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今晚加拿大 vs 波黑，我买加拿大赢 🇨🇦 加拿大这几年进步很明显，前场速度、身体对抗和冲击力都提升不少。面对波黑这种节奏偏慢、后防转身不快的球队，加拿大的边路推进和反击会很有威胁 波黑虽然名气还在，但稳定性一般，阵容年龄偏大，攻防转换容易脱节。如果加拿大把节奏拉快、持续冲击防线，这场主场拿分希望不小 想跟着比赛做预测的话，可以看看 @MGBX_ZH 正式上线的 “MGBX 预测市场” 最近有三个活动可以预测同时拿奖金，总奖池一共10,000 USDT： ⚽️ 首单预测礼 第一次在预测市场买入，只要下单金额达到10u，就有机会获得2u奖励，名额仅限前500名，适合新手小额体验 ⚽️ 世界杯猜王榜 平台每周会统计世界杯相关比赛的买入+卖出交易额，冲进Top10就能拿奖励，榜一有240u ⚽️ 预测全能王榜 不限足球，整个预测板块都算！一周内参与至少3种不同类型预测，有效交易额≥100u，就可以冲击Top10奖励 活动时间从 6 月 9 日持续到 7 月 19 日，每周独立结算 喜欢边看球边做判断的，可以趁这波活动去体验下，DYOR 传送门👉：

6月12日 加密，美股🇺🇸行情分析 ‼️ 【美股】 昨日美股科技修复，晚上关注SpaceX的第一次表演。 可能后续一周埃隆马斯克成为个人财富1万亿美金第一人。 今晚的上市是否会带崩之前的科技还是大家高歌猛进看今晚。 【 bitcoin:native 抄底三部曲】 1.每天观察日线级别是否继续创新低。【满足，关注周一】 【最低点： BTC：59130.91 ETH：1505.68，不再创新低】 2.关键位置的低点，需要整数关口数字。【不满足，没有整数关口】 【没有整数关口】 3.关注12小时级别的底分型的形成。【满足】 【出现扭转分型】 以上三点(2/3)，继续等待，等待最后一个信号，破低点大概率也是后上车多单。 结论【震荡休整】 策略：✅中枢盘整✅ 1️⃣ 大盘 【BTC ETH】当前关键支撑位：交易策略没有变化，看今晚最大IPO的吸血能力。 【BTC】空 开仓：上涨破64250可布局空单 止损：12小时收盘价高于64500 止盈：60800 【ETH】空 开仓：上涨破1710可布局空单 止损：12小时收盘价高于1738 止盈：1620 【BTC】多单 开仓：下跌至60000左右多单 止损：12小时收盘价低于59000 止盈：64000附近 【ETH】空 开仓：下跌至1600左右多单 止损：12小时收盘价低于1505 止盈：1700附近 【BTC】【ETH】关注BTC：59000，58000，55000, ETH:1500 , 1450跌幅收窄底部区域附近了。底部区域附近，直线拉飞的可能性不大，底部开始震仓吸筹需要本周完成，不要暴跌就是胜利。 如果对你有帮助 请给强哥点赞👍+关注11 所有观点仅代表个人看法 不作为任何投资建议DYOR

$AMD| The FOMO to buy @AMD Chips is NOW 🧵 Not Financial Advice! DYOR! Research Purpose Only! The Inference Queen is the biggest winner in Agentic AI where all other CPUs are struggling to compete with a 2yr old EPYC Turin and EPYC Venice is in mass production phase. AMD stresses deployability today on standard x86 platforms (no proprietary architectures required), full software compatibility, and open standards. This positions Venice + Helios as a practical, high-density alternative to competing solutions while underscoring that agentic AI shifts the balance toward CPU-rich racks alongside GPUs, and most importantly, lowering the cost of token to accelerate adoption and innovation. Context: @WSJ yesterday came out with an article that @OpenAI is condiering drasstically lowering the token prices to win more customers from Anthropic. The narrative "they" are trying to exacerbate the current AI selloff won't last long. This is a fundamental misunderstanding of what is going on, or what I already discussed for months and years. Followers and Subscribers already knew this for years, that this day would come, where token cost will bcome the central discussion among enterprises as there is no such thing as unlimited budget or Tokenmaxxing when they use $NVDA chips or In-house Hyperscalers chips. I will link various threads if you are interested in understanding the full picture from supply chain to recent TSMC Rapid 2nm expansion up to 12 Fabs total by 2027/2028. Hyperscalers and AI natives effectively have no choice but to buy more AMD system for Agentic AI as leadership in economical, power-aware, high-volume internal + agentic use. However, due to supply constraints where Supply is far behind Demand, this makes multi-vendor reality along with in-house chips drive faster industry progress, lower overall costs, and better sustainability. NVIDIA’s Vera Rubin cannot compete with a 2 years old EPYC Turin, but AMD under Dr. Lisa Su has engineered the lowest cost-per-million-tokens, highly competitive energy-efficient solutions, and superior CPU orchestration for agentic AI at scale with Helios. Dr. Su has championed this shift since at least 2023, foreseeing the rise of agentic workflows that demand far more orchestration, parallel agents, and balanced compute well before the industry fully embraced it. Her long-term vision of AI moving from simple prompts to always on, multi-agent systems has driven AMD’s investments in high-core EPYC CPUs and integrated rack-scale solutions, perfectly positioning the company for today’s realities. The OpenAI-AMD 1GW Helios deployment (starting H2 2026) represents a pivotal vertical integration move that directly supercharges the inference economics. This isn't incremental; it's a structural shift toward ownership of massive, optimized rack-scale capacity, enabling the lowest token costs and triggering the enterprise adoption flywheel. We need to be honest, $AMD is the only company that made a big bet on Inference since the day Chatgpt became sensational where $NVDA and others were betting big on Training. At the end of the day, Token bill from @AnthropicAI has to obey economics. Meaning the bills rise, companies have to get more out of it to justify the cost. It cannot be an unlimited inference budget, and it has to show up on efficiency, profitability and operating leverage. 1. Tokenomics After you understand this, you will understand why Citi cited @AnthropicAI is likely to sign a deal with $AMD along with Hyperscalers, AI Labs, Sovereign AI like Softbank 5GW in France and many other countries. However, OpenAI and $META are now wanting faster deployment, and they are AMD shareholders now, they have prioritized allocation. Anthropic and Hyperscalers just cannot compete when Helios Rack lower token cost to$0.0003–$0.0005 per million tokens at GW scale. Cost to build 1GW data center 1GW Helios Rack full build is estimated $30-$35B 1GW Rubin Rack full build is estimated $45-$55B Inference (Cost per Million Tokens) ~$NVDA B200 / HGX: ~$0.02–$0.08 on optimized workloads (FP4/MXFP4, speculative decoding). Significant improvement over Hopper but still premium-priced. GB200 NVL72 rack-scale: $0.05–$0.25+ ~$AMD Helios Racks: $0.0003-$0.0005 per M tokens, dramatically lower than NVIDIA equivalents in owned infra. MI355X node-level: Up to 40% more tokens per dollar vs. competing solutions ( B200), driven by higher memory capacity (up to 288GB+ HBM), strong bandwidth, and lower acquisition costs. Training ~$NVDA Rubin Rack is estimated $0.7-$1.2/M Tokens ~$AMD Helios Rack is estimated $0.65-$1.0/M Tokens Now, OpenAI, META and Hyperscalers can lower Inference cost even further with $AMD EPYC Venice "dense rack" or Agentic AI Rack. AMD published a detailed technical blog emphasizing that the future of agentic AI autonomous, multi-step AI systems requiring heavy orchestration, databases, caching, APIs, and control planes demands massive CPU-dense rack-scale infrastructure, not just GPUs. The catalyst prominently positions their upcoming 6th Gen EPYC "Venice" processors as the key enabler for next-generation dense racks, delivering leadership throughput under real-world power, cooling, and density constraints. ~EPYC Venice (Zen 6 architecture, up to 256 cores / 512 threads per socket) is projected to deliver exceptional rack-level performance. In AMD’s modeled 100 kW rack comparisons, Venice-powered systems are expected to achieve ~3.30x the throughput of NVIDIA’s Vera (88-core Olympus) baseline across a broad mix of agentic-supporting workloads. ~This builds on current-generation 5th Gen EPYC "Turin" (up to 192 cores), which already delivers ~2.37x rack throughput vs. Vera and ~1.6x vs. Intel’s Xeon 6980P (128 cores). ~ Liquid-cooled Turin deployments already support >27,000 CPU cores per rack today. Venice is architected to push this beyond 36,000 cores in the same rack class, dramatically increasing concurrent agent capacity and overall infrastructure efficiency. 2. Ownership vs renting compute from Hyperscalers matter to OpenAI and only owning $AMD chips can meaningfully lower token cost for enterprises. ~Eliminates cloud overhead: No provider margins, utilization buffers, or egress fees. Direct control over power contracts, cooling, scheduling, and orchestration at dedicated facilities. ~Helios optimizations at GW scale: Rack-level density (1.4+ exaFLOPS FP8 per rack), high HBM4 bandwidth, EPYC orchestration for agentic workloads, and superior TCO/TDP. AMD's long-standing focus on tokens per dollar/watt shines here 20-40%+ efficiency edges in inference-heavy scenarios. ~At 1GW+ optimized deployment, inference hits $0.0003–$0.0005 per million tokens (community/analyst models tied to Helios metrics). This is dramatically lower than typical rented/cloud equivalents, especially for high-volume output tokens in agentic flows. High token bills today, enterprises running heavy agentic/coding/analysis workloads can face $50-100M+/month at current API rates (flagship models $5-30+/M output, scaled to massive volumes). Post-Helios compression, same volume will drop to $10-15M/month (or better) via lower underlying costs passed through as pricing flexibility, volume tiers, caching, or batch discounts. ROI thresholds collapse. More companies greenlight pilots → production → massive scaling. Agentic AI (autonomous workflows) multiplies token demand exponentially, but affordability removes the friction. OpenAI gains flexibility, Unlike more cloud-dependent rivals (Anthropic), they can lower effective pricing, offer aggressive enterprise bundles, or absorb volume without margin destruction directly tackling "high token bill" complaints while maintaining profitability as usage explodes. 3. Agentic AI Models shifted CPU:GPU Ratio to 1:1 toward 3-5:1 with Explosively Token-Hungry Workloads Agentic AI (autonomous, multi-step agents with planning, tool use, iteration, and self-correction) is fundamentally more compute and token intensive than conversational or single-turn generative AI. Agentic AI. autonomous, multi-step workflows with orchestration, tool use, parallel agents, data movement, and enterprise integration has dramatically increased the importance of strong host CPUs alongside GPUs. This shifts the CPU-to-GPU ratio higher and makes balanced systems critical toward 1:1 to 5:1 as enterprises testing more than 5-10 agents. AMD EPYC Venice excels ~Leadership core density (up to 256 Zen 6 cores per socket) for running many agents in parallel, orchestration layers, and high-throughput control-plane tasks. ~Superior performance-per-core and power efficiency ( up to 2.1x higher perf/core and 2.26x better SPECpower vs. NVIDIA Grace in benchmarks). ~Tight integration in Helios: One Venice CPU + multiple MI450 GPUs per node, enabling efficient data feeding to GPUs ("zero-copy"), parallel execution, and full rack utilization for complex agentic loops. Hyperscalers (Meta, Microsoft, Amazon, Google, Softbank) and AI natives (OpenAI, Anthropic...) are adopting high-core EPYC at scale specifically for these agentic demands, as CPUs now handle a larger share of non-model work (orchestration, policy enforcement, tool calls). This complements AMD’s lower-cost GPUs for overall TCO wins. ~Agents often generate 10–100x+ more tokens per task due to iterative reasoning chains, multiple tool calls, verification loops, and long-context orchestration. ~Goldman Sachs forecasts token consumption multiplying 24x by 2030 (to 120 quadrillion tokens/month) largely driven by agentic adoption in consumer and enterprise. ~Enterprise data shows agent-pattern workloads growing at 680% annualized rates, projected to surpass conversational AI in token volume by Q3 2026. ~Daily enterprise agent token consumption is already in the billions, with complex workflows (coding, workflows, analysis) amplifying this dramatically. 4. Competitive Edge: Winning Customers from Anthropic Anthropic’s Claude models (especially Opus/Sonnet) excel in complex reasoning and agentic coding, commanding premium positioning. However, their higher underlying costs (heavier reliance on third-party cloud with margins) limit pricing flexibility compared to OpenAI’s owned Helios capacity. Anthropic is on track to generate $10.9 billion in Q2 revenue. The company expects to achieve its first-ever quarterly adjusted operating profit of $559 million. However, sustaining full-year profitability remains challenging due to immense computing and model training costs The truth is, Anthropic has no choice but to buy as much $AMD chips as possible if they want to compete with OpenAI or get investors attention. This 5% adjusted operating profit to revenue ratio is just pathetic. Current pricing dynamics (2026): OpenAI already undercuts on many tiers ( flagship output tokens significantly cheaper than equivalent Claude Opus). Nano/mini models offer 5–10x advantages for volume work. Anthropic holds edges in long-context flat pricing and certain reasoning quality. OpenAI after Helios Rack Ownership, At $0.0003–$0.0005/M effective costs, OpenAI gains massive headroom to: ~Aggressively discount high-volume agentic tiers or bundles. ~Offer “unlimited” enterprise plans or usage-based models that Anthropic struggles to match without margin erosion. ~Target cost-sensitive, high-throughput agent deployments (dev tools, automation platforms) where token bills explode. Enterprises facing $ millions in monthly agentic bills will migrate to the provider delivering better economics at scale. OpenAI’s combination of strong models (o-series reasoning) + lowest TCO positions it to erode Anthropic’s enterprise share, especially as agentic becomes the dominant token consumer. Cheaper tokens expand the total addressable market dramatically. This feeds the data/model improvement loop, justifying further capex. AMD benefits from proven scale pulling in more customers (Meta, Oracle, Microsfot, Amazon, Softbank, TensorWave, LumaAI ... already aligned on Helios). Conclusion: Dr. Lisa Su has been laser focused on inference economics since at least 2022–2023, repeatedly emphasizing that the real battleground for AI scalability would be TCO, power efficiency (TDP), and ultimately tokens per dollar and per watt not just raw training FLOPS. While many viewed inference as a secondary, commoditized workload, Dr. Su architected AMD’s roadmap around rack-scale systems optimized for high-volume, sustained inference that would dominate as models matured and usage exploded. Helios represents the culmination of that multi-year bet: a fully integrated, open platform designed precisely for the economics of massive token throughput. This deep, strategic partnership with OpenAI starting with the 1GW Helios deployment in H2 2026 and scaling to 6GW, is the embodiment of that shared vision. Both companies foresaw a future where agentic AI models evolve to become extraordinarily token-hungry: autonomous agents executing complex, iterative workflows with planning, tool use, verification loops, and long-context reasoning. These workloads can consume 100x+ more tokens per task than traditional chat or single-turn generation, driving exponential demand as capabilities improve and enterprises deploy them at scale. By owning and optimizing this massive Helios capacity at GW scale, OpenAI achieves inference costs as low as $0.0003–$0.0005 per million tokens. This structural cost advantage allows OpenAI to absorb the coming token explosion profitably, dramatically lower effective pricing for enterprises, and win high-volume agentic workloads from higher-cost competitors like Anthropic. What was once a prohibitive monthly token bill becomes an affordable accelerator for productivity and innovation. The OpenAI-AMD alliance validates Dr. Su’s prescient strategy and turns the Agentic flywheel into reality: Collapsing inference costs → explosive token consumption → richer data and better models → accelerate greater demand. This partnership doesn’t just address today’s economics, it positions both leaders at the center of the infrastructure buildout that will power AI’s next decade. By delivering the lowest inference economics at scale, OpenAI not only solves enterprise bill pain but gains a decisive weapon to win share from higher-cost rivals like Anthropic. And that is why @OpenAI and $META will deploy EPYC Dense Rack Not Financial Advice! DYOR! Research Purpose Only!

📅 世界杯开幕预测 · 2026年最精彩的一届 2026世界杯今晚凌晨正式打响 48支球队，16个城市，美国+加拿大+墨西哥三国联办，史上规模最大的一届 我其实是不看足球的，是昨晚 @babemiki209 告诉我，她原本想回加拿大现场看球赛，因为这届世界杯真正让人无法平静的原因只有一个 这是最后一次 👑 巨星谢幕倒计时 🇦🇷 梅西 · 39岁 · 2022卡塔尔终于圆梦，这是他的告别演出 🇧🇷 内马尔 · 34岁 · 伤病缠身仍归来，巴西人的最后期待 🇵🇹 C罗 · 41岁 · 超越时间的男人，这次真的是最后一次 三个人同台，可能是足球史上最后一次 不看进球，就看这件事本身，已经值回票价 我哪懂啊，我只懂看帅哥 🔮 预测市场今年最火 随便打开预测市场平台的页面 冠军归属、小组出线、梅西进球数、内马尔首场是否上场……每一个问题背后都是真金白银在博弈 预测市场有意思就在这里，它不是在猜，是在用钱表达判断。赔率会实时反映大家对这届世界杯的集体定价。比FIFA的官方预测更诚实 📊 小组赛首战：🇲🇽墨西哥 VS 🇿🇦南非 👉 今晚开幕赛，你的判断是？ □ 🇲🇽 墨西哥 □ 🇿🇦 南非 □ 平局 ⭕️ 战力速览 🇲🇽 墨西哥 ▪️ 东道主 + 高海拔主场，对手体能消耗大 ▪️ 近8场不败，6胜2平，最近5-1大胜塞尔维亚 ▪️ 阿兹台克球场底蕴加持，大赛经验无出其右 🇿🇦 南非 ▪️ 非洲代表，速度快、冲击力强 ▪️ 2010年东道主，有世界杯DNA ▪️ 但客场高原作战，体能是最大变数 我的判断：墨西哥赢，但别指望大比分。（虽然我也不太懂），听朋友分析的，主场+海拔双重优势，南非体能扛不住下半场 有没有人今年跟着世界杯做预测市场的？ 来评论区说说你押哪队冠军 👇 DYOR 非投资建议 #世界杯2026# #WorldCup2026#

2026年世界杯即将开幕，我们也别只看AI啥的了，我们来看看竞技体育。 旧王落幕，新王崛起 Messi和Ronaldo的“最后一舞”，使得这届世界杯的看点拉满。同时今晚8:30美国5月CPI数据即将发布，对于股市的走向将是关键。 不评价哪支球队厉害，只想搞钱 大家都知道，每届世界杯都是球迷们的狂欢，也是赌徒的狂欢。 所以，球星们代言的产品，会随着比赛的表现、新闻等受到剧烈的波动 美股 $DKNG ：博彩龙头 $NKE：耐克，C罗、姆巴佩代言 $ADDYY：阿迪，FIFA官方伙伴，梅西代言 港股 申洲国际 ( 安踏体育 ( 裕元集团 ( 海信家电 ( 回顾历史上世界杯期间，体育与博彩股，在球星叙事、品牌曝光的影响下，股价波动很大。 个人看法 这类股票只能做短中期，后期不建议参与。 而且，有些事情不建议参与，稳当当的买点股票就挺好 同时对于球星的新闻，一定要重点关注，因为这会直接影响股价走势。 同时相关的产业和股票还有很多，大家可以多关注 最后 祝大家喜欢的球队和球星取得好成绩 一念天堂，一念地狱 DYOR #美股# #世界杯#

兄弟们，杠杆交易那点破事我算看透了。 每次一开仓就盯着价格心跳加速，生怕爆仓睡不着觉，对吧？ TermMax Alpha 这玩意儿不一样，它直接把风险给“封顶”了。你想赌NVDA、QQQ、SPY这些方向，没错，但最多就亏掉你一开始付的那点固定费用，不会因为市场抖一下就清零。 项目方刚在BNB链上给这些Ondo的代币加了更多到期时间和行权价，选的空间更大了。想做多做空都行，规则提前说死，成本固定，没那些乱七八糟的追缴。 交易的人：相当于有杠杆，但不用天天提心吊胆。 放钱的人：把资产放进去就能赚，相当于拿固定收益等行情。 我自己试了下，感觉这模式挺实在的，不像传统DeFi一惊一乍。感兴趣的可以点进去看看： （纯个人体验分享，DYOR啊） @TermMaxFi

美国本土财阀的关系和人脉还是NB啊。SpaceX的申购价，Kraken海妖 135美金，算上5%的费用，也就是141美金左右。目前相对其他，很良心了。 SpaceX总额度里，Kraken 400M，Bybit 100M(额度还是xStocks给bybit的，xStocks是Kraken子公司)。 相当于在Kraken这里打钱登记，Kraken会把总额度给承销商，承销商来进行IPO分配。然后Kraken会在CEX和链上提供流动性开放交易。开盘后做LP的话，说不定年化能过千，因为理论上，Kraken也要拿到股票后才能去兑换成代币组池子。 Kraken马上要上市了。比99%的交易所都合规，应该不敢乱搞。闭眼冲这个Kraken海妖打新啊，兄弟们。 DYOR 注册链接： 身份证就可以注册，KYC的时候一定要把地址写成和身份证上的完全一致。就不会弹地址证明要求。

特朗普最近几个月一直在暗示你该买哪些美股？普通人玩美股最头疼的就是不知道买啥。 其实思路超级简单： 第一选择：直接定投标普500或纳指100，长期基本稳赚，不用操心选股。 第二选择：跟着特朗普的交易和公开表态走（下面附上好用的追踪网站）。 他最近大举买入并多次提及的标的，很多人都提前埋伏了，比如 $INTC $DELL $MU 等科技暴涨股。特朗普重点点名领域及标的（基于近期公开信息整理）： AI： DELL MU SNDK WDC 芯片： INTC AMD NVDA TSMC ARM 太空： RKLB PL SATS 加密货币： HOOD CRCL PURR 能源： BE GEV FCEL STE 无人机： UMAC ONDS AVEX 核能： X CCJ OKLO UUUU 机器人： OUST AEVA 量子： IONQ QBTS RGTI INFQ 电池： FLNC AMPX KULR 医疗保健： OSCR CLOV 光子学： AXTI AAOI LITE CRDO 稀土： USAR CRML TMC 制造业： STRL CDNL 关键矿产： TMQ MP LAC 想实时跟进特朗普及其团队的交易记录？推荐这些靠谱网站（数据接近官方，方便排序查看）： Trump Tracker： 覆盖政府人物交易和资产，一站式浏览超级方便。 OGE官网： 最权威的原始披露文件，虽有PDF较多，但最官方。 ProPublica： 聚合多位官员披露，搜索和辅助分析很实用。 TrumpTrades： 特朗普Q1交易可视化数据库，能轻松看清行业分布和热门标的。 Open Cabinet： 追踪特朗普官员OGE交易记录，数据最全最直观，支持按行业和Top标的排序。 额外推荐一个类似好用的： Unusual Whales Trump Portfolio： 专业追踪政客股票交易历史和持仓，数据实时性强，适合想看完整画像的朋友。这些网站都是事后公开数据，会有一定延迟，适合做长期参考和灵感来源。 平时多看看关注特朗普的讲话和采访，也经常能抓到新机会。 投资有风险，以上仅供参考，DYOR！

黑莓 $BB 最近风声挺大的，今天下午占卜了，想着币安支持美股，现在手续费又降低了，只要万分之五，我就占卜下，看看能不能买的。 结果不行，就没在币安买这只股票了。 月，日都占卜了，晚上想整理，但是脖子太痛了，晚上 7:35 分，在 BIT 说了简要观点。 日我也占卜了，目前看基本应卦，我占卜时候盘前价格 11.38，现在回调了一点。 明天我不整理细节了，这里说下简要观点，甲午月走势前期不太好，回调力度也不小的。 我今天的港美互联的占卜非常关键，因为涉及美股，如果预测对了，应该会帮助到有缘人。 #Dyor#