🚨SlowMist TI Alert🚨 AIDC token on BSC has been exploited. 💸 Loss: 220.12 WBNB (~$120929.35) 🔍 Root Cause: AIDCToken's `_sellTransfer()` accumulates a 30% burn amount without deducting it from the seller. Subsequently, any non-Pair transfer triggers `_executeAccumulatedBurn()`, which incorrectly burns tokens from the `uniswapPair` balance instead of the seller. After burning, `sync()` is called, artificially deflating the AIDC reserve in the AMM, allowing the attacker to drain WBNB. 📌 Attacker: 0x89eb2c99e970d831525c7a52badc290afa116b63 📌 Victim: 0x2725033282b3bd4be8873b7f0f622c18e3b7cbd8 (Pancake V2 AIDC/WBNB Pair) 📌 Vulnerable Contract: 0x5021d71859f81b4c905b573591db8f9cc4a0c6fe (AIDCToken) The attacker exploited a flawed burn mechanism where sell-induced burn debt is wrongly imposed on the liquidity pool, enabling repeated reserve manipulation and a final swap that drained nearly all WBNB from the Pair. Powered by #SlowMist#.AI

@Bitdeer has executed a 16-year #AIDC# colocation lease for Tydal, Norway 🇳🇴 Campus with Volta, an @nvidia Cloud Partner. 🤝 ~$4.7B in contracted base-term revenue, with the potential to reach $8B over 24 years. ⚡️ 121 IT MW configured to run #NVIDIA# GPUs for a leading AI lab, with @Dell as the #technology# provider. ♻️ 100% renewable energy with ~1.1 PUE, TDC expected to be among Norway's most efficient #AIInfrastructure# upon completion. 🛡️ Anticipated credit backstop totaling ~$1.3B, arranged via Letter of Credit by affiliates of @jpmorgan and another top-tier global financial institution. Read the full details here: $BTDR #Bitdeer# #datacenter# #gpu#

Compute is the hard currency of AI. At SF Tech Week, we brought together founders and leaders building data centers, power, chips, neoclouds & compute markets for the AIDC Builder Dinner, with @ellazhang516 @Hui_Huangg hosting in person. Thanks to all who made it special ✨

Weekly|Singapore Gathering, Malaga ECOC Happy Hour, AI Labs Keep Training, Optics Supply Tightens, AIDC Power, CRM Dreamforce, PLTR Sovereign AI, BE First, thank you to everyone who joined our gathering in Singapore this week. Registration and attendance were well beyond our expectations, and the atmosphere was amazing. Members of both our analyst and developer teams were present and had great conversations with investors and industry experts. Next, our analyst Fabian will attend ECOC in Malaga, Spain on Sep 22-23 and will host a happy hour there. Please RSVP if you are interested. Coming back to the market, the AI hardware selloff after Amodei’s call for restraint looked overdone to us, and the subsequent rebound suggests investors are reconsidering what a slowdown would actually mean. We spoke with people at three frontier labs: internal training and compute expansion are continuing, while additional safety checks are more likely to lengthen evaluation and public-release timelines. Safety risks deserve attention, but our base case remains limited disruption to near-term infrastructure demand. The enterprise side helps explain that view. In our 41-company Tokenomics panel, less than 5% of AI spending goes to the most advanced frontier models. Existing deployments can keep expanding as models become cheaper, more reliable, and easier to integrate. Greater scrutiny also creates work for security platforms and identity providers: enterprises need to monitor agents in production, govern what they can access, and retain logs they can trust. Drug discovery gives us another reason to be constructive on AI demand beyond the current enterprise rollout. The Morgan Stanley Healthcare Conference commentary points to early spending across the workflow: TMO is already seeing AI-driven high-throughput experiments lift reagent consumption, CRL expects more shots on goal to support preclinical demand, and DHR is seeing early lab-automation adoption. SDGR says pharma AI budgets are increasingly incremental, with BMS an early proof point. Morgan Stanley’s healthcare specialist Dan Bone also highlighted Novo Nordisk’s use of Claude Science for drug-discovery challenges, GenScript’s completion of Lilly’s TuneLab validation loop for wet-lab services, and $290mn of financing for Anew Labs, which spun out of ByteDance’s internal drug-discovery team in June. The rally in names such as TWST shows investors are taking notice. For us, the demand case is that more AI-generated candidates can support repeated rounds of modeling, screening and physical validation, expanding compute use alongside laboratory spending. It is early to size that compute opportunity, but the evidence of incremental budgets and reagent consumption makes drug discovery a credible additional source of AI demand. Physical delivery remains the harder constraint across the infrastructure names we cover. CIOE orders and production schedules extend into 2027, but 3nm DSPs, lasers, and PCBs determine which optics vendors can ship. On power, our follow-up channel work supports 2.4–3.0MW of turbine nameplate per MW of IT for the off-grid designs we examined; that ratio doesn’t apply to the entire turbine market. Oracle’s results reinforce the value of earlier energization for Bloom, with permitting, manufacturing, and service capacity still the key checks. This Week’s Reports AI labs keep training despite the pacing debate. Our interviews point to longer evaluation and release timelines with limited near-term disruption to training investment or enterprise inference demand. Optics: orders extend into 2027, and access to supply determines who delivers. Our conference and CIOE notes track higher laser pricing, tight 3nm DSP capacity and the NPO/CPO ramp, with leading vendors best placed to turn strong demand into shipments. AIDC: nameplate capacity needs to be translated into dependable IT power. We answer six investor questions with new channel checks and a rebuilt off-grid sizing framework, separating redundancy, site derating and project readiness from headline turbine supply. Cybersecurity: AI safety concerns strengthen the case for platform and identity security. Our note maps the gaps exposed by agent incidents to runtime monitoring, non-human identity governance, isolation, vulnerability management and tamper-resistant logs. Premium Report Snapshot A portion of our research is reserved for Premium subscribers and is not distributed via Substack. Below is a snapshot of what Premium subscribers received this week beyond the Substack feed. Research | CRM: Dreamforce Clarifies Claudeforce Monetization as Salesforce Cedes the UI Deep | PLTR: Sovereign AI Expands the Opportunity; Partner Delivery Sets the Long-Term Ceiling Research & Roadshow | BE: Oracle Reinforces the Time-to-Power Thesis; Delivery Remains the Test Weekly Expert Interviews Summary A snapshot of the expert interviews we conducted during the past week is below; full transcripts and takeaways are available on the FUNDA platform. Meta: Muse Monetization and Advertising Share (META, GOOGL) Enterprise AI: Token Budgets and Model Routing (GOOGL) Microsoft: Internal AI Spend and Usage Mix (MSFT) RoboSoft: Workflow Automation and AI Spend Growth LendingClub: Production AI and Model Routing (LC, AMZN) Delta: Vertical Power Supply Bottlenecks and 800V Architecture (FLEX, GOOGL, MPWR, META) Vicor: Vertical Power Economics at Very High Current (VICR, NVDA) Detailed Report

$BTDR Q2 2026 Financial & Operational Highlights 📊 🔹Total revenue $228.8M (+47% Y/Y); Adjusted EBITDA $31.1M (+576% Y/Y) 🔹Self-mining #hashrate# 73 EH/s (+342% Y/Y) across 243,000 #miningrigs# (+113% Y/Y); 2,694 $BTC mined (+377% Y/Y). 🔹3 GW global power portfolio for #AIDC# and #BitcoinMining#; Executed a $4.7B, 16-year #AI# colocation lease in Tydal, Norway. #Bitdeer# #AIInfrastructure# #datacenter# #Investors#

Welcome to the era of the AI Factory. The new gold standards? 𝗖𝗼𝘀𝘁 𝗽𝗲𝗿 𝗧𝗼𝗸𝗲𝗻 and 𝗧𝗼𝗸𝗲𝗻𝘀 𝗽𝗲𝗿 𝗪𝗮𝘁𝘁. 💫 Our core thesis at the @SGTechSocial 𝗔𝗜𝗗𝗖 𝗪𝗼𝗿𝗸𝘀𝗵𝗼𝗽 2026: 💡 𝗘𝘃𝗲𝗿𝘆 𝗪𝗮𝘁𝘁 𝗠𝘂𝘀𝘁 𝗘𝗮𝗿𝗻 𝗜𝘁𝘀 𝗧𝗼𝗸𝗲𝗻: A watt lost to an idle queue or mid-job restart is stranded capital. Smart 𝙤𝙧𝙘𝙝𝙚𝙨𝙩𝙧𝙖𝙩𝙞𝙤𝙣 and 𝙥𝙧𝙤𝙖𝙘𝙩𝙞𝙫𝙚 𝙥𝙤𝙤𝙡𝙞𝙣𝙜 turn raw power into relentless AI throughput. ⚙️ 𝗦𝗵𝗮𝘁𝘁𝗲𝗿 𝗧𝗵𝗲 𝗦𝗶𝗹𝗼𝘀: Tuning facility PUE and software in isolation kills efficiency. 𝙄𝙣𝙛𝙧𝙖𝙨𝙩𝙧𝙪𝙘𝙩𝙪𝙧𝙚, 𝙥𝙤𝙬𝙚𝙧, 𝙘𝙤𝙤𝙡𝙞𝙣𝙜, and 𝙨𝙚𝙧𝙫𝙞𝙣𝙜 must be co-optimized as a single, unified engine. At @Bitdeer_AI, we own the full stack, engineering true AI workload economics from the grid all the way to the generated token. 🌐💰 Massive thanks to @SGTechSocial for bringing the ecosystem together and sparking such an insightful conversation! 👏 @Dell @nvidia @NVIDIAAP Bridge Data Centers

Latest CXMT update: Hefei & Beijing fabs are fully booked & preparing to add capacity thru 2028 (could increase to 600k wpm by 2028). Hefei-3, Beijing-2 + Shanghai? CXMT talks about G5 platform already matching industry leading mass produced nodes. LPDDR6 product hitting 12800 Mbps & lowering power consumption by 20% vs LPDDDR5X. Achieved this through SAQP. Company achieved 4F2 & other critical advancement in architecture. Again, this has hue application across mobile devices, edge compute, AIDC & smart cars.

Deep| $FTAI : Aviation Aftermarket Meets AI Power We initiate coverage of FTAI, an independent aviation aftermarket platform focused on the CFM56-5B/-7B and V2500 engine families. It is expanding into power generation by converting CFM56 engines into aeroderivative turbines. FTAI is the second BTM solution provider we have covered, after Bloom Energy. We remain bullish on off-grid power providers. As estimated in our AIDC Deep Dive, North America could face a ~15GW power shortfall in 2027. Securing grid power could take ~5 years, while traditional gas turbine OEMs such as GEV are booked out to 2032 with cash commitments. We are therefore looking for alternative BTM providers with reliable technology and confirmed orders. FTAI trades at ~10.5x forward EV/EBITDA and has yet to receive the re-rating seen at other BTM providers, despite the $1.465b Power order announced in late July. We see two reasons. Its traditional Leasing and MRE businesses face pressure on margins and industry demand. Its Power business has yet to deliver Mod-1 units to customers, making future earnings harder to assess. Bears still view Mod-1 as a prototype rather than a mature commercial product. In short, we believe that margin compression in its MRE business does not prevent it from maintaining earnings growth, supported by expanding market share from ~15% to ~26% based on our proprietary supply-demand industry model; and Power could deliver ~10 Mod-1 products in 26Q4 vs LSD consensus; ~80 in 2027 vs ~70 consensus and ~100 company maximum target. Management were guiding $450-750mn Adj. EBITDA in Power, suggesting a range of ~60 to 100 Mod-1 deliveries as guidance in 2027. We see the first batch of Mod-1 delivery in Q4 as the next rerating catalyst, and do not think the execution bar for Power is that high in the near term. Successful delivery and acceptance from customers should be enough for the street to catch up as it clears ambiguity at current valuation. Our reverse SOTP suggests that the market is paying nothing for Power, and we estimate it should be worth $82/share in our base case of 80 Mod-1 delivery in 2027. Detailed Report