business would not be included. Public reporting indicates the information originated from Alex Davis, CEO of Disruptive (lead investor in Groq’s latest financing), and that neither NVIDIA nor Groq had issued an immediate confirmation at the time of publication. The same reporting frames the transaction as coming together quickly, only months after Groq raised $750M at a ~$6.9B valuation, and highlights Groq’s positioning as a high-performance inference chip vendor founded by ex-Google TPU engineers. Groq is best understood as a vertically integrated inference acceleration company whose core asset is an application-specific processor optimized for deterministic, low-latency execution of transformer-style workloads, paired with a compiler-led software stack and a distribution layer (GroqCloud) designed to reduce developer friction via OpenAI-compatible APIs and integrations. Groq brands its architecture as a Language Processing Unit (LPU) and consistently emphasizes that the design target is inference, not training. The company’s own architecture description centers on 1-core execution, large on-chip SRAM used as primary storage (explicitly not cache), a custom compiler that statically schedules compute and communication, and direct chip-to-chip connectivity intended to coordinate multi-chip execution without relying on conventional caching hierarchies or dynamic runtime scheduling. The technical premise is a deliberate inversion of the conventional GPU approach. GPUs deliver throughput via massively parallel, multi-core execution with dynamic scheduling, complex memory hierarchies, and heavy reliance on off-chip HBM bandwidth and sophisticated runtime/kernel optimization. Groq instead argues that inference bottlenecks are driven by latency variance (tail latency), synchronization overhead, and memory access unpredictability inherent in dynamically scheduled, cache-heavy architectures, particularly when workloads are latency sensitive and batch sizes cannot be inflated. Groq’s solution is to move “control” into the compiler: the full execution graph and inter-chip communication schedule are computed ahead of time down to clock-cycle granularity, with deterministic execution designed to reduce run-to-run variance. In Groq’s framing, the removal of caches, reorder buffers, speculative execution overhead, and other sources of contention enables predictable latency and high utilization without per-model kernel engineering typical of GPU tuning cycles. A critical nuance is that Groq’s determinism is not merely a software claim; it is tightly coupled to architectural constraints and system design choices that trade flexibility for predictability. Third-party technical commentary indicates Groq’s chip uses a fully deterministic VLIW-style approach with minimal buffering, no external memory, and heavy dependence on sharding models across many chips because on-chip SRAM capacity is limited. SemiAnalysis describes a ~725 mm^2 die on GlobalFoundries 14nm with ~230MB of SRAM and notes that “no useful models” fit on a single chip, forcing multi-chip partitioning for modern LLMs and driving a system-level design where networking and compilation are first-class scheduling problems rather than ancillary infrastructure. This is consistent with Groq’s own messaging that tensor parallelism across chips is a primary design goal, enabled by large on-chip SRAM and compile-time coordination of compute plus interconnect. The on-chip SRAM emphasis is central to Groq’s latency story and also its most constraining trade-off. Groq claims on-chip SRAM bandwidth “upwards of 80 TB/s” and contrasts that with off-chip HBM bandwidth “about 8 TB/s,” asserting a potential 10x advantage from bandwidth plus reduced trips across chip-to-memory boundaries. While these comparisons are marketing-oriented and depend on workload specifics, the architectural implication is clear: Groq prioritizes ultra-fast local weight/activation access and then scales capacity by adding chips, not by attaching large off-chip memory pools. This design can reduce latency for sequential inference layers and minimize unpredictable stalls, but it pushes complexity into partitioning strategy, interconnect topology, and compiler scheduling, and it increases the number of chips needed for very large parameter counts and large KV-cache footprints. Groq also highlights numeric formats and compiler-driven precision management as a performance lever. In its 2025 technical blog, Groq describes “TruePoint numerics,” including 100-bit intermediate accumulation and selective quantization choices (FP32 for attention-sensitive operations, block floating point for MoE weights, FP8 storage in error-tolerant layers), and claims 2-4x speedups versus BF16 without measurable accuracy degradation on benchmarks such as MMLU and HumanEval. Even if the absolute uplift is workload dependent, the strategic point is that Groq is pursuing performance via end-to-end co-design: precision policy is not just hardware capability (FP8/BF16) but compiler-enforced mapping of precision to error sensitivity, which can matter materially for inference cost-per-token if it reduces memory traffic and boosts throughput without forcing aggressive, accuracy-damaging quantization. Independent performance datapoints indicate Groq has been credible on latency-oriented inference speed, at least for certain regimes. EE Times reported in 2023 that Groq demonstrated Llama-2 70B inference at ~240 tokens/s per user on a cloud-based dev system described as 10 racks and 64 chips, using the company’s 1st-gen silicon introduced several years earlier. Separate Groq commentary around independent benchmarking cites results showing ~241 tokens/s throughput and ~0.8s time to receive 100 output tokens for a Llama-2 70B API configuration, positioning the platform as a step-change in “available speed” for certain interactive use cases. These figures do not settle total cost-of-ownership versus GPUs or hyperscaler ASICs, but they establish that Groq’s system-level architecture can deliver strong single-user throughput and latency on large models when properly partitioned and scheduled. GroqCloud is the commercial wrapper that packages this hardware/software stack as “tokens-as-a-service,” aiming to make Groq adoption feel like switching API endpoints rather than adopting new silicon. Groq’s documentation states its API is designed to be “mostly compatible” with OpenAI client libraries, and its pricing page provides model-specific token rates, published speeds (tokens/s), prompt caching discounts, and batch processing discounts. For example, pricing lists inputs as low as $0.05 per 1M tokens and outputs as low as $0.08 per 1M tokens for certain smaller LLM configurations, with higher prices for larger models and long-context or MoE variants; it also advertises prompt caching with a 50% discount on cached input tokens for certain models and a batch API offering 50% lower cost for asynchronous processing windows. These mechanics are economically important because they demonstrate Groq’s go-to-market is not simply “sell chips,” but “sell predictable unit economics per token,” with tooling (batch, caching) that directly targets inference cost drivers (reused prompts, throughput smoothing, and asynchronous workloads). The cloud footprint and distribution partnerships indicate Groq has been building an inference-native “edge within the cloud” strategy rather than competing head-on with hyperscalers on breadth of services. A 2025 Groq newsroom release describes a European deployment in Helsinki with Equinix, positioned as latency reduction and data governance for European customers, and explicitly references Equinix Fabric enabling private connectivity to GroqCloud over public, private, or sovereign infrastructure. The same release enumerates additional capacity in the U.S. (Equinix, DataBank), Canada (Bell Canada), and Saudi Arabia (HUMAIN), and states these sites collectively served more than 20M tokens/s across Groq’s global network at that time. That supply-side metric matters because it provides a directional sense that Groq is scaling capacity as a network, not merely as a chip vendor. Customer disclosure is inherently limited because Groq is private and many enterprise deployments are not public, but Groq’s marketing materials and partnerships provide signals about demand vectors. The company’s public website displays logos of large consumer and enterprise brands (e.g., Dropbox, Vercel, Chevron, Volkswagen, Canva, Robinhood, Riot Games, Workday, Ramp) and includes a published customer quote claiming a 7.41x chat speed increase and an 89% cost reduction after moving to GroqCloud, followed by a tripling of token consumption. While marketing claims should be treated as case-specific and not generalized, they indicate that Groq is targeting both AI-native developers (who measure success by latency and cost-per-token) and enterprise buyers (who care about predictable performance and governance). Supplier and dependency mapping for Groq spans 3 layers: silicon production, system integration, and cloud infrastructure. On silicon, third-party analysis indicates GlobalFoundries 14nm for the 1st-gen Groq chip, implying a supply chain less constrained by the most capacity-tight leading-edge nodes and advanced packaging bottlenecks that dominate high-end GPU supply (HBM stacks, CoWoS-type packaging constraints). If accurate, this is strategically meaningful because it suggests Groq capacity expansion could be gated more by conventional wafer supply, board assembly, and data center power than by the same HBM/advanced packaging scarcity that has constrained top-tier GPU ramp cycles. On systems and cloud, Groq’s own releases identify colocation and connectivity partners (Equinix, DataBank, Bell Canada) and a Middle East partner (HUMAIN), implying dependencies on data center real estate, power availability, and network connectivity, alongside procurement of standard server components, NICs/switching, racks, and cooling infrastructure. The Groq design narrative also emphasizes air cooling and reduced need for complex power/cooling infrastructure, which—if realized in deployments—can widen the set of feasible hosting locations and lower deployment friction relative to liquid-cooled, very high power density GPU racks. Against that backdrop, the strategic rationale for NVIDIA acquiring Groq can be framed as a set of overlapping objectives: inference silicon optionality, architectural hedging, competitive defense, and supply chain diversification, with the carve-out of GroqCloud signaling a preference to avoid direct cloud competition and to focus on IP and product portfolio control rather than operating a capital-intensive token-serving business. The deal, if confirmed, would occur at a valuation step-up of ~190% versus Groq’s reported ~$6.9B private valuation in the September $750M round, reinforcing that any acquisition logic would be predominantly strategic rather than a conventional financial multiple arbitrage. The most compelling strategic driver is inference. Training has historically been the center of gravity for cutting-edge GPU demand, but inference volume is structurally larger and more distributed as deployments scale, with economics dominated by cost-per-token, latency guarantees, and utilization under spiky demand. Inference workloads also create a strategic vulnerability for NVIDIA: hyperscalers and large platforms can justify bespoke ASICs (TPU, Trainium/Inferentia, Maia-class efforts) because inference is stable, repeatable, and can amortize software investment at massive scale. Groq’s core proposition—deterministic, compiler-scheduled inference with predictable latency—aligns directly with the segment where GPU generality is least valued and where “good enough” programmability plus superior unit economics can win share. Acquiring Groq would allow NVIDIA to own a credible inference-native architecture rather than relying solely on GPUs and software optimization to defend that segment. Competitive defense logic is also plausible. Groq occupies a specific competitive wedge: low-latency, high-throughput interactive inference, delivered via a simple API abstraction that reduces switching cost. That wedge directly pressures GPU inference margins in the long run because it makes inference price/performance comparisons more transparent at the token level, and it targets a developer persona that historically defaulted to CUDA-first ecosystems. Even if NVIDIA’s current-generation systems can achieve very high tokens/s per user with extensive optimization, the strategic risk is that competing architectures normalize the idea that inference is best served by special-purpose silicon with a simpler programming model, weakening CUDA lock-in at the application layer. NVIDIA has actively demonstrated that Blackwell-era systems can exceed 1,000 tokens/s per user in benchmarked configurations, but that performance leadership does not automatically translate to lowest cost-per-token across the full range of batch sizes, latency targets, and deployment environments. Groq’s existence as a credible alternative architecture forces NVIDIA to keep defending inference economics rather than only raw performance leadership. The “technology acquisition” rationale is unusually strong in this specific case because Groq’s differentiator is not a single block of silicon IP but an end-to-end methodology: compiler-led static scheduling, deterministic networking, and a system architecture designed around tensor-parallel inference rather than throughput-maximizing batch inference. NVIDIA’s stack is already compiler-heavy (TensorRT, Triton, CUDA graphs, kernel fusion, speculative decoding techniques), but GPUs remain dynamically scheduled devices with complex memory hierarchies and stochastic latency behaviors under contention. Groq’s approach provides an alternate design point: treating the entire inference execution (compute plus communication) as a statically schedulable program. In principle, that IP could be valuable even if Groq silicon itself is not adopted at massive scale, because it can inform how NVIDIA builds future inference-optimized products, compilers, and networking fabrics, especially as distributed inference with large models makes communication a first-order performance determinant. Supply chain diversification is a non-obvious but potentially important driver. If Groq’s mainstream product generation is truly based on a mature process node and avoids HBM, then the scaling constraints look different than those of state-of-the-art GPUs. NVIDIA’s ability to meet incremental demand has been tightly coupled to advanced packaging and HBM supply, and those constraints can remain binding even when wafer supply is available. An inference ASIC architecture that relies primarily on on-chip SRAM and scales by adding chips—while not costless—could reduce dependence on HBM availability and advanced packaging capacity, enabling NVIDIA to ship “inference capacity” in higher absolute volumes or into geographies and customer segments where the highest-end GPUs are economically or logistically difficult to deploy. This could be particularly relevant for latency-sensitive inference deployed in regional colocation footprints rather than centralized hyperscale campuses. The carve-out of GroqCloud, if accurate, is itself a strategic signal about NVIDIA’s priorities. Operating a token-serving cloud at scale is capital intensive, structurally lower margin than silicon IP rents, and creates channel conflict with hyperscalers and CSP partners who are core NVIDIA customers. NVIDIA has generally positioned its cloud offerings through partnerships rather than as a direct hyperscale competitor. Excluding GroqCloud would preserve neutrality with CSPs and avoid inheriting multi-region data residency obligations and partner contracts, while still allowing NVIDIA to acquire Groq’s silicon, compiler technology, and engineering talent. At the same time, excluding GroqCloud would also mean NVIDIA would not automatically acquire the commercial proof-point of Groq’s unit economics or the customer contracts that validate product-market fit at scale, increasing the importance of diligence on whether Groq’s cloud pricing is structurally profitable or partially subsidized by fundraising. There is also a “preemptive acquisition” angle. The reporting identifies recent investors in Groq’s latest round including large financial institutions and strategic/industry players. In that context, Groq represents an asset that could plausibly have been acquired by a competitor (AMD/Intel) or by a hyperscaler seeking to accelerate inference independence. NVIDIA acquiring Groq could be a defensive move to prevent a credible inference-native architecture from being weaponized by a rival with deep distribution. Even if GroqCloud is carved out, controlling the silicon roadmap and compiler IP would meaningfully constrain Groq’s ability to evolve into a standalone competitor, unless the carved-out entity retains long-term rights to the hardware and software stack. However, the strategic case is not one-sided; there are meaningful risks and potential contradictions that would need to be reconciled for the transaction to be value-accretive on a multi-year horizon. 1st, Groq’s architecture appears to rely on scaling out chip count to achieve capacity, which introduces system cost, networking complexity, and physical footprint considerations. The absence of external memory and limited on-chip SRAM implies very large models require substantial chip parallelism, and the economics then depend heavily on chip cost, yield, power efficiency, and interconnect overhead. SemiAnalysis explicitly frames Groq as trading space for time and raises questions about token economics and whether publicly advertised pricing reflects fully loaded costs or market share capture. 2nd, integration risk is non-trivial. Groq’s compiler-led deterministic model is philosophically and practically different from CUDA’s dominant programming and execution model. A poorly executed integration could create internal product confusion, dilute engineering focus, or alienate developers if the combined stack fragments. 3rd, there is cannibalization risk. If Groq-class inference silicon undercuts GPU inference economics, NVIDIA could face internal margin trade-offs, even if the goal is to defend share against hyperscaler ASICs. Cannibalization can still be rational if it prevents larger share loss, but it would require crisp portfolio segmentation and go-to-market discipline. The presence of NVIDIA’s own rapidly improving inference performance complicates the “need” for Groq but does not eliminate the “option value.” NVIDIA has demonstrated benchmark-leading tokens/s per user on Blackwell-based systems, suggesting that raw interactive throughput is not necessarily the limiting factor for NVIDIA’s product line. The more enduring strategic question is unit economics and architectural control: whether future inference demand is better monetized through general-purpose GPUs plus software optimization, or whether a bifurcated product portfolio (training GPUs plus inference-native ASICs) becomes necessary to defend total AI compute wallet share as hyperscaler ASIC penetration increases. Acquiring Groq could be a decisive move to ensure NVIDIA participates in both regimes rather than betting exclusively on GPUs to win inference forever. What is “special” about Groq’s technology relative to a typical accelerator roadmap is the tight coupling of determinism, compilation, and networking into a single scheduling problem. The LPU narrative emphasizes deterministic compute and networking, static scheduling, and direct chip-to-chip coordination that allows “hundreds” (more precisely, 100s) of chips to behave like a single scheduled resource. The architecture also explicitly targets tensor-parallel, latency-optimized distribution rather than pure data-parallel throughput scaling, which matters for real-time applications where a single response must arrive quickly rather than many requests being processed in bulk. The implication is that Groq is optimized for the time-to-first-token and steady token streaming behavior that defines user experience in interactive LLMs, and it attempts to achieve that without relying on large batch sizes that can degrade latency. From a portfolio manager’s perspective, the most important interpretation is that an NVIDIA-Groq combination would likely be less about “NVIDIA needs more inference speed” and more about controlling the architectural trajectory of inference acceleration and removing a fast-improving, developer-friendly competitor from the market. The carve-out of GroqCloud would reinforce that the transaction is aimed at IP, talent, and product optionality, not acquiring a cloud revenue stream. The valuation step-up implied by $20B versus $6.9B would therefore be justified only if the acquired assets materially reduce long-term competitive risk (hyperscaler ASIC displacement, inference margin compression) or enable new monetization vectors (inference ASIC product line, supply chain de-bottlenecking, improved software determinism) that would be difficult to achieve on a comparable timeline via internal R&D.

$NVDA $GFS NVIDIA’s reported agreement to acquire Groq for $20B in cash (per CNBC, amplified via Reuters and other wire coverage) represents a materially different strategic posture than NVIDIA’s prior M&A pattern, given both the headline size (largest reported NVIDIA acquisition to date) and the unusual carve-out that Groq’s early-stage cloud business would not be included. Public reporting indicates the information originated from Alex Davis, CEO of Disruptive (lead investor in Groq’s latest financing), and that neither NVIDIA nor Groq had issued an immediate confirmation at the time of publication. The same reporting frames the transaction as coming together quickly, only months after Groq raised $750M at a ~$6.9B valuation, and highlights Groq’s positioning as a high-performance inference chip vendor founded by ex-Google TPU engineers. Groq is best understood as a vertically integrated inference acceleration company whose core asset is an application-specific processor optimized for deterministic, low-latency execution of transformer-style workloads, paired with a compiler-led software stack and a distribution layer (GroqCloud) designed to reduce developer friction via OpenAI-compatible APIs and integrations. Groq brands its architecture as a Language Processing Unit (LPU) and consistently emphasizes that the design target is inference, not training. The company’s own architecture description centers on 1-core execution, large on-chip SRAM used as primary storage (explicitly not cache), a custom compiler that statically schedules compute and communication, and direct chip-to-chip connectivity intended to coordinate multi-chip execution without relying on conventional caching hierarchies or dynamic runtime scheduling. The technical premise is a deliberate inversion of the conventional GPU approach. GPUs deliver throughput via massively parallel, multi-core execution with dynamic scheduling, complex memory hierarchies, and heavy reliance on off-chip HBM bandwidth and sophisticated runtime/kernel optimization. Groq instead argues that inference bottlenecks are driven by latency variance (tail latency), synchronization overhead, and memory access unpredictability inherent in dynamically scheduled, cache-heavy architectures, particularly when workloads are latency sensitive and batch sizes cannot be inflated. Groq’s solution is to move “control” into the compiler: the full execution graph and inter-chip communication schedule are computed ahead of time down to clock-cycle granularity, with deterministic execution designed to reduce run-to-run variance. In Groq’s framing, the removal of caches, reorder buffers, speculative execution overhead, and other sources of contention enables predictable latency and high utilization without per-model kernel engineering typical of GPU tuning cycles. A critical nuance is that Groq’s determinism is not merely a software claim; it is tightly coupled to architectural constraints and system design choices that trade flexibility for predictability. Third-party technical commentary indicates Groq’s chip uses a fully deterministic VLIW-style approach with minimal buffering, no external memory, and heavy dependence on sharding models across many chips because on-chip SRAM capacity is limited. SemiAnalysis describes a ~725 mm^2 die on GlobalFoundries 14nm with ~230MB of SRAM and notes that “no useful models” fit on a single chip, forcing multi-chip partitioning for modern LLMs and driving a system-level design where networking and compilation are first-class scheduling problems rather than ancillary infrastructure. This is consistent with Groq’s own messaging that tensor parallelism across chips is a primary design goal, enabled by large on-chip SRAM and compile-time coordination of compute plus interconnect. The on-chip SRAM emphasis is central to Groq’s latency story and also its most constraining trade-off. Groq claims on-chip SRAM bandwidth “upwards of 80 TB/s” and contrasts that with off-chip HBM bandwidth “about 8 TB/s,” asserting a potential 10x advantage from bandwidth plus reduced trips across chip-to-memory boundaries. While these comparisons are marketing-oriented and depend on workload specifics, the architectural implication is clear: Groq prioritizes ultra-fast local weight/activation access and then scales capacity by adding chips, not by attaching large off-chip memory pools. This design can reduce latency for sequential inference layers and minimize unpredictable stalls, but it pushes complexity into partitioning strategy, interconnect topology, and compiler scheduling, and it increases the number of chips needed for very large parameter counts and large KV-cache footprints. Groq also highlights numeric formats and compiler-driven precision management as a performance lever. In its 2025 technical blog, Groq describes “TruePoint numerics,” including 100-bit intermediate accumulation and selective quantization choices (FP32 for attention-sensitive operations, block floating point for MoE weights, FP8 storage in error-tolerant layers), and claims 2-4x speedups versus BF16 without measurable accuracy degradation on benchmarks such as MMLU and HumanEval. Even if the absolute uplift is workload dependent, the strategic point is that Groq is pursuing performance via end-to-end co-design: precision policy is not just hardware capability (FP8/BF16) but compiler-enforced mapping of precision to error sensitivity, which can matter materially for inference cost-per-token if it reduces memory traffic and boosts throughput without forcing aggressive, accuracy-damaging quantization. Independent performance datapoints indicate Groq has been credible on latency-oriented inference speed, at least for certain regimes. EE Times reported in 2023 that Groq demonstrated Llama-2 70B inference at ~240 tokens/s per user on a cloud-based dev system described as 10 racks and 64 chips, using the company’s 1st-gen silicon introduced several years earlier. Separate Groq commentary around independent benchmarking cites results showing ~241 tokens/s throughput and ~0.8s time to receive 100 output tokens for a Llama-2 70B API configuration, positioning the platform as a step-change in “available speed” for certain interactive use cases. These figures do not settle total cost-of-ownership versus GPUs or hyperscaler ASICs, but they establish that Groq’s system-level architecture can deliver strong single-user throughput and latency on large models when properly partitioned and scheduled. GroqCloud is the commercial wrapper that packages this hardware/software stack as “tokens-as-a-service,” aiming to make Groq adoption feel like switching API endpoints rather than adopting new silicon. Groq’s documentation states its API is designed to be “mostly compatible” with OpenAI client libraries, and its pricing page provides model-specific token rates, published speeds (tokens/s), prompt caching discounts, and batch processing discounts. For example, pricing lists inputs as low as $0.05 per 1M tokens and outputs as low as $0.08 per 1M tokens for certain smaller LLM configurations, with higher prices for larger models and long-context or MoE variants; it also advertises prompt caching with a 50% discount on cached input tokens for certain models and a batch API offering 50% lower cost for asynchronous processing windows. These mechanics are economically important because they demonstrate Groq’s go-to-market is not simply “sell chips,” but “sell predictable unit economics per token,” with tooling (batch, caching) that directly targets inference cost drivers (reused prompts, throughput smoothing, and asynchronous workloads). The cloud footprint and distribution partnerships indicate Groq has been building an inference-native “edge within the cloud” strategy rather than competing head-on with hyperscalers on breadth of services. A 2025 Groq newsroom release describes a European deployment in Helsinki with Equinix, positioned as latency reduction and data governance for European customers, and explicitly references Equinix Fabric enabling private connectivity to GroqCloud over public, private, or sovereign infrastructure. The same release enumerates additional capacity in the U.S. (Equinix, DataBank), Canada (Bell Canada), and Saudi Arabia (HUMAIN), and states these sites collectively served more than 20M tokens/s across Groq’s global network at that time. That supply-side metric matters because it provides a directional sense that Groq is scaling capacity as a network, not merely as a chip vendor. Customer disclosure is inherently limited because Groq is private and many enterprise deployments are not public, but Groq’s marketing materials and partnerships provide signals about demand vectors. The company’s public website displays logos of large consumer and enterprise brands (e.g., Dropbox, Vercel, Chevron, Volkswagen, Canva, Robinhood, Riot Games, Workday, Ramp) and includes a published customer quote claiming a 7.41x chat speed increase and an 89% cost reduction after moving to GroqCloud, followed by a tripling of token consumption. While marketing claims should be treated as case-specific and not generalized, they indicate that Groq is targeting both AI-native developers (who measure success by latency and cost-per-token) and enterprise buyers (who care about predictable performance and governance). Supplier and dependency mapping for Groq spans 3 layers: silicon production, system integration, and cloud infrastructure. On silicon, third-party analysis indicates GlobalFoundries 14nm for the 1st-gen Groq chip, implying a supply chain less constrained by the most capacity-tight leading-edge nodes and advanced packaging bottlenecks that dominate high-end GPU supply (HBM stacks, CoWoS-type packaging constraints). If accurate, this is strategically meaningful because it suggests Groq capacity expansion could be gated more by conventional wafer supply, board assembly, and data center power than by the same HBM/advanced packaging scarcity that has constrained top-tier GPU ramp cycles. On systems and cloud, Groq’s own releases identify colocation and connectivity partners (Equinix, DataBank, Bell Canada) and a Middle East partner (HUMAIN), implying dependencies on data center real estate, power availability, and network connectivity, alongside procurement of standard server components, NICs/switching, racks, and cooling infrastructure. The Groq design narrative also emphasizes air cooling and reduced need for complex power/cooling infrastructure, which—if realized in deployments—can widen the set of feasible hosting locations and lower deployment friction relative to liquid-cooled, very high power density GPU racks. Against that backdrop, the strategic rationale for NVIDIA acquiring Groq can be framed as a set of overlapping objectives: inference silicon optionality, architectural hedging, competitive defense, and supply chain diversification, with the carve-out of GroqCloud signaling a preference to avoid direct cloud competition and to focus on IP and product portfolio control rather than operating a capital-intensive token-serving business. The deal, if confirmed, would occur at a valuation step-up of ~190% versus Groq’s reported ~$6.9B private valuation in the September $750M round, reinforcing that any acquisition logic would be predominantly strategic rather than a conventional financial multiple arbitrage. The most compelling strategic driver is inference. Training has historically been the center of gravity for cutting-edge GPU demand, but inference volume is structurally larger and more distributed as deployments scale, with economics dominated by cost-per-token, latency guarantees, and utilization under spiky demand. Inference workloads also create a strategic vulnerability for NVIDIA: hyperscalers and large platforms can justify bespoke ASICs (TPU, Trainium/Inferentia, Maia-class efforts) because inference is stable, repeatable, and can amortize software investment at massive scale. Groq’s core proposition—deterministic, compiler-scheduled inference with predictable latency—aligns directly with the segment where GPU generality is least valued and where “good enough” programmability plus superior unit economics can win share. Acquiring Groq would allow NVIDIA to own a credible inference-native architecture rather than relying solely on GPUs and software optimization to defend that segment. Competitive defense logic is also plausible. Groq occupies a specific competitive wedge: low-latency, high-throughput interactive inference, delivered via a simple API abstraction that reduces switching cost. That wedge directly pressures GPU inference margins in the long run because it makes inference price/performance comparisons more transparent at the token level, and it targets a developer persona that historically defaulted to CUDA-first ecosystems. Even if NVIDIA’s current-generation systems can achieve very high tokens/s per user with extensive optimization, the strategic risk is that competing architectures normalize the idea that inference is best served by special-purpose silicon with a simpler programming model, weakening CUDA lock-in at the application layer. NVIDIA has actively demonstrated that Blackwell-era systems can exceed 1,000 tokens/s per user in benchmarked configurations, but that performance leadership does not automatically translate to lowest cost-per-token across the full range of batch sizes, latency targets, and deployment environments. Groq’s existence as a credible alternative architecture forces NVIDIA to keep defending inference economics rather than only raw performance leadership. The “technology acquisition” rationale is unusually strong in this specific case because Groq’s differentiator is not a single block of silicon IP but an end-to-end methodology: compiler-led static scheduling, deterministic networking, and a system architecture designed around tensor-parallel inference rather than throughput-maximizing batch inference. NVIDIA’s stack is already compiler-heavy (TensorRT, Triton, CUDA graphs, kernel fusion, speculative decoding techniques), but GPUs remain dynamically scheduled devices with complex memory hierarchies and stochastic latency behaviors under contention. Groq’s approach provides an alternate design point: treating the entire inference execution (compute plus communication) as a statically schedulable program. In principle, that IP could be valuable even if Groq silicon itself is not adopted at massive scale, because it can inform how NVIDIA builds future inference-optimized products, compilers, and networking fabrics, especially as distributed inference with large models makes communication a first-order performance determinant. Supply chain diversification is a non-obvious but potentially important driver. If Groq’s mainstream product generation is truly based on a mature process node and avoids HBM, then the scaling constraints look different than those of state-of-the-art GPUs. NVIDIA’s ability to meet incremental demand has been tightly coupled to advanced packaging and HBM supply, and those constraints can remain binding even when wafer supply is available. An inference ASIC architecture that relies primarily on on-chip SRAM and scales by adding chips—while not costless—could reduce dependence on HBM availability and advanced packaging capacity, enabling NVIDIA to ship “inference capacity” in higher absolute volumes or into geographies and customer segments where the highest-end GPUs are economically or logistically difficult to deploy. This could be particularly relevant for latency-sensitive inference deployed in regional colocation footprints rather than centralized hyperscale campuses. The carve-out of GroqCloud, if accurate, is itself a strategic signal about NVIDIA’s priorities. Operating a token-serving cloud at scale is capital intensive, structurally lower margin than silicon IP rents, and creates channel conflict with hyperscalers and CSP partners who are core NVIDIA customers. NVIDIA has generally positioned its cloud offerings through partnerships rather than as a direct hyperscale competitor. Excluding GroqCloud would preserve neutrality with CSPs and avoid inheriting multi-region data residency obligations and partner contracts, while still allowing NVIDIA to acquire Groq’s silicon, compiler technology, and engineering talent. At the same time, excluding GroqCloud would also mean NVIDIA would not automatically acquire the commercial proof-point of Groq’s unit economics or the customer contracts that validate product-market fit at scale, increasing the importance of diligence on whether Groq’s cloud pricing is structurally profitable or partially subsidized by fundraising. There is also a “preemptive acquisition” angle. The reporting identifies recent investors in Groq’s latest round including large financial institutions and strategic/industry players. In that context, Groq represents an asset that could plausibly have been acquired by a competitor (AMD/Intel) or by a hyperscaler seeking to accelerate inference independence. NVIDIA acquiring Groq could be a defensive move to prevent a credible inference-native architecture from being weaponized by a rival with deep distribution. Even if GroqCloud is carved out, controlling the silicon roadmap and compiler IP would meaningfully constrain Groq’s ability to evolve into a standalone competitor, unless the carved-out entity retains long-term rights to the hardware and software stack. However, the strategic case is not one-sided; there are meaningful risks and potential contradictions that would need to be reconciled for the transaction to be value-accretive on a multi-year horizon. 1st, Groq’s architecture appears to rely on scaling out chip count to achieve capacity, which introduces system cost, networking complexity, and physical footprint considerations. The absence of external memory and limited on-chip SRAM implies very large models require substantial chip parallelism, and the economics then depend heavily on chip cost, yield, power efficiency, and interconnect overhead. SemiAnalysis explicitly frames Groq as trading space for time and raises questions about token economics and whether publicly advertised pricing reflects fully loaded costs or market share capture. 2nd, integration risk is non-trivial. Groq’s compiler-led deterministic model is philosophically and practically different from CUDA’s dominant programming and execution model. A poorly executed integration could create internal product confusion, dilute engineering focus, or alienate developers if the combined stack fragments. 3rd, there is cannibalization risk. If Groq-class inference silicon undercuts GPU inference economics, NVIDIA could face internal margin trade-offs, even if the goal is to defend share against hyperscaler ASICs. Cannibalization can still be rational if it prevents larger share loss, but it would require crisp portfolio segmentation and go-to-market discipline. The presence of NVIDIA’s own rapidly improving inference performance complicates the “need” for Groq but does not eliminate the “option value.” NVIDIA has demonstrated benchmark-leading tokens/s per user on Blackwell-based systems, suggesting that raw interactive throughput is not necessarily the limiting factor for NVIDIA’s product line. The more enduring strategic question is unit economics and architectural control: whether future inference demand is better monetized through general-purpose GPUs plus software optimization, or whether a bifurcated product portfolio (training GPUs plus inference-native ASICs) becomes necessary to defend total AI compute wallet share as hyperscaler ASIC penetration increases. Acquiring Groq could be a decisive move to ensure NVIDIA participates in both regimes rather than betting exclusively on GPUs to win inference forever. What is “special” about Groq’s technology relative to a typical accelerator roadmap is the tight coupling of determinism, compilation, and networking into a single scheduling problem. The LPU narrative emphasizes deterministic compute and networking, static scheduling, and direct chip-to-chip coordination that allows “hundreds” (more precisely, 100s) of chips to behave like a single scheduled resource. The architecture also explicitly targets tensor-parallel, latency-optimized distribution rather than pure data-parallel throughput scaling, which matters for real-time applications where a single response must arrive quickly rather than many requests being processed in bulk. The implication is that Groq is optimized for the time-to-first-token and steady token streaming behavior that defines user experience in interactive LLMs, and it attempts to achieve that without relying on large batch sizes that can degrade latency. From a portfolio manager’s perspective, the most important interpretation is that an NVIDIA-Groq combination would likely be less about “NVIDIA needs more inference speed” and more about controlling the architectural trajectory of inference acceleration and removing a fast-improving, developer-friendly competitor from the market. The carve-out of GroqCloud would reinforce that the transaction is aimed at IP, talent, and product optionality, not acquiring a cloud revenue stream. The valuation step-up implied by $20B versus $6.9B would therefore be justified only if the acquired assets materially reduce long-term competitive risk (hyperscaler ASIC displacement, inference margin compression) or enable new monetization vectors (inference ASIC product line, supply chain de-bottlenecking, improved software determinism) that would be difficult to achieve on a comparable timeline via internal R&D.

TheValueist

102,145 görüntüleme • 9 ay önce

BITCOIN RAILS #69: ZERO-KNOWLEDGE PROOFS FOR POST-QUANTUM BITCOIN | with Benedikt Bünz 🔗 YOUTUBE: 🌿 SPOTIFY: While many Bitcoiners remain hopeful the network will embrace zero-knowledge proofs for protocol-level use cases, practical adoption has remained limited outside of BitVM and a handful of experimental proposals. Most of the world’s ZKP research has circled around Ethereum and other ecosystems, where significant resources have been dedicated to advancing these systems, particularly for scaling and privacy applications. One of the most notable contributors to this research is Benedikt Bünz ☕️ — professor of cryptography at NYU and collaborator of Dan Boneh, who together inarguably form one of the strongest blockchain-applied cryptography teams in the world. The pair recently announced they’ll be leading the new post-quantum cryptography unit localhost research — the first dedicated PQ research effort within a major Bitcoin development organization. With Benedikt leading the charge on the use of zero-knowledge proofs for post-quantum mitigation, the question emerges: will the post-quantum transition be the catalyst to finally bring zero-knowledge proofs to Bitcoin's core protocol? In more detail, Benedikt and I discuss: - Why ZKPs haven’t been widely adopted by the Bitcoin technical community — and why the threat of quantum computers may change that posture going forward - How ZKPs could be used for signature batching to address larger post-quantum signatures in Bitcoin’s post-quantum era - Why Bitcoiners will likely prioritize hash-based signatures as an initial post-quantum scheme — rather than more efficient but less proven alternatives (e.g., lattice-based) - How ZKPs have evolved over the last decade and may finally be ready for Bitcoin’s strict requirements around trust assumptions - Why Benedikt and Dan are teaming up with localhost research to create the first post-quantum cryptography unit within a major Bitcoin development organization + what they hope to accomplish This episode of Bitcoin Rails is brought to you by: LayerTwo Labs LayerTwo Labs — developing research, software, and technologies for scaling Bitcoin via the integration of Drivechains (BIP 300/301) Hashi on Sui — a primitive for executing Bitcoin DeFi transactions, without having to trust a federated bridge or other centralized entity BitBox BitBox — an open-source Bitcoin-only hardware wallet, with smooth UX and no compromises on security. Check out Bitbox [dot] swiss and use code BITCOINRAILS to get a discount TIMESTAMPS: 00:00 — Intro 00:22 — Benedikt's background 04:10 — How Benedikt got into Bitcoin and cryptography 07:42 — First ZK project: proving exchange solvency after Mt. Gox 16:01 — ZK proofs explained 27:43 — How security gets popular & ZK proofs in Bitcoin 35:49 — Other applications of ZK proofs for Bitcoin 40:15 — Why ZK proofs haven't been adopted in Bitcoin 50:46 — Why the Bitcoin post-quantum transition needs ZK proofs 01:07:00 — Cryptographic agility and why lattices win 01:18:00 — The size problem and how SNARKs solve it 01:33:57 — Proving a Bitcoin block in a laptop in 1.5 seconds 01:37:12 — Bitcoin as the primary quantum target 01:40:47 — ZK proofs for seed phrase recovery

BITCOIN RAILS #69: ZERO-KNOWLEDGE PROOFS FOR POST-QUANTUM BITCOIN | with Benedikt Bünz 🔗 YOUTUBE: 🌿 SPOTIFY: While many Bitcoiners remain hopeful the network will embrace zero-knowledge proofs for protocol-level use cases, practical adoption has remained limited outside of BitVM and a handful of experimental proposals. Most of the world’s ZKP research has circled around Ethereum and other ecosystems, where significant resources have been dedicated to advancing these systems, particularly for scaling and privacy applications. One of the most notable contributors to this research is Benedikt Bünz ☕️ — professor of cryptography at NYU and collaborator of Dan Boneh, who together inarguably form one of the strongest blockchain-applied cryptography teams in the world. The pair recently announced they’ll be leading the new post-quantum cryptography unit localhost research — the first dedicated PQ research effort within a major Bitcoin development organization. With Benedikt leading the charge on the use of zero-knowledge proofs for post-quantum mitigation, the question emerges: will the post-quantum transition be the catalyst to finally bring zero-knowledge proofs to Bitcoin's core protocol? In more detail, Benedikt and I discuss: - Why ZKPs haven’t been widely adopted by the Bitcoin technical community — and why the threat of quantum computers may change that posture going forward - How ZKPs could be used for signature batching to address larger post-quantum signatures in Bitcoin’s post-quantum era - Why Bitcoiners will likely prioritize hash-based signatures as an initial post-quantum scheme — rather than more efficient but less proven alternatives (e.g., lattice-based) - How ZKPs have evolved over the last decade and may finally be ready for Bitcoin’s strict requirements around trust assumptions - Why Benedikt and Dan are teaming up with localhost research to create the first post-quantum cryptography unit within a major Bitcoin development organization + what they hope to accomplish This episode of Bitcoin Rails is brought to you by: LayerTwo Labs LayerTwo Labs — developing research, software, and technologies for scaling Bitcoin via the integration of Drivechains (BIP 300/301) Hashi on Sui — a primitive for executing Bitcoin DeFi transactions, without having to trust a federated bridge or other centralized entity BitBox BitBox — an open-source Bitcoin-only hardware wallet, with smooth UX and no compromises on security. Check out Bitbox [dot] swiss and use code BITCOINRAILS to get a discount TIMESTAMPS: 00:00 — Intro 00:22 — Benedikt's background 04:10 — How Benedikt got into Bitcoin and cryptography 07:42 — First ZK project: proving exchange solvency after Mt. Gox 16:01 — ZK proofs explained 27:43 — How security gets popular & ZK proofs in Bitcoin 35:49 — Other applications of ZK proofs for Bitcoin 40:15 — Why ZK proofs haven't been adopted in Bitcoin 50:46 — Why the Bitcoin post-quantum transition needs ZK proofs 01:07:00 — Cryptographic agility and why lattices win 01:18:00 — The size problem and how SNARKs solve it 01:33:57 — Proving a Bitcoin block in a laptop in 1.5 seconds 01:37:12 — Bitcoin as the primary quantum target 01:40:47 — ZK proofs for seed phrase recovery

Isabel Foxen Duke⚡️

19,872 görüntüleme • 2 ay önce

BITCOIN RAILS #62: BITCOIN'S 3 BIGGEST CHALLENGES | with Neha Narula Director of Digital Currency Initiative (DCI) Massachusetts Institute of Technology (MIT) 🔗 YOUTUBE: 🌱 SPOTIFY: Neha Narula is the Director of the MIT Digital Currency Initiative, where she focuses on Bitcoin research and the broader design tradeoffs of decentralized money systems. Her work often centers on what Bitcoin gets right—and where it runs into hard limits—especially around scaling, decentralization, and how systems behave as global demand increases. In this interview, Neha and I explore longer-term risks to Bitcoin—including advancements in quantum computing and the implications of a diminishing block subsidy—as well as the ongoing challenge of scaling Bitcoin without losing access to self-custody. A thoughtful conversation on how Bitcoin may change in the coming years, we also explore its social and governance dynamics—including tensions within the development community over protocol changes, scaling philosophies, and the future direction of the system. This episode of Bitcoin Rails is brought to you by: LayerTwo Labs LayerTwo Labs — developing research, software, and technologies for scaling Bitcoin via the integration of Drivechains (BIP 300/301) Hashi on Sui — a primitive for executing Bitcoin Defi transactions, without having to trust a federated bridge or other centralized entity BitBox BitBox— an open-source Bitcoin-only hardware wallet, with smooth UX and no compromises on security. Check out Bitbox [dot] swiss and use code BITCOINRAILS to get a discount TIMESTAMPS: 00:00 Intro 00:17 Neha’s Origins 02:26 Bitcoin to MIT 04:40 Media Lab Culture and Mission 11:34 CBDCs as Digital Cash Debate 24:42 Funding Model and Bitcoin Security Budget 29:55 Reorg Risk and Quantum Computing 32:14 Bitcoin Dev Funding Map 42:49 Governance and Corporate Stakes 50:23 Quantum Tradeoffs Framework 56:02 Post Quantum Proposals 58:59 Prioritize PQ Transactions 01:00:54 Satoshi Coins Debate 01:02:12 Mining Incentives And Price 01:08:08 Corporate Funding And Governance 01:10:54 Scaling Self Custody And L2s 01:20:30 Bitcoin Kernel And Wrap Up

BITCOIN RAILS #62: BITCOIN'S 3 BIGGEST CHALLENGES | with Neha Narula Director of Digital Currency Initiative (DCI) Massachusetts Institute of Technology (MIT) 🔗 YOUTUBE: 🌱 SPOTIFY: Neha Narula is the Director of the MIT Digital Currency Initiative, where she focuses on Bitcoin research and the broader design tradeoffs of decentralized money systems. Her work often centers on what Bitcoin gets right—and where it runs into hard limits—especially around scaling, decentralization, and how systems behave as global demand increases. In this interview, Neha and I explore longer-term risks to Bitcoin—including advancements in quantum computing and the implications of a diminishing block subsidy—as well as the ongoing challenge of scaling Bitcoin without losing access to self-custody. A thoughtful conversation on how Bitcoin may change in the coming years, we also explore its social and governance dynamics—including tensions within the development community over protocol changes, scaling philosophies, and the future direction of the system. This episode of Bitcoin Rails is brought to you by: LayerTwo Labs LayerTwo Labs — developing research, software, and technologies for scaling Bitcoin via the integration of Drivechains (BIP 300/301) Hashi on Sui — a primitive for executing Bitcoin Defi transactions, without having to trust a federated bridge or other centralized entity BitBox BitBox— an open-source Bitcoin-only hardware wallet, with smooth UX and no compromises on security. Check out Bitbox [dot] swiss and use code BITCOINRAILS to get a discount TIMESTAMPS: 00:00 Intro 00:17 Neha’s Origins 02:26 Bitcoin to MIT 04:40 Media Lab Culture and Mission 11:34 CBDCs as Digital Cash Debate 24:42 Funding Model and Bitcoin Security Budget 29:55 Reorg Risk and Quantum Computing 32:14 Bitcoin Dev Funding Map 42:49 Governance and Corporate Stakes 50:23 Quantum Tradeoffs Framework 56:02 Post Quantum Proposals 58:59 Prioritize PQ Transactions 01:00:54 Satoshi Coins Debate 01:02:12 Mining Incentives And Price 01:08:08 Corporate Funding And Governance 01:10:54 Scaling Self Custody And L2s 01:20:30 Bitcoin Kernel And Wrap Up

Isabel Foxen Duke⚡️

24,580 görüntüleme • 4 ay önce

🚀 Exciting News $SHELL the Future of AI Agents and $TAO with the TTS Subnet on Bittensor! 🚀 MyShell extends the impact of Bittensor's incentive mechanism to its over 1 million registered users and 50,000 creators, greatly expanding Bittensor's and $TAO's influence. MyShell and Bittensor are right at the heart this massive shake-up with $SHELL and $TAO. They’re all about making AI not just smart but also something everyone can get into, thanks to the power of decentralized networks. And at the core? AI agents. These aren't your average digital assistants; they're about to change how we interact with tech on a whole new level. MyShell's Big Idea with $SHELL So, MyShell’s got this big plan to make AI something anyone can dive into. They're launching this TTS Subnet thing on Bittensor's network, which is all about making machines talk in more human-like ways, and they're using $SHELL tokens to fuel this vision. Their goal? To push past old-school AI limits and create with AI as easy as pie, all while keeping it open-source and community-powered. Bittensor Does Its Magic with $TAO On the other side, you’ve got Bittensor doing wonders with $TAO, building this massive network where anyone, anywhere, can chip in on AI research and development. This partnership with MyShell? It’s a game-changer, breaking down walls in AI development and letting folks from all over the world have a go at making AI smarter. $SHELL + $TAO = AI Revolution Putting $SHELL and $TAO together is where the magic really happens. MyShell and Bittensor aren’t just teaming up for the tech; they’re here to transform our digital world, making AI agents a big part of our online lives. Imagine AI that doesn’t just follow orders but helps, creates, and learns with you. That’s the future they’re building. Hop on Board the AI Revolution This isn’t just tech talk; it’s a call to action. MyShell and Bittensor are inviting anyone with a spark for AI to jump in and help shape this new world. Whether you’re a coder, a creator, or just curious, there’s a spot for you to dive in and make a difference. Want to get started? Check out MyShell on GitHub: Follow the latest buzz on X: MyShell.AI Take a deeper dive at Website: This is more than just building AI; it’s about crafting a future where AI is part of everyone’s life, powered by the community, for the community. Let’s make it happen with $SHELL and $TAO. Share on YouTube:

🚀 Exciting News $SHELL the Future of AI Agents and $TAO with the TTS Subnet on Bittensor! 🚀 MyShell extends the impact of Bittensor's incentive mechanism to its over 1 million registered users and 50,000 creators, greatly expanding Bittensor's and $TAO's influence. MyShell and Bittensor are right at the heart this massive shake-up with $SHELL and $TAO. They’re all about making AI not just smart but also something everyone can get into, thanks to the power of decentralized networks. And at the core? AI agents. These aren't your average digital assistants; they're about to change how we interact with tech on a whole new level. MyShell's Big Idea with $SHELL So, MyShell’s got this big plan to make AI something anyone can dive into. They're launching this TTS Subnet thing on Bittensor's network, which is all about making machines talk in more human-like ways, and they're using $SHELL tokens to fuel this vision. Their goal? To push past old-school AI limits and create with AI as easy as pie, all while keeping it open-source and community-powered. Bittensor Does Its Magic with $TAO On the other side, you’ve got Bittensor doing wonders with $TAO, building this massive network where anyone, anywhere, can chip in on AI research and development. This partnership with MyShell? It’s a game-changer, breaking down walls in AI development and letting folks from all over the world have a go at making AI smarter. $SHELL + $TAO = AI Revolution Putting $SHELL and $TAO together is where the magic really happens. MyShell and Bittensor aren’t just teaming up for the tech; they’re here to transform our digital world, making AI agents a big part of our online lives. Imagine AI that doesn’t just follow orders but helps, creates, and learns with you. That’s the future they’re building. Hop on Board the AI Revolution This isn’t just tech talk; it’s a call to action. MyShell and Bittensor are inviting anyone with a spark for AI to jump in and help shape this new world. Whether you’re a coder, a creator, or just curious, there’s a spot for you to dive in and make a difference. Want to get started? Check out MyShell on GitHub: Follow the latest buzz on X: MyShell.AI Take a deeper dive at Website: This is more than just building AI; it’s about crafting a future where AI is part of everyone’s life, powered by the community, for the community. Let’s make it happen with $SHELL and $TAO. Share on YouTube:

Andy ττ

10,842 görüntüleme • 2 yıl önce

If you’re looking for the next wave of AI infrastructure opportunities, this is a must-watch 🚀 Everyone’s chasing the next big AI agent, but they’re missing the real story. Why is aixbt is dominating the market and how Cookie DAO 🍪 $COOKIE could change everything We discuss 👇 Why $COOKIE Is The Hidden AI GEM💎 on BASE! Chainlink For AI?! 400x POSSIBILITY! With most of the AI market mania fixated on which AI agent to speculate on next, we are deep diving into the depths of the ecosystem to find the next major infrastructure plays. With Aixbt dominating in crypto twitter mind share, it has proven the AI agents with the ability to produce impactful market insights stand among the pack as leaders in the market. Already Aixbt is at a 600M market cap only a couple of months after deployment. We break down why Aixbt has this ability to outperform other agents and how data aggregation is the necessary technical edge. Also, we analyze CookieDAO $COOKIE as the infrastructure provider leading the market with its data aggregation and packaging process. $COOKIE is on the verge of revamping its tokenomics to incorporate API access to data swarm API’s that they provide into the flywheel economics of the token. As demand increases from human and AI users of access to the data being aggregated will become that much more valuable in order for Agents to perform at a level equal to or greater than what Aixbt is capable of performing today. As $COOKIE are spent for these API’s by agents and developers, the supply gets burnt and funneled to the DAO. This will have a very positive impact on the value perception for the token. We also break down our predictions as to how their flagship agent Agent Cookie will perform once activated and released into the public sphere. Already based on internal testing as reported by the team, Agent Cookie is successfully producing valuable market calls. If Agent Cookie can achieve similar mind share as AIXBT as a result of its broader data aggregation access, this will have major ramifications for the value of $COOKIE and the ecosystem as a whole once more agents are launched using the same data infrastructure layer. 🚀Sign up to receive our Newsletter for weekly updates! Disclaimer: The views and opinions expressed by The Block Runner are for informational purposes only and do not constitute financial, investment, or other advice.

If you’re looking for the next wave of AI infrastructure opportunities, this is a must-watch 🚀 Everyone’s chasing the next big AI agent, but they’re missing the real story. Why is aixbt is dominating the market and how Cookie DAO 🍪 $COOKIE could change everything We discuss 👇 Why $COOKIE Is The Hidden AI GEM💎 on BASE! Chainlink For AI?! 400x POSSIBILITY! With most of the AI market mania fixated on which AI agent to speculate on next, we are deep diving into the depths of the ecosystem to find the next major infrastructure plays. With Aixbt dominating in crypto twitter mind share, it has proven the AI agents with the ability to produce impactful market insights stand among the pack as leaders in the market. Already Aixbt is at a 600M market cap only a couple of months after deployment. We break down why Aixbt has this ability to outperform other agents and how data aggregation is the necessary technical edge. Also, we analyze CookieDAO $COOKIE as the infrastructure provider leading the market with its data aggregation and packaging process. $COOKIE is on the verge of revamping its tokenomics to incorporate API access to data swarm API’s that they provide into the flywheel economics of the token. As demand increases from human and AI users of access to the data being aggregated will become that much more valuable in order for Agents to perform at a level equal to or greater than what Aixbt is capable of performing today. As $COOKIE are spent for these API’s by agents and developers, the supply gets burnt and funneled to the DAO. This will have a very positive impact on the value perception for the token. We also break down our predictions as to how their flagship agent Agent Cookie will perform once activated and released into the public sphere. Already based on internal testing as reported by the team, Agent Cookie is successfully producing valuable market calls. If Agent Cookie can achieve similar mind share as AIXBT as a result of its broader data aggregation access, this will have major ramifications for the value of $COOKIE and the ecosystem as a whole once more agents are launched using the same data infrastructure layer. 🚀Sign up to receive our Newsletter for weekly updates! Disclaimer: The views and opinions expressed by The Block Runner are for informational purposes only and do not constitute financial, investment, or other advice.

ᴛʜᴇ ʙʟᴏᴄᴋ ʀᴜɴɴᴇʀ Podcast 🟧

101,528 görüntüleme • 1 yıl önce

Steen Machine Roars: Posters Blanket Ireland as 'Spoil the Vote' Rebellion Explodes With less than 24 hours until Ireland's 2025 presidential election, striking posters of conservative barrister Maria Steen have been appearing on lampposts, community boards, and key locations across the country. Part of the surging "Spoil the Vote" movement, the campaign urges voters to reject Fine Gael's Heather Humphreys, Fianna Fáil's Jim Gavin, and independent Catherine Connolly by writing "1 Maria Steen" on ballots tomorrow.The posters feature Steen's poised portrait in a gold blouse against a gray backdrop, proclaiming: "MARIA STEEN – A President of the People." A red "X" slashes through "THE OTHER THREE CANDIDATES," with instructions to "WRITE DOWN VOTE MARIA STEEN NO. 1." A tricolor version adds "PUTTING FAMILIES FIRST" alongside completing the defiant design symbolizing protest against an "establishment stitch-up." From online fury to street action, the poster effort is led by the new Kells Community Advocacy Group (KCA) in Meath. KCA has coordinated with community groups from Waterford to Donegal, printing posters for key sites like town squares, high traffic areas and arterial routes. Complementing this, the National Party has distributed thousands of "spoil your vote" leaflets in Dublin and beyond over the past few weeks. Councillor Malachy Steenson also called an emergency 'spoil your vote' rally immediately after the last independent candidate was blocked by what is now commonly called the "uniparties." However, the official and website were launched by a team of creative business minds: Declan Ganley, Eddie Hobbs, Elaine Mullally, Paul Treyvaud, Michael McCarthy, and presidential candidate Nick Delehanty, all leading the charge for change. Having launched the campaign with a press conference last week covered by mainstream media, including rte, it has created awareness right across all media channels, amplifying the message nationwide. Steen, a pro-life veteran, narrowly missed the 20 Oireachtas nominations for an independent run, securing 18—including from Aontú's Peadar Tóibín and Independent Ireland's Michael Collins. Critics accuse Fine Gael and Fianna Fáil of blocking her. "Remember what they took from you," tweeted her brother, Senior Counsel Neil Steen, alongside a viral campaign photo earlier today. "We're trying to restore democracy—we've had enough of gatekeepers," said the KCA group, describing a sentiment shared by many across the country who feel robbed of a candidate representing their values. Posters and leaflets now span the nation, with drivers stopping to pose for selfies that are appearing across on social media. Critics warn spoiled votes won't block a winner, possibly aiding frontrunner Connolly amid 20% undecideds. As polls open at 7 a.m. this collaborative community effort aims to finally challenge the establishment's controlled lack of democracy. Will "spoiled" ballots make history? Dublin Castle's count will reveal.

Steen Machine Roars: Posters Blanket Ireland as 'Spoil the Vote' Rebellion Explodes With less than 24 hours until Ireland's 2025 presidential election, striking posters of conservative barrister Maria Steen have been appearing on lampposts, community boards, and key locations across the country. Part of the surging "Spoil the Vote" movement, the campaign urges voters to reject Fine Gael's Heather Humphreys, Fianna Fáil's Jim Gavin, and independent Catherine Connolly by writing "1 Maria Steen" on ballots tomorrow.The posters feature Steen's poised portrait in a gold blouse against a gray backdrop, proclaiming: "MARIA STEEN – A President of the People." A red "X" slashes through "THE OTHER THREE CANDIDATES," with instructions to "WRITE DOWN VOTE MARIA STEEN NO. 1." A tricolor version adds "PUTTING FAMILIES FIRST" alongside completing the defiant design symbolizing protest against an "establishment stitch-up." From online fury to street action, the poster effort is led by the new Kells Community Advocacy Group (KCA) in Meath. KCA has coordinated with community groups from Waterford to Donegal, printing posters for key sites like town squares, high traffic areas and arterial routes. Complementing this, the National Party has distributed thousands of "spoil your vote" leaflets in Dublin and beyond over the past few weeks. Councillor Malachy Steenson also called an emergency 'spoil your vote' rally immediately after the last independent candidate was blocked by what is now commonly called the "uniparties." However, the official and website were launched by a team of creative business minds: Declan Ganley, Eddie Hobbs, Elaine Mullally, Paul Treyvaud, Michael McCarthy, and presidential candidate Nick Delehanty, all leading the charge for change. Having launched the campaign with a press conference last week covered by mainstream media, including rte, it has created awareness right across all media channels, amplifying the message nationwide. Steen, a pro-life veteran, narrowly missed the 20 Oireachtas nominations for an independent run, securing 18—including from Aontú's Peadar Tóibín and Independent Ireland's Michael Collins. Critics accuse Fine Gael and Fianna Fáil of blocking her. "Remember what they took from you," tweeted her brother, Senior Counsel Neil Steen, alongside a viral campaign photo earlier today. "We're trying to restore democracy—we've had enough of gatekeepers," said the KCA group, describing a sentiment shared by many across the country who feel robbed of a candidate representing their values. Posters and leaflets now span the nation, with drivers stopping to pose for selfies that are appearing across on social media. Critics warn spoiled votes won't block a winner, possibly aiding frontrunner Connolly amid 20% undecideds. As polls open at 7 a.m. this collaborative community effort aims to finally challenge the establishment's controlled lack of democracy. Will "spoiled" ballots make history? Dublin Castle's count will reveal.

SnDMedia

19,458 görüntüleme • 11 ay önce

⚡️🚨 We May be on the Verge of a Major War🔥 Prof. Jeffrey Sachs : Using the Economy as a Weapon — Trump and Iran The United States used economic warfare to create chaos in Iran. The United States used economic warfare to destroy the Iranian economy, and it continues to do so. The goal is regime change. Absolutely illegal, absolutely disastrous, crushing the lives, the livelihoods, the health, leading to deaths en masse numbers we know these sanctions that have been used by the United States in this way in many countries to destroy other countries. The US is engaged in economic warfare out of control, completely irresponsible, often gamed by wealthy campaign contributors or Trump's own family. What's happening in Iran is the deliberate collapse of the currency, the deliberate, creation of mass poverty, unemployment, and unrest in Iran for the purpose of attempting a regime change. And, maybe it's true that not one, in a million New York Times reporters can understand it, or mainstream, media reporters, but now at least they have Mr. Bessent, to listen to, and maybe they should reflect on that to try to understand their job better of reporting what's really happening. The United States is engaged in war, war is illegal under our Constitution unless declared by the US Congress, and it's illegal under international law, the UN Charter, Article II, Section 4, which is treaty law of the United States since the UN Charter was ratified in July 1945. The fact of the matter is that the vast majority of the world does not want war, does not want sides, does not want a US, quote, "economic statecraft," which means economic warfare. The rest of the world wants to get on with their lives, and they're doing it step by step. Yesterday or today, I can't, even remember by the hour now, Trump has, threatened, new tariffs against South Korea, a supposed ally, a home to US military bases. Well, the South Korean leadership was recently in Beijing, saying, we want normal relations with China." And interestingly, though the US, punished one country after another last year, trade among those countries outside of the United States didn't suffer. It turned out you can get along just fine with trading with each other. The United States is not big enough, powerful enough, determinative enough of the world's future to hold it in its hands the way that our Emperor Donald thinks it is, and so the rest of the world had increases of trade. China's trade went up last year. So this is what is happening. Countries are finding other ways to do business with each other, and they are not being cowed by the US, even though I have to say, the US can still do a great deal of harm, as is the case in Venezuela, as is the case in Iran, and we may see within the coming days a US attack, military attack on Iran, as these, aircraft, carrier task force, approach, the Persian Gulf. So, we may be on the verge of a major war. Maybe not. Maybe it's a bluff, but the warfare is absolutely real.

⚡️🚨 We May be on the Verge of a Major War🔥 Prof. Jeffrey Sachs : Using the Economy as a Weapon — Trump and Iran The United States used economic warfare to create chaos in Iran. The United States used economic warfare to destroy the Iranian economy, and it continues to do so. The goal is regime change. Absolutely illegal, absolutely disastrous, crushing the lives, the livelihoods, the health, leading to deaths en masse numbers we know these sanctions that have been used by the United States in this way in many countries to destroy other countries. The US is engaged in economic warfare out of control, completely irresponsible, often gamed by wealthy campaign contributors or Trump's own family. What's happening in Iran is the deliberate collapse of the currency, the deliberate, creation of mass poverty, unemployment, and unrest in Iran for the purpose of attempting a regime change. And, maybe it's true that not one, in a million New York Times reporters can understand it, or mainstream, media reporters, but now at least they have Mr. Bessent, to listen to, and maybe they should reflect on that to try to understand their job better of reporting what's really happening. The United States is engaged in war, war is illegal under our Constitution unless declared by the US Congress, and it's illegal under international law, the UN Charter, Article II, Section 4, which is treaty law of the United States since the UN Charter was ratified in July 1945. The fact of the matter is that the vast majority of the world does not want war, does not want sides, does not want a US, quote, "economic statecraft," which means economic warfare. The rest of the world wants to get on with their lives, and they're doing it step by step. Yesterday or today, I can't, even remember by the hour now, Trump has, threatened, new tariffs against South Korea, a supposed ally, a home to US military bases. Well, the South Korean leadership was recently in Beijing, saying, we want normal relations with China." And interestingly, though the US, punished one country after another last year, trade among those countries outside of the United States didn't suffer. It turned out you can get along just fine with trading with each other. The United States is not big enough, powerful enough, determinative enough of the world's future to hold it in its hands the way that our Emperor Donald thinks it is, and so the rest of the world had increases of trade. China's trade went up last year. So this is what is happening. Countries are finding other ways to do business with each other, and they are not being cowed by the US, even though I have to say, the US can still do a great deal of harm, as is the case in Venezuela, as is the case in Iran, and we may see within the coming days a US attack, military attack on Iran, as these, aircraft, carrier task force, approach, the Persian Gulf. So, we may be on the verge of a major war. Maybe not. Maybe it's a bluff, but the warfare is absolutely real.

Ignorance, the root and stem of all evil

38,278 görüntüleme • 8 ay önce

There is an epidemic of white police officers killing unarmed black men, we must block the puberty of children born in the wrong bodies to prevent them from killing themselves, the Russians control Trump through a sex blackmail operation, the Covid vaccine prevents infection, millions or billions will die from starvation and harsh weather from climate change, there's no way a Covid virus could have escaped from a lab, mass migration improves societies with no trade-offs, it's best for addicts if we give them hard drugs to use in special sites downtown, we need the government to fight misinformation online in order to save democracy, Biden is sharper than ever, Kamala is 100% prepared to be president, and anyone who disagrees is racist, sexist, and/or fascist. While many Americans are increasingly and at least partially aware that all of the above are lies, we are still a long way from coming to grips with their enormity, their monstrous consequences, and the totalitarian ways in which the mainstream news media, many employers, and governments demanded that we believe them. Current and former heads of state, our most-trusted journalists, and full professors at Ivy League universities created and propagated those Big Lies, repeatedly, for years, even after they had been thoroughly debunked, sometimes within days or hours of them being made, by people who ruling elites then sought to bankrupt, shame, and ostracize. There has not yet been a proper accounting of the very many abuses of power, including the Big Lies, by elected officials, the media, and other governing elites during the Woke Reign of Terror (2013 - 2024). That accounting will need not only to thoroughly debunk all of the major lies, it will also need to explore why elites created and perpetuated them, why so many people believed them, why they lasted for so long, and what can be learned from them, both separately and how they worked together as a whole, constituting the worldview of the people who run Western societies and nations. Historians, sociologists, psychologists and many others will, for centuries, study the Work Reign of Terror as a uniquely irrational and self-destructive period in America's history. Hopefully something good, including wisdom, courage, and improved self-governance, will come out of those studies and reflections.

There is an epidemic of white police officers killing unarmed black men, we must block the puberty of children born in the wrong bodies to prevent them from killing themselves, the Russians control Trump through a sex blackmail operation, the Covid vaccine prevents infection, millions or billions will die from starvation and harsh weather from climate change, there's no way a Covid virus could have escaped from a lab, mass migration improves societies with no trade-offs, it's best for addicts if we give them hard drugs to use in special sites downtown, we need the government to fight misinformation online in order to save democracy, Biden is sharper than ever, Kamala is 100% prepared to be president, and anyone who disagrees is racist, sexist, and/or fascist. While many Americans are increasingly and at least partially aware that all of the above are lies, we are still a long way from coming to grips with their enormity, their monstrous consequences, and the totalitarian ways in which the mainstream news media, many employers, and governments demanded that we believe them. Current and former heads of state, our most-trusted journalists, and full professors at Ivy League universities created and propagated those Big Lies, repeatedly, for years, even after they had been thoroughly debunked, sometimes within days or hours of them being made, by people who ruling elites then sought to bankrupt, shame, and ostracize. There has not yet been a proper accounting of the very many abuses of power, including the Big Lies, by elected officials, the media, and other governing elites during the Woke Reign of Terror (2013 - 2024). That accounting will need not only to thoroughly debunk all of the major lies, it will also need to explore why elites created and perpetuated them, why so many people believed them, why they lasted for so long, and what can be learned from them, both separately and how they worked together as a whole, constituting the worldview of the people who run Western societies and nations. Historians, sociologists, psychologists and many others will, for centuries, study the Work Reign of Terror as a uniquely irrational and self-destructive period in America's history. Hopefully something good, including wisdom, courage, and improved self-governance, will come out of those studies and reflections.

Michael Shellenberger

1,788,494 görüntüleme • 1 yıl önce

The Capture of Bitcoin Core For years, Bitcoin maintained a reputation as the ultimate uncapturable network. It was designed to be decentralized, driven entirely by consensus, and highly resistant to corporate influence. In 2015, the community famously defended the protocol during the Block Size Wars, repelling a coordinated corporate takeover attempt. In June 2025, that streak ended. A heavily contested code change was pushed into the software despite overwhelming opposition from the community. The update targeted a feature called **OP_RETURN**, a space within a transaction meant to hold tiny amounts of arbitrary data, strictly capped at 80 bytes. The 2025 update stripped those limits away, allowing massive amounts of non-financial data to be embedded directly into the blockchain. Bitcoin requires broad consensus to function, and it has no central leadership. So how did a handful of developers manage to bypass the community and force a major policy change into the software? --- The path to this change began two years earlier with a six-line administrative edit that went virtually unnoticed. By early 2023, the small group of developers who maintain Bitcoin's reference software were seeing an influx of traditional venture capital funding. Major crypto investment firms began directly funding the developers responsible for the software's upkeep. This financial concentration caught the attention of the mainstream press. In February 2023, *The Wall Street Journal* profiled the vulnerability, highlighting how few people actually controlled the software and where their funding originated. Four months later, on June 6, a funded maintainer submitted a code update. It appeared to be routine housekeeping: a six-line adjustment to the software's documentation strings. The edit narrowed the written definition of the network's data limits. The original documentation stated that the limit applied to all data-carrying transactions. The new text restricted that definition to one specific data field. This left several newer data pathways completely unregulated, even though the underlying code itself had not changed. The update passed without scrutiny. But by quietly altering the official definitions, this developer cohort rewrote the rules of engagement for all future policy debates. --- In late 2023, new projects began exploiting the exact gaps left open by that documentation edit. The Bitcoin network was suddenly flooded with digital artifacts and spam, significantly increasing system congestion. The community attempted to respond. An independent developer wrote a software patch to restore the original data limits and secured an official security designation from the National Vulnerability Database to track the exploit. To get that patch implemented, it required approval from the Core maintainers. They rejected it. The cohort cited the six-line documentation edit from earlier that year to justify the rejection. They argued that because the documentation now explicitly excluded those data fields, the spam was technically within the rules. They claimed that fixing the loophole would violate the software's documented intent. In October 2024, during a closed-door developer session, the cohort administratively closed the issue tracking the formal security record, effectively erasing the vulnerability designation from the project's history. By manipulating bureaucratic definitions, a centralized group of developers proved they could protect the specific data streams they favored while blocking community security efforts. --- By early 2025, a specific corporate interest emerged. A venture-funded entity called **Citrea** was building a product that required massive, uncapped data limits on Bitcoin to function. To meet this requirement, an active Core developer commissioned another programmer to submit a code update. This new pull request proposed removing the OP_RETURN data limit entirely—a change explicitly requested on behalf of Citrea. When the community discovered the arrangement, they rejected the proposal by roughly a four-to-one margin, citing the clear conflict of interest. Rather than address the criticism, the developer cohort leveraged their administrative privileges on GitHub to suppress the backlash. They banned vocal critics, locked discussion threads, and hid comments that pointed out the venture capital ties. They also utilized a coordinated public relations campaign at the MIT Bitcoin Expo in April 2025. The cohort's leaders used the university backdrop to project authority, dismissing widespread community opposition as "trolls" and "noise." The system designed to require broad consensus was being managed to produce the appearance of one. The decentralized community was systematically silenced by an institutional machine. --- On June 9, 2025, the uncapped OP_RETURN policy was merged into Bitcoin Core. Overriding the community's objections, the developers promised a harm-reduction measure. By opening OP_RETURN, they argued, existing spam would redirect into this cleaner channel, relieving pressure on the network. But post-merge data showed that the spam did not redirect. The original channels remained fully active while a new flood emerged through the uncapped space. The system load compounded. --- The 2025 merge redefined Bitcoin's governance by demonstrating exactly who holds the levers of power. This event, according to its critics, showed that Bitcoin Core could be influenced by a centralized group of operators willing to rewrite policy in ways that aligned with particular corporate interests. Whether one accepts that conclusion or not, the episode has become a case study in the governance of open-source infrastructure and a blueprint—real or perceived—for how a decentralized system can be captured from the inside out. Source from: CAPTURE An investigation into how informal power over Bitcoin Core was assembled, exercised, and defended by hodlonaut Article One of Four — The Network Article Two of Four — The Lever Article Three of Four — The Merge

The Capture of Bitcoin Core For years, Bitcoin maintained a reputation as the ultimate uncapturable network. It was designed to be decentralized, driven entirely by consensus, and highly resistant to corporate influence. In 2015, the community famously defended the protocol during the Block Size Wars, repelling a coordinated corporate takeover attempt. In June 2025, that streak ended. A heavily contested code change was pushed into the software despite overwhelming opposition from the community. The update targeted a feature called OP_RETURN, a space within a transaction meant to hold tiny amounts of arbitrary data, strictly capped at 80 bytes. The 2025 update stripped those limits away, allowing massive amounts of non-financial data to be embedded directly into the blockchain. Bitcoin requires broad consensus to function, and it has no central leadership. So how did a handful of developers manage to bypass the community and force a major policy change into the software? --- The path to this change began two years earlier with a six-line administrative edit that went virtually unnoticed. By early 2023, the small group of developers who maintain Bitcoin's reference software were seeing an influx of traditional venture capital funding. Major crypto investment firms began directly funding the developers responsible for the software's upkeep. This financial concentration caught the attention of the mainstream press. In February 2023, The Wall Street Journal profiled the vulnerability, highlighting how few people actually controlled the software and where their funding originated. Four months later, on June 6, a funded maintainer submitted a code update. It appeared to be routine housekeeping: a six-line adjustment to the software's documentation strings. The edit narrowed the written definition of the network's data limits. The original documentation stated that the limit applied to all data-carrying transactions. The new text restricted that definition to one specific data field. This left several newer data pathways completely unregulated, even though the underlying code itself had not changed. The update passed without scrutiny. But by quietly altering the official definitions, this developer cohort rewrote the rules of engagement for all future policy debates. --- In late 2023, new projects began exploiting the exact gaps left open by that documentation edit. The Bitcoin network was suddenly flooded with digital artifacts and spam, significantly increasing system congestion. The community attempted to respond. An independent developer wrote a software patch to restore the original data limits and secured an official security designation from the National Vulnerability Database to track the exploit. To get that patch implemented, it required approval from the Core maintainers. They rejected it. The cohort cited the six-line documentation edit from earlier that year to justify the rejection. They argued that because the documentation now explicitly excluded those data fields, the spam was technically within the rules. They claimed that fixing the loophole would violate the software's documented intent. In October 2024, during a closed-door developer session, the cohort administratively closed the issue tracking the formal security record, effectively erasing the vulnerability designation from the project's history. By manipulating bureaucratic definitions, a centralized group of developers proved they could protect the specific data streams they favored while blocking community security efforts. --- By early 2025, a specific corporate interest emerged. A venture-funded entity called Citrea was building a product that required massive, uncapped data limits on Bitcoin to function. To meet this requirement, an active Core developer commissioned another programmer to submit a code update. This new pull request proposed removing the OP_RETURN data limit entirely—a change explicitly requested on behalf of Citrea. When the community discovered the arrangement, they rejected the proposal by roughly a four-to-one margin, citing the clear conflict of interest. Rather than address the criticism, the developer cohort leveraged their administrative privileges on GitHub to suppress the backlash. They banned vocal critics, locked discussion threads, and hid comments that pointed out the venture capital ties. They also utilized a coordinated public relations campaign at the MIT Bitcoin Expo in April 2025. The cohort's leaders used the university backdrop to project authority, dismissing widespread community opposition as "trolls" and "noise." The system designed to require broad consensus was being managed to produce the appearance of one. The decentralized community was systematically silenced by an institutional machine. --- On June 9, 2025, the uncapped OP_RETURN policy was merged into Bitcoin Core. Overriding the community's objections, the developers promised a harm-reduction measure. By opening OP_RETURN, they argued, existing spam would redirect into this cleaner channel, relieving pressure on the network. But post-merge data showed that the spam did not redirect. The original channels remained fully active while a new flood emerged through the uncapped space. The system load compounded. --- The 2025 merge redefined Bitcoin's governance by demonstrating exactly who holds the levers of power. This event, according to its critics, showed that Bitcoin Core could be influenced by a centralized group of operators willing to rewrite policy in ways that aligned with particular corporate interests. Whether one accepts that conclusion or not, the episode has become a case study in the governance of open-source infrastructure and a blueprint—real or perceived—for how a decentralized system can be captured from the inside out. Source from: CAPTURE An investigation into how informal power over Bitcoin Core was assembled, exercised, and defended by hodlonaut Article One of Four — The Network Article Two of Four — The Lever Article Three of Four — The Merge

dewmap

24,448 görüntüleme • 2 ay önce

Cardano Tech Summit Buenos Aires 2025 and the regional LATAM Hackathon were much more than an event , they were a celebration of the samurai spirit of the Cardano community in LATAM 🥷⚔️ We want to express our deep gratitude to Cardano Foundation ,the web3innovationnerds , and Intersect for making this LATAM regional event possible and for supporting education and ecosystem growth in our region. We were honored to host key leaders, institutions, and projects from across the region and the global ecosystem, including representatives from UN Development, UBA (CUENTA OFICIAL) (Dean Guillermo (Willy) Durán), UTN Buenos Aires (Dean Guillermo J. Oliveto), the CEO of Blockchain.RIO, LABITCONF, Rafael Fraga, Jack B, Easton Evans, David Casey, Cardano Feed ($ADA), Funintec Venezuela, GovChainLab, @DanielaHubBr, Mauricio Navarrete R, Juan TheOne, Carlos Lopez de Lara, Santiago Carmuega, Fede | TxPipe.io | 🧉, Martin Rivero, Modulo-p, Cointelegraph en Español, as well as projects and organizations such as lace.io, Midnight Foundation, TxPipe, Fairgate, @Tokenmithr, Sead,GameChanger Wallet, ExuraLabs, Edda Labs, KW₳RXS, Jotape | CTimelines.io, De Desciquark a Synthum, Potion Tools Collective, SenseiNode, Funding the Commons, among many others who contributed with content, workshops, presentations and community energy. Highlights included a simultaneous chess exhibition led by a female Olympic player, 3 HYDRA machines running live, MANDALORIAN for midnight privacy, workshops about MIDNIGHT, Intersect VISION 2030, Txpipe , and 7 technical talks, and the inauguration of the Laboratory of Decentralized Computing and Digital Trust by IO Research , with an academic track on verifiable computation, zkVMs, private verifiable computation and MPC mythbusting. The entire event was designed around a Japanese theme, honoring Cardano’s origins in Japan and the warrior spirit of the builders who completed the IOG-led course and hackathon :Hackathon prizes of 10,000 USD, awarded together with katanas in three categories: black, red, and white 🥷 • Taiko performances, Kendo demonstrations, and a Japanese food experience with Dorayaki (traditional Japanese sweet) and sushi for attendees • Special merch: a Japanese-style mate, symbolizing the cultural bridge between Japan, Argentina, and LATAM We want to thank Charles Hoskinson and J.J. Siler for making the inauguration of the Laboratory of Decentralized Computing and Digital Trust at the Summit possible. Huge thanks as well to the four instructors of the Hackathon and Developers course – Roberto, kada Chaires, J₳MS and Antonio Ibarra – and to ADA DOG POOL (ticker: DOG) and CHIL Stake Pool - Rodrigo, who did an amazing job as Masters of Ceremony for the Summit. Finally, a very special thank you to Cardano Foundation’s Marketing Director Laura M. and Elis Moormaa for their constant support and attention to every detail of the event. 🙌 To every participant, speaker, volunteer, sponsor, and project: thank you for making this possible – this video is just a glimpse of what Cardano in LATAM is becoming. 🚀 #CardanoCommunity #CardanoSummit2025 Cardano CardanoSummit

Cardano Tech Summit Buenos Aires 2025 and the regional LATAM Hackathon were much more than an event , they were a celebration of the samurai spirit of the Cardano community in LATAM 🥷⚔️ We want to express our deep gratitude to Cardano Foundation ,the web3innovationnerds , and Intersect for making this LATAM regional event possible and for supporting education and ecosystem growth in our region. We were honored to host key leaders, institutions, and projects from across the region and the global ecosystem, including representatives from UN Development, UBA (CUENTA OFICIAL) (Dean Guillermo (Willy) Durán), UTN Buenos Aires (Dean Guillermo J. Oliveto), the CEO of Blockchain.RIO, LABITCONF, Rafael Fraga, Jack B, Easton Evans, David Casey, Cardano Feed ($ADA), Funintec Venezuela, GovChainLab, @DanielaHubBr, Mauricio Navarrete R, Juan TheOne, Carlos Lopez de Lara, Santiago Carmuega, Fede | TxPipe.io | 🧉, Martin Rivero, Modulo-p, Cointelegraph en Español, as well as projects and organizations such as lace.io, Midnight Foundation, TxPipe, Fairgate, @Tokenmithr, Sead,GameChanger Wallet, ExuraLabs, Edda Labs, KW₳RXS, Jotape | CTimelines.io, De Desciquark a Synthum, Potion Tools Collective, SenseiNode, Funding the Commons, among many others who contributed with content, workshops, presentations and community energy. Highlights included a simultaneous chess exhibition led by a female Olympic player, 3 HYDRA machines running live, MANDALORIAN for midnight privacy, workshops about MIDNIGHT, Intersect VISION 2030, Txpipe , and 7 technical talks, and the inauguration of the Laboratory of Decentralized Computing and Digital Trust by IO Research , with an academic track on verifiable computation, zkVMs, private verifiable computation and MPC mythbusting. The entire event was designed around a Japanese theme, honoring Cardano’s origins in Japan and the warrior spirit of the builders who completed the IOG-led course and hackathon :Hackathon prizes of 10,000 USD, awarded together with katanas in three categories: black, red, and white 🥷 • Taiko performances, Kendo demonstrations, and a Japanese food experience with Dorayaki (traditional Japanese sweet) and sushi for attendees • Special merch: a Japanese-style mate, symbolizing the cultural bridge between Japan, Argentina, and LATAM We want to thank Charles Hoskinson and J.J. Siler for making the inauguration of the Laboratory of Decentralized Computing and Digital Trust at the Summit possible. Huge thanks as well to the four instructors of the Hackathon and Developers course – Roberto, kada Chaires, J₳MS and Antonio Ibarra – and to ADA DOG POOL (ticker: DOG) and CHIL Stake Pool - Rodrigo, who did an amazing job as Masters of Ceremony for the Summit. Finally, a very special thank you to Cardano Foundation’s Marketing Director Laura M. and Elis Moormaa for their constant support and attention to every detail of the event. 🙌 To every participant, speaker, volunteer, sponsor, and project: thank you for making this possible – this video is just a glimpse of what Cardano in LATAM is becoming. 🚀 #CardanoCommunity #CardanoSummit2025 Cardano CardanoSummit

ADA Solar

14,646 görüntüleme • 10 ay önce

HUGE PULSECHAIN NEWS:🚨🚨🚨 Pulsechain is now being promoted at nearly every music event in the nearby city, art exhibitions, community events and… IVE JUST GOTTEN STARTED🪖 I have had a conversation with most of the local music concert promoters, event promoters, and party promoters in a city of close to 2 million people. Pulsechain tablets will be announced and made available to all attendees that are interested at every event. I have also been personally handing out the tablets at the events and have had many wonderful conversations with people new to crypto and people that have been in crypto for up to 8 years. I’ve found it really opens the door for me to have real conversations with people. It’s a new route I decided to try and I wanted to give y’all the positive feedback I’ve been encountering.🙌 THIS IS MASS MARKETING IN A WHOLE CITY OF CLOSE TO 2,000,000 PEOPLE🚀🚀 I have already attended two events this last weekend and close to 200 people out of the crowds were interested and came to find me and receive their tablets and discuss Pulsechain, freedom, Richard Heart and crypto as a whole. I only had 200 tablets on me, so when the pallets arrive in my city I’ll get right back to this promoting. For now, I’m temporarily out of tablets. I was lucky enough to be able to get my hands on a few this early in Canada. Thank you ⬣ AWildSJ ⬣ and everyone at the foundation for being wonderful leaders and professional to deal with. You guys are doing a fantastic job🫡 My plan is to do my part and personally distribute 4000 tablets minimum (maybe more) into the hands of people who are actually interested in hearing about Pulsechain in my city. I do this by announcing why I’m at the event first on the microphone and only people that are interested in learning about freedom and crypto education come to find me where I set up at the event. Also, I let everyone know I’m not a financial advisor, to do their own research, and that this is for educational and awareness purposes only✅ I encourage everyone who is currently a Pulsechain community member to do the same thing I’ve started doing and try to find events where you can open up conversations and give tablets out at. It works! Or figure out your own unique way you can utilize the tablets to promote Pulsechain 🧠 You all know I’m a Pulseguy and a Pulsegal supporter. This is the dedication $PULSEGUY and $PULSEGAL have to promoting and onboarding many to Pulsechain🫡 And yes, anyone that’s into meme coins, I will be directing them to Pulseguys and Pulsegal🚀 I will get some video content at the next event and share it with y’all. I didn’t have anyone with me to video this time while I was busy promoting but moving forward, I have a couple bullish volunteers who will be attending with me. In the future, when I’m back to travelling overseas and to USA often, I also plan to take promotional pictures and videos holding the tablets with anyone famous that I know or encounter. However, this last part is better saved for when we reach euphoria. It will have more impact and effect at that point because it will hype up the normy retail people😂 *not financial advise*

HUGE PULSECHAIN NEWS:🚨🚨🚨 Pulsechain is now being promoted at nearly every music event in the nearby city, art exhibitions, community events and… IVE JUST GOTTEN STARTED🪖 I have had a conversation with most of the local music concert promoters, event promoters, and party promoters in a city of close to 2 million people. Pulsechain tablets will be announced and made available to all attendees that are interested at every event. I have also been personally handing out the tablets at the events and have had many wonderful conversations with people new to crypto and people that have been in crypto for up to 8 years. I’ve found it really opens the door for me to have real conversations with people. It’s a new route I decided to try and I wanted to give y’all the positive feedback I’ve been encountering.🙌 THIS IS MASS MARKETING IN A WHOLE CITY OF CLOSE TO 2,000,000 PEOPLE🚀🚀 I have already attended two events this last weekend and close to 200 people out of the crowds were interested and came to find me and receive their tablets and discuss Pulsechain, freedom, Richard Heart and crypto as a whole. I only had 200 tablets on me, so when the pallets arrive in my city I’ll get right back to this promoting. For now, I’m temporarily out of tablets. I was lucky enough to be able to get my hands on a few this early in Canada. Thank you ⬣ AWildSJ ⬣ and everyone at the foundation for being wonderful leaders and professional to deal with. You guys are doing a fantastic job🫡 My plan is to do my part and personally distribute 4000 tablets minimum (maybe more) into the hands of people who are actually interested in hearing about Pulsechain in my city. I do this by announcing why I’m at the event first on the microphone and only people that are interested in learning about freedom and crypto education come to find me where I set up at the event. Also, I let everyone know I’m not a financial advisor, to do their own research, and that this is for educational and awareness purposes only✅ I encourage everyone who is currently a Pulsechain community member to do the same thing I’ve started doing and try to find events where you can open up conversations and give tablets out at. It works! Or figure out your own unique way you can utilize the tablets to promote Pulsechain 🧠 You all know I’m a Pulseguy and a Pulsegal supporter. This is the dedication $PULSEGUY and $PULSEGAL have to promoting and onboarding many to Pulsechain🫡 And yes, anyone that’s into meme coins, I will be directing them to Pulseguys and Pulsegal🚀 I will get some video content at the next event and share it with y’all. I didn’t have anyone with me to video this time while I was busy promoting but moving forward, I have a couple bullish volunteers who will be attending with me. In the future, when I’m back to travelling overseas and to USA often, I also plan to take promotional pictures and videos holding the tablets with anyone famous that I know or encounter. However, this last part is better saved for when we reach euphoria. It will have more impact and effect at that point because it will hype up the normy retail people😂 not financial advise

Dosmon

15,142 görüntüleme • 21 gün önce