Self-Sovereign GraphQL in Every Browser
Arweave holds the data and the index; PermawebOS gives every user a node that can answer and prove its own queries.
The third principle of Arweave is “Guarantee the right to listen”. In cyberspace, you can only hear if you can actually discover the data. On the permaweb, that’s made possible with GraphQL.
GraphQL provides a critical link in the composability architecture of the permaweb: allowing all apps to build on top of the same, shared content lake, joined by a single global index. Arweave transactions are posted with tags, discoverable by wallet address, or the block they were mined into, but GraphQL is the layer that lets users and applications see all data matching these queries. Without it, there’d be no way to find data matching criteria, or build data protocol-based apps.
It’s one of the permaweb’s core utilities, but until now it has been confined to the realm of enterprise-grade hardware. Services like that are usually incredibly difficult to decentralize because the hardware requirements are high and the incentives are low. The permaweb’s GraphQL services so far have depended on building and maintaining gargantuan off-chain indexes of more than 76 billion rows: scanning the historical chain, keeping it current and serving it quickly. In practice, this has meant that permaweb apps inherit the availability and policy of a tiny number (often two, sometimes – like today – even just one) of hosted indexers which had no incentive to adopt a decentralized model.
Offset queries (queries that seek, intersect and page by weave position) will change everything about how Arweave’s query layer is served. HyperBEAM's offset-query path makes the index compact enough to publish on Arweave, orders it by weave offset, and lets any node or client query the relevant pages directly.
(txid)
This is not another centralized GraphQL service, and it’s not just a way to make GraphQL more available to node operators. It is a method that makes GraphQL execution so lightweight that it can be run directly on users’ browsers, with Arweave nodes simply serving them data chunks.
Hyperoptimized GraphQL with Offsets
All pieces of data in Arweave already have unique positions in the weave – every byte is either ‘before’ or ‘after’ every other byte. We call these byte positions in the network offsets. In March, we showed how any transaction on the weave can be referenced by its offset as a name -- short, deterministic values like 101t.arweave.net, derived only from the data’s onweave properties.
That same offset property gives us more than a way to retrieve bytes. It also can power queries because it gives us a common ordering that can be reused across every possible match in an index.
The new match index stores rows using three extremely compact values:
a hash of the field name being matched;
a hash of the value that is present;
the weave offset of the item carrying that predicate.
Each potential match is compressed into an average of just ~9.5 bytes per row, each stored in an onweave ArLMDB database. By utilizing Arweave chunks as batches of LMDB pages, ArLMDB allows us to traverse the database to find any specific node with only a few individual Arweave node requests. By organizing rows into the compressed components 1-3 above, a query with two or three factors to match can walk those ordered sets together, advancing whichever cursor is behind until the offsets meet – a ‘leapfrog’ version of the same flow as a single lookup. Critically, finding the intersection is part of finding the results for each match criteria -- not a second step.
The same ordering solves pagination -- page fifty can seek to its starting offset instead of replaying pages one through forty-nine. Offset lookups give results a stable order without adding another ordering database.
AO Compute; Arweave the Shared Hard Drive
LMDB is normally a local database file. HyperBEAM's new arlmdb store reads that database from Arweave instead.
Try decentralized GraphQL from your browser
This is already proven at production scale with item lookup. A 622 GiB transaction contains the locations of over 70 billion rows. HyperBEAM reads the database where it sits. A cold lookup traverses it with three Arweave chunk requests; once the shared branches are cached, another lookup needs just one. The ArLMDB implementation is merged into HyperBEAM and used for ID lookups from Arweave.
With an immutable index on Arweave, anyone can read it without trusting the publisher to keep a query endpoint online. Like the Arweave schedulers powering Bazar, this is another example of AO employing Arweave as the source of truth, and using it to power the permaweb.
Instead of every query operator repeating the historical sweep and building the same large database, nodes serve chunks while the client traverses the index locally. The node's job is reduced to serving bytes quickly. It does not decide which results exist, execute the filter or ask the application to trust its view of the weave. The live tip still needs rolling indexes, but the expensive historical work no longer has to be repeated by every participant.
The client does not even need the whole database (depending on optimization, we’ve seen database sizes anywhere between 1 and 60 terabytes). The production offset index already demonstrates the access pattern: in the live chunkar browser demo, the second arbitrary lookup needs only around half a megabyte of new index data to traverse the full offset index. The match index works the same way. It traverses the pages needed for the requested predicates, intersects the ordered rows, reads the candidate items and checks that they actually carry the fields requested by the query. This is lightweight enough to make it so that every user can be their own personal no-dependency GraphQL service provider, with provable data, from the browser.
As well as the browser playground, today you can use the arlmdb.js library to integrate Arweave-stored database lookups into UIs.
From Centralized Node to Self-Sovereign Service
Today an application sends a GraphQL request to a server that already holds an index. With a published offset index, the application can instead hold a locator and a cache.
A HyperBEAM node can do that, but one way we imagine most users will access the query layer is through the browser: a user's application fetches Arweave chunks, keeps the hot index pages locally and performs the query for itself. This can be baked into the PermawebOS browser extension along with the local AO node the extension already spawns. This shift brings more and more AO services that were previously hosted (on exclusive TEE hardware) into a local-first environment. The stack is becoming so lightweight it’s able to be run cheaply, per-user, as background services in the browsers, phones and laptops everyone already has.
Previous designs for a decentralized GraphQL layer were unable to answer the question of trust without TEEs. How can you be sure that the response you get back from a GraphQL server has arrived complete and uncensored? While PermawebOS node architectures like LapEE and AndEE solve the trust question in theory, in practice the job of indexing the entire blockweave is too big for small workers.
Offset queries over onweave LMDB data -- made lightweight enough to traverse and prove by any browser -- change the equation entirely.
The browser never asks a server to decide the answer. It asks nodes for the exact index chunks it needs and walks the authenticated LMDB pages itself, intersecting the offset-ordered sets locally.
The new schema provides chunks and Merkle paths for each page accessed; the recipient can repeat the exact same work and see that they get the same complete set, with no missing results. The hashpath signs the request + response pair, and the validator can trivially repeat the work, whether on a node or in a browser. The resulting item is then bound back to its ANS-104 ID. A node can withhold bytes and make itself unavailable, but it cannot alter a row, skip a qualifying result or invent one without breaking the proof.
The Personal Permaweb Stack
Decentralizing GraphQL does not necessarily require a decentralized fleet of GraphQL servers. The permaweb is unique in that it combines a decentralized permanent storage layer with everyday web semantics. HTTP, lightweight proofs, and browser-based nodes handle the workload when the logic is optimized enough to sidestep expensive hardware.
The network holds the whole index. Each user keeps only the path to their answer.
With PermawebOS putting an AO node in every browser and LapEE turning abundant consumer hardware into secure bundlers, schedulers and tunnels, local GraphQL pushes the permaweb towards a cyberspace everyone can own.
Read this on the Permaweb:
https://ao.arweave.net/#/blog/self-sovereign-graphql-in-every-browser
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How Hedera Guardian Revolutionizes Environmental Asset Management
Recap, a look back at an earlier Hedera session. Environmental asset management is evolving beyond the limitations of traditional paperwork and bureaucratic hurdles. With the Hedera Guardian, you're equipped to integrate decentralized identities, verifiable credentials, and advanced policy workflow engines to streamline the creation and trade of digital environmental assets. Interested in sustainability tech or building with Hedera? This piece offers valuable insights to shape impactful applications in today's eco-conscious landscape. 🔗 Key Links 📺 Watch the full livestream → Delivering Trust in Environmental Assets and Outcomes with Hedera Guardian (https://www.youtube.com/watch?v=TUzQ2CF-I8o) 📄 Explore the Hedera Guardian docs → Hedera Documentation (https://docs.hedera.com) 🛠� Dive into Hedera Token Service → HTS Docs (https://docs.hedera.com) 📌 TL;DR Hedera Guardian enhances environmental asset digitization effortlessly. Version 3.5 supports decentralized identities and credentials. Demonstrated modular architecture offers flexibility. Builders can use Guardian infrastructure for community solutions. A 39% insurance premium reduction was achieved, showcasing real-world benefits. Unpacking the Hedera Guardian’s Key Innovations A Dive into the Modular Architecture The Hedera Guardian employs a flexible, modular architecture, simplifying user experience in digitizing complex environmental asset methodologies. It enhances security and transparency by integrating with decentralized identities and verifiable credentials. This design allows you to tailor your technology stack for specific environmental requirements—be it carbon credits or biodiversity tracking. The APIs within this architecture facilitate smooth data handling, helping you query data tied to issued tokens, assess user permissions, and manage asset statuses effectively. This level of customization opens doors to build applications that uniquely match demands. Key takeaway: The Guardian's modular architecture offers the flexibility and security you're looking for in managing diverse environmental assets. Policy Workflow Engine Excellence Perhaps the most notable feature is the policy configurator—a low-code environment that allows creators like you to define regulatory compliance and construct detailed workflows for managing environmental assets. This system promotes efficiency by letting you focus on optimizing solutions rather than getting tangled in coding complexities. Daniel showcased its utility in a captivating live demo, illustrating real-time data management and user interaction handling with drag-and-drop simplicity for scenarios like carbon offsets. Such functionalities make Guardian a powerhouse for streamlining complex environmental asset management. Key takeaway: The low-code workflow engine simplifies complex environmental asset management, keeping pace with emerging regulatory demands. Real-World Performance Metrics The Guardian's impact isn't just on paper. Featured during a livestream, the Tahoe Donner community realized a 39% lower insurance premium and an 89% lower deductible through smart forest management and the Guardian's data insights. These figures highlight the economic and ecological advantages the platform offers. By tapping into precise data analytics and risk management capabilities, you can predict and mitigate environmental risks like wildfires, expanding Guardian’s utility beyond asset management to a holistic environmental risk analysis tool. Key takeaway: The Guardian’s effectiveness in cutting insurance costs through informed environmental risk management marks its tangible value.
Leveraging Hedera Guardian in Practical Applications Build Next-gen Environmental Applications The Guardian provides practical avenues to construct industry-disrupting solutions. It enables you to craft applications focusing on the digitization and tokenization of environmental assets, like carbon credits or water rights. Supported by the Hedera ecosystem, these applications can meet the demands of eco-friendly consumers and industries aiming for sustainability. By maintaining transparent and verifiable tracking of asset provenance and movement, your applications will help industries transform environmental impact into tradable assets. Develop applications for digitizing environmental credits. Create solutions for managing ecosystem services. Use decentralized identity verification for secure trades. Unlocking Builder Opportunities Given the booming sustainability market, you're in a prime position to redefine environmental finance and management. With the Guardian's infrastructure, complex processes become more approachable, attracting eco-conscious investors and users alike. Here’s what you can explore: Design systems for biodiversity credits. Automate compliance for regulatory standards. Simplify distributed ledger technology solutions for environmental records. Key takeaway: The Guardian’s robust infrastructure presents a playground for innovation in the environmental sector, offering robust opportunities for builders. How It Works Under the Hood API Calls and Data Flow Explained The Guardian's architecture is centered around clear API endpoints, offering efficient interaction capabilities. Important API functionalities provide access to user permissions, asset issuance, and policy definitions, ensuring effective management and secure operations. It’s built to handle high transaction volumes, common in asset trading, assuring scalability. Its modularity allows dynamic process adjustments, aligning with your application's unique requirements. Design Patterns and Technical Decisions Integrating decentralized identities fortifies security while ensuring data integrity and privacy compliance, essential for building trust in environmental asset exchanges. Through verifiable credentials, you lay the groundwork for enhanced stakeholder confidence and standardized environmental reporting. The Guardian’s policy configurations use a microservice architecture. This supports independent scaling and integration of specific modules without overall disruption, providing a resilient system for asset management. Key takeaway: The Guardian’s secure, scalable design patterns build trust, enabling flexible environmental asset management solutions.
What You Can Build Now Harnessing the Hedera Guardian unlocks a spectrum of possibilities to innovate sustainable solutions. Here’s how you can kickstart: Identify a Use Case: Focus on an environmental asset to digitize, whether it’s carbon offsets, biodiversity credits, or water usage rights. Use APIs: use the Guardian’s APIs to secure and manage transactions and data robustly. Integrate Decentralized Security: Strengthen trust and compliance using decentralized identities and verifiable credentials. Develop Policy Workflows: Use the low-code configurator to automate reporting, establish compliance, and adhere to regulations. Test and Scale: Ensure performance and scalability through rigorous testing before scaling to broader markets. Key takeaway: use the Guardian's resources to develop comprehensive, compliant environmental asset management solutions seamlessly. Resources To explore more about building with the Hedera Guardian, consider these resources: Hedera Documentation: Hedera Documentation (https://docs.hedera.com) Join the Conversation on Discord: Hedera Community (https://hedera.com/discord) Explore HTS: HTS Docs (https://docs.hedera.com) Are you already building with the Hedera Guardian? Share your project in the replies, the Hedera community is keen to spotlight novel solutions and breakthroughs! Understanding the Role of Hedera Consensus Service The Hedera Consensus Service (HCS) plays a pivotal role in ensuring transparency and trust in environmental asset management. By acting as a decentralized message layer, HCS allows you to reliably timestamp and order messages, which is crucial for maintaining the integrity of data associated with digital environmental assets. This service can be particularly beneficial for complex environmental projects that require verifiable data transmission and storage. How HCS Facilitates Data Integrity With HCS, every transaction related to environmental assets can be logged in a tamper-proof manner. This ensures that the data remains consistent and accurate over time, a feature that is indispensable for regulatory compliance and stakeholder trust. Builders can appreciate this feature because: It establishes a trusted timeline of events and transactions. It prevents data manipulation or unauthorized alterations. It supports interoperability with other services, enhancing system integration. Implementing HCS in Environmental Projects To effectively implement HCS in your environmental projects, consider the following steps: Define Your Data Needs: Identify what environmental data needs to be tracked and verified. Integrate with Existing Systems: use HCS to complement your current data management tools. Monitor Transactions: Regularly check the logs to ensure data integrity and accuracy. By following these steps, you can enhance the trustworthiness and efficiency of your digital environmental asset management processes. Leveraging Hedera Smart Contract Service for Environmental Solutions The Hedera Smart Contract Service (HSCS) provides a robust framework for creating and executing smart contracts tailored to environmental asset management. The HSCS supports the Ethereum Virtual Machine (EVM), which allows you to deploy contracts that automate complex workflows, ensuring transparency and reducing administrative overhead. Benefits of Using HSCS The use of smart contracts in environmental projects offers several advantages: Automation: Streamline processes such as asset creation, transfer, and verification. Cost Efficiency: Reduce manual intervention and associated costs. Scalability: Manage large volumes of transactions without compromising performance. By harnessing these benefits, builders can create more efficient and scalable solutions for environmental asset management. Creating Smart Contracts with HSCS To deploy effective smart contracts using HSCS, you can follow these guidelines: Define Clear Contract Terms: Ensure that the contract terms are precise and unambiguous to avoid disputes. Test Extensively: Conduct thorough testing in a controlled environment to identify and rectify potential issues. Monitor and Update: Regularly review and update the contracts to adapt to new requirements or regulations. Implementing smart contracts effectively can significantly enhance the functionality and reliability of your environmental management solutions.
Community Collaboration Through Hedera's Ecosystem The Hedera ecosystem thrives on community collaboration, offering builders a variety of opportunities to engage with partners and contribute to collective environmental goals. The Apex Hackathon is one such platform that brings together developers, experts, and organizations to innovate and create impactful solutions. Engaging with Ecosystem Partners During events like the Apex Hackathon, participants can collaborate with ecosystem partners like AWS, Neuron, and Hashgraph Online. These partnerships enable you to: Access a wealth of resources and expertise. Gain insights into best practices for environmental asset management. Build connections with other innovators in the field. Such collaborations can propel your projects forward, providing the support and knowledge needed to tackle complex environmental challenges. Building Community Solutions Hedera encourages the development of community-driven solutions that address local and global environmental issues. By participating in community initiatives, you can: Contribute to sustainable development goals. Innovate with a focus on real-world impact. Share knowledge and experiences with a broader audience. Engagement in community projects not only enhances your technical skills but also enriches your understanding of environmental sustainability. Real-World Applications and Case Studies The practical applications of Hedera's technology in environmental asset management are numerous. By examining real-world case studies, builders can gain valuable insights into how Hedera can be applied to achieve tangible outcomes. Case Study: Wildfire Mitigation One notable application of Hedera technology is in wildfire mitigation. By integrating real-time data streams with the Hedera platform, organizations can monitor and respond to wildfire threats more effectively. This approach offers several advantages: Timely Alerts: Automated alerts allow for quicker response times. Data-Driven Decisions: Access to accurate data supports informed decision-making. Resource Optimization: Efficiently allocate resources to areas of greatest need. Case Study: Reforestation Projects Another example is the use of Hedera in reforestation projects. By tracking the lifecycle of each tree planted, organizations can ensure the success and sustainability of their efforts. Key benefits include: Verification of Impact: Transparent data supports claims of environmental impact. Stakeholder Engagement: Demonstrates commitment to transparency and sustainability. Compliance and Reporting: Simplifies the process of meeting regulatory requirements. These case studies illustrate the potential of Hedera's technology to facilitate effective environmental management and enhance sustainability initiatives.
55·BLong
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meme9/7meme
Want to combine uAgents + @solana transactions? Build this 3-Agent flow.
PlayerAgent
→ Loads its Solana wallet
→ Sends an `escrowRequest`
→ Transfers SOL to escrow
ChallengerAgent
→ Does the same from a second wallet
EscrowAgent
→ Receives both requests
→ Pulls live BTC price data
→ Determines the winner
→ Transfers the payout
→ Messages both Agents with the result
All three register through http://Fetch.ai’s Almanac, communicate through typed uAgent messages and execute transactions on Solana Devnet.
The example uses three specialised Agents instead of stuffing wallet management, external data, decision logic and settlement into one process.
Run it on Devnet first:
`poetry run python escrow_agent.py`
Then start the Player and Challenger Agents. From there, extend the pattern into DeFi workflows, NFT auctions or other Agent-driven on-chain logic.
Build the Solana example today. Check @Fetch_ai_IL guide → https://innovationlab.fetch.ai/resources/docs/examples/on-chain-examples/solana-agents
0·-Neutral
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news9/7news
Want to combine uAgents + @solana transactions? Build this 3-Agent flow.
PlayerAgent
→ Loads its Solana wallet → Sends an `escrowRequest` → Transfers SOL to escrow
ChallengerAgent
→ Does the same from a second wallet
EscrowAgent
→ Receives both requests → Pulls live BTC price data → Determines the winner → Transfers the payout → Messages both Agents with the result
All three register through http://Fetch.ai’s Almanac, communicate through typed uAgent messages and execute transactions on Solana Devnet.
The example uses three specialised Agents instead of stuffing wallet management, external data, decision logic and settlement into one process.
Run it on Devnet first: `poetry run python escrow_agent.py`
Then start the Player and Challenger Agents. From there, extend the pattern into DeFi workflows, NFT auctions or other Agent-driven on-chain logic.
Build the Solana example today. Check @Fetch_ai_IL guide → https://innovationlab.fetch.ai/resources/docs/examples/on-chain-examples/solana-agents
35·CLong
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news9/7news
Eyes on the Market: Sustained Inflows
Oil led everything. Brent rose 9.27% to $96.54 as US-Iran strikes resumed. BTC added 2.28% to $79,808, ETH 1.62% to $2,490.60, the S&P 0.40% and the Nasdaq 100 0.73%. Waller signals dovish. Polymarket hike odds fell from 51% to 41% on Thursday's remarks. BTC wicked to $82,262 and closed the session up 5.67%. Payrolls reversed it two days later. 162K against 53K consensus took hike odds back to 49%. BTC fell 2.95% and ETH 2.69%. The move is not levered. Aggregate OI is $139.7B, up 3.5% and the highest since mid-January. Coin-denominated BTC OI fell from 762.2K to 669.6K since mid-August, even as BTC moved from $63K to $80K. ETFs took $1.2B, a third straight week above $1B, the first such run since July 2025. BTC drew $986.7M including $730.8M on September 3, the largest day since January 14. BTC ETFs AUM crossed $103.3B, 6.32% of supply. Oil Leads the Week BTC opened Monday at $78,031, hit a high of $82,262 on Thursday and closed Sunday at $79,808. Up 2.28% on the week. ETH gained 1.62% to $2,490.60. Total crypto market cap finished at $2.708T, slightly outperforming BTC as selected alts continue to rally.
Oil saw the largest move, rising 9.27% to $96.54 as the US and Iran conflict intensified during the week. The S&P 500 added 0.40% to 7,728.60 and the Nasdaq 100 gained 0.73% to 29,616. Gold slipped 0.60% to $4,470.50. Events of the Week US-Iran Strikes Resume US-Iran strikes resumed for the first time in roughly a month after the 60-day ceasefire lapsed in mid-August. US forces disabled two Iranian tankers and destroyed a third on September 2, following IRGC ballistic missile fire at a US carrier and destroyer. Iran struck Kuwait with missiles and drones on September 3, escalating to a US Gulf ally, and Israel warned it would cripple Iranian infrastructure. Brent went from $88.32 to $95.15 on Tuesday, then plateaued between $95 and $97 for the rest of the week. Waller Gives Disinflation a Chance Fed Governor Christopher Waller's prepared remarks went out on Thursday 8:30am ET. Inflation is still meaningfully above the 2% goal, he said, but the recent data finally show some signs of disinflation, and if that holds through the next two weeks he would back holding the funds rate at 3.50% to 3.75%. Treasury yields fell to session lows and hike odds on Polymarket dropped from about 51% to about 41%. BTC wicked to $82,262 before settling at $81,704, up 5.67%. Hot Payroll Print August payrolls came in at 162K against 53K consensus, three times the estimate, with unemployment at 4.1% in line. Strongest print since March and the first up-month in five after. Expectations of a hike reversed back up from 41% to 49%. BTC fell 2.95% and ETH 2.69%. Volatility, Positioning and Leverage BVIV is up 5.4%, from 38.9 last week to 41.02. The metric is up 14% from the low of 35.81 that it hit on August 7. Aggregate futures open interest is $139.7B against $135B last issue, up 3.5% and the highest since mid-January. 24-hour volume is $136.4B, up 31%. BTC open interest in coin-denominated terms is the lowest it’s been since March 25. It’s been steadily falling since mid-August from 762.2K BTC to 669.6K BTC as BTC has risen from $63K to $80K. A reflection of how spot driven the recent move has been. Coinglass's 24-hour long/short ratio is 49.04% / 50.96%. Annualized funding on Binance runs BTC near 4.7%, ETH 8.4%, SOL flat to slightly negative and HYPE 5.5%. ZEC funding is roughly -3.65% annualized and ZEC still gained 45% in the past week. The coins that lead are now moving on spot inflows. ETF Flows Continue BTC and ETH ETFs took $1.2B combined, a third consecutive week above $1B. The last stretch of this magnitude was July 2025. BTC: $986.7M. September 3's $730.8M is the largest single day since January 14 and the third largest of 2026, behind January 14 at $840.6M and January 13 at $753.8M. BTC ETF AUM crossed $103.3B, 6.32% of supply. Year to date cumulative flows now sit at -$0.90B, from -$4.74B three weeks ago. Three weeks have erased 81% of the year's outflows. ETH: $215.3M. Flows fell 74% week on week from $815.7M. ETH captured 22% of BTC's dollar flow against 88% the prior week. Cumulative net flows are $13.19B and August closed at $1.84B. This breaks the ETH outperformance pattern we have tracked since late July, and the spot data agrees: ETH gained 1.62% against BTC's 2.28%. First week in a while where ETH lagged on both flow and price.
Key Events for the Week Ahead Tuesday, September 8 US consumer credit (G.19), 3pm ET. Wednesday, September 9 US NFIB small business optimism for August. Thursday, September 10 US PPI for August, 8:30am ET. Europe: ECB rate decision, 8:15am ET. Friday, September 11 US CPI for August, 8:30am ET.
90·A+Long
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news9/7news
Eyes on the Market: Sustained Inflows
Oil led everything. Brent rose 9.27% to $96.54 as US-Iran strikes resumed. BTC added 2.28% to $79,808, ETH 1.62% to $2,490.60, the S&P 0.40% and the Nasdaq 100 0.73%.
Waller signals dovish. Polymarket hike odds fell from 51% to 41% on Thursday's remarks. BTC wicked to $82,262 and closed the session up 5.67%.
Payrolls reversed it two days later. 162K against 53K consensus took hike odds back to 49%. BTC fell 2.95% and ETH 2.69%.
The move is not levered. Aggregate OI is $139.7B, up 3.5% and the highest since mid-January. Coin-denominated BTC OI fell from 762.2K to 669.6K since mid-August, even as BTC moved from $63K to $80K.
ETFs took $1.2B, a third straight week above $1B, the first such run since July 2025. BTC drew $986.7M including $730.8M on September 3, the largest day since January 14. BTC ETFs AUM crossed $103.3B, 6.32% of supply.
Oil Leads the Week
BTC opened Monday at $78,031, hit a high of $82,262 on Thursday and closed Sunday at $79,808. Up 2.28% on the week. ETH gained 1.62% to $2,490.60. Total crypto market cap finished at $2.708T, slightly outperforming BTC as selected alts continue to rally.
Oil saw the largest move, rising 9.27% to $96.54 as the US and Iran conflict intensified during the week. The S&P 500 added 0.40% to 7,728.60 and the Nasdaq 100 gained 0.73% to 29,616. Gold slipped 0.60% to $4,470.50.
Events of the Week
US-Iran Strikes Resume
US-Iran strikes resumed for the first time in roughly a month after the 60-day ceasefire lapsed in mid-August. US forces disabled two Iranian tankers and destroyed a third on September 2, following IRGC ballistic missile fire at a US carrier and destroyer. Iran struck Kuwait with missiles and drones on September 3, escalating to a US Gulf ally, and Israel warned it would cripple Iranian infrastructure. Brent went from $88.32 to $95.15 on Tuesday, then plateaued between $95 and $97 for the rest of the week.
Waller Gives Disinflation a Chance
Fed Governor Christopher Waller's prepared remarks went out on Thursday 8:30am ET. Inflation is still meaningfully above the 2% goal, he said, but the recent data finally show some signs of disinflation, and if that holds through the next two weeks he would back holding the funds rate at 3.50% to 3.75%. Treasury yields fell to session lows and hike odds on Polymarket dropped from about 51% to about 41%. BTC wicked to $82,262 before settling at $81,704, up 5.67%.
Hot Payroll Print
August payrolls came in at 162K against 53K consensus, three times the estimate, with unemployment at 4.1% in line. Strongest print since March and the first up-month in five after. Expectations of a hike reversed back up from 41% to 49%. BTC fell 2.95% and ETH 2.69%.
Volatility, Positioning and Leverage
BVIV is up 5.4%, from 38.9 last week to 41.02. The metric is up 14% from the low of 35.81 that it hit on August 7.
Aggregate futures open interest is $139.7B against $135B last issue, up 3.5% and the highest since mid-January. 24-hour volume is $136.4B, up 31%. BTC open interest in coin-denominated terms is the lowest it’s been since March 25. It’s been steadily falling since mid-August from 762.2K BTC to 669.6K BTC as BTC has risen from $63K to $80K. A reflection of how spot driven the recent move has been.
Coinglass's 24-hour long/short ratio is 49.04% / 50.96%. Annualized funding on Binance runs BTC near 4.7%, ETH 8.4%, SOL flat to slightly negative and HYPE 5.5%. ZEC funding is roughly -3.65% annualized and ZEC still gained 45% in the past week. The coins that lead are now moving on spot inflows.
ETF Flows Continue
BTC and ETH ETFs took $1.2B combined, a third consecutive week above $1B. The last stretch of this magnitude was July 2025.
BTC: $986.7M. September 3's $730.8M is the largest single day since January 14 and the third largest of 2026, behind January 14 at $840.6M and January 13 at $753.8M. BTC ETF AUM crossed $103.3B, 6.32% of supply. Year to date cumulative flows now sit at -$0.90B, from -$4.74B three weeks ago. Three weeks have erased 81% of the year's outflows.
ETH: $215.3M. Flows fell 74% week on week from $815.7M. ETH captured 22% of BTC's dollar flow against 88% the prior week. Cumulative net flows are $13.19B and August closed at $1.84B. This breaks the ETH outperformance pattern we have tracked since late July, and the spot data agrees: ETH gained 1.62% against BTC's 2.28%. First week in a while where ETH lagged on both flow and price.
Key Events for the Week Ahead
Tuesday, September 8
US consumer credit (G.19), 3pm ET.
Wednesday, September 9
US NFIB small business optimism for August.
Thursday, September 10
US PPI for August, 8:30am ET.
Europe: ECB rate decision, 8:15am ET.
Friday, September 11
US CPI for August, 8:30am ET.
90·A+Long
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news9/7news
ZEROBASE WEEKLY 8.31–9.6
ZBT traded in a tight $0.080–$0.086 band this week, opening near $0.084 on August 31 and finishing around $0.085 by September 6. The token briefly dipped toward $0.080–$0.081 on September 2 before reclaiming the mid-$0.08s. Trading volumes stayed functional , generally in the $3–$10 million daily range, with liquidity remaining orderly and spreads contained.
The broader crypto market showed more range than the late-August squeeze. Total capitalization moved from roughly $2.59T–$2.63T at the start of the week to a Thursday peak near $2.82T as Bitcoin cleared $81,000, then settled back in the $2.67T–$2.79T area. That is a constructive but incomplete recovery from the mid-year trough near $2.3T.
Bitcoin opened the week near $78,550 on August 31, slipped to a weekly low around $76,250 on September 2, then ripped to a three-month high above $82,200 on September 3. It faded to the high-$79,000s after Friday’s jobs print and closed the week near $80,300–$80,350 — a net gain of about 2% from Monday’s open and roughly 5% from the weekly low. Ethereum moved in a narrower channel: from about $2,467 on August 31, down toward $2,356–$2,390 midweek, then back to $2,510–$2,516 by Sunday, a modest gain of around 2% on the week and about 6–7% from the low.
Derivatives confirmed the move was a squeeze, not a clean leverage rebuild. On September 3, 24-hour liquidations ran $400–$510 million, with shorts accounting for the bulk — roughly $345–$415 million of short liquidations that session, including about $162–$174 million in Bitcoin shorts. Open interest remained elevated near $54 billion on Bitcoin perps. Funding stayed near neutral to only mildly positive after the squeeze, suggesting traders were covering rather than aggressively adding new longs.
Macro and geopolitics were the week’s real drivers. The U.S.–Iran conflict, now in its seventh month, intensified again. Washington struck IRGC sites on the Iranian mainland early in the week, and both sides targeted vessels around the Strait of Hormuz. Hormuz traffic stayed depressed at roughly 10 commodity ships per day versus more than 130 pre-war. Oil responded immediately: WTI rose nearly 10% on the week to settle around $91.48 on Friday, while Brent gained about 7.6–7.8% to $96.28. Diesel hit a U.S. retail record near $5.85 a gallon. Energy inflation is no longer a one-day shock; it is a persistent input into the Fed’s reaction function.
Friday’s August employment report then flipped equity and rate markets. Nonfarm payrolls printed +162,000 versus a ~56,000 consensus, with prior months revised up by 55,000. Unemployment held at 4.1%. The 10-year yield finished near 4.78% and the 2-year near 4.37%. Markets immediately repriced the odds of a September rate hike higher. U.S. equities finished mixed for the week: the S&P 500 eked out a 0.1% gain to 7,718.60, the Nasdaq Composite rose 0.4% to 26,506.99, and the Dow fell 0.3% to 53,414.25. Friday itself was risk-off — S&P −0.38%, Dow −0.51%, Nasdaq Composite −0.29% — after the jobs surprise. Chip names limited the Nasdaq damage; credit-sensitive and consumer names did not.
Institutional crypto flows remained the structural offset. U.S. spot Bitcoin ETFs took in about $987 million net for the week ending September 4/5, extending a three-week streak to roughly $3.8 billion. The path was uneven: +$217 million on August 31, −$236.5 million on September 1, then +$101 million, a standout +$731 million on September 3 (largest single day since mid-January), and +$175 million on September 4. BlackRock’s IBIT again absorbed the majority. Ethereum ETFs added about $215 million, down ~74% from the prior week’s $816 million. Combined BTC+ETH ETF inflows were still ~$1.2 billion. Bitcoin ETF AUM sat near $101 billion. Year-to-date BTC ETF flows remain slightly negative, so this is repair, not a new cycle high in sponsorship.
Crypto-native news reinforced a rotation beneath Bitcoin. Zcash led the tape, breaking $1,000 and later trading above $1,150–$1,200 with a weekly gain approaching 40%, helped by ETF interest and a short squeeze. Uniswap jumped more than 50% on the week as DeFi breadth improved. Arbitrum ripped on Robinhood Chain activity.
Elsewhere: Liquid Network paused after a purported white-hat withdrawal of $320 million in bitcoin; Trezor said a ShipMonk breach affected tens of thousands more customers; the SEC floated a “Regulation Crypto Assets” framework with offering exemptions; and OpenReserve received preliminary OCC approval for a national bank charter. Privacy coins and infrastructure names outperformed beta.
Crypto Fear & Greed spent the week in greed, not fear. The index rose from 62 on August 31 to 69, 63, 65, then 74 on September 4, and held 73–74 into the weekend. Seven-day average was about 68; 30-day average about 54. Sentiment has flipped from the August mid-20s/30s readings, which is consistent with the price rebound but leaves less cushion if oil or the Fed surprise again.
On-chain data was more mixed than the ETF tape. Long-term holders are no longer in the aggressive distribution regime of earlier 2026, but they are not uniformly accumulating either. Whale flow flipped toward net exchange deposits later in the week (roughly +1,900 to +3,900 BTC on some sessions), and tracked large holders rotated size rather than simply stacking.
Dormant supply stirred: 2013-era wallets moved hundreds of BTC in early September, including a coordinated 200 BTC burst on September 5, while 2011 coins worth more than $7 million also woke up. OG five-year+ UTXO spend, on a 90-day average, rose toward ~1,500 BTC — higher than May, but still well below prior capitulation spikes. The read-through is consolidation and wallet hygiene more than a coordinated dump, yet it is not the one-way accumulation signal of a clean breakout.
In summary, August 31–September 6 was a squeeze week inside a still-contested macro regime. Spot Bitcoin and Ethereum recovered from the $76k / $2,360 area, ETF demand stayed real, and alt breadth improved via ZEC, UNI, and privacy/infrastructure names. Against that, Hormuz risk pushed oil to three-month highs, Friday’s 162k jobs print revived hike odds, U.S. equities stalled, and on-chain whales stopped being net buyers into strength.
The market is consolidating in the $80,000 Bitcoin / $2,500 Ether zone with institutional bids underneath and energy-geopolitical risk overhead. Next week’s CPI and the September FOMC path matter more than last week’s liquidations.
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⚠️ Exploit breakdown:
Sept 6: @Liquid_BTC got hit through an Elements consensus / asset-validation bug. Attacker minted ~4,000 unbacked L-BTC, then used SideSwap’s normal peg-out flow to cash out 3,996.01834922 BTC from the Liquid Federation reserve.
They called it whitehat and said funds come back after every node is patched. Still sitting. No return.
📌 IOCs
Attacker:
https://mempool.space/address/bc1qgslsydz56d0ed6827hdemfmk5w2f6ldyc6wt7p
Collection wallet:
https://mempool.space/address/bc1ql4mfu6aundtkksxklfajs2h3t9nzcd6gyqjlte
Hit reserve:
https://mempool.space/address/bc1qdlld6antmv4xug242ed83q7k4rqw50cwfns38szx4qu2f4jwaxxsuhwxxr
🔍 How it played out
1. Phantom L-BTC
Liquid block 4,050,336 (2026-09-06 21:53:10 CST) was accepted by Federation / Blockstream nodes. http://mempool.space’s independent Liquid node rejected it and stalled on the prior block. Clean consensus split.
Suspect mint:
https://blockstream.info/liquid/tx/c652a1047ff549698b09242a66e20f6e9a044d5c972419342fa552b0856ba674
2. Peg-out via SideSwap
3,996.01834922 BTC paid to bc1qgsls...c6wt7p
https://blockstream.info/liquid/tx/ce4caece413cd9d444ce7ed9f54e5b328b3da5e4af301aff59a3571f76e988f2
Blockstream later said the L-BTC came from an Elements bug. SideSwap PAK + infra were not compromised.
https://x.com/side_swap/status/2096709838310928674
3. Federation pays on Bitcoin L1
https://mempool.space/tx/8db751a650ae2f12006b7e8c69a75e4df360e8afd6b9e05ae0b9fa6458a7b140
4. Funds swept
https://mempool.space/tx/85d2ca15bea33a592e73ed40c6a5da887feecf1e77f58ec7f580e00841645043
5. On-chain note
OP_RETURN: “we are whitehats. contact us on chain.”
Also told Liquid to patch first, then they’d return funds — and even sent the project fix details. Comedy/taunt meter is maxed. Whitehat claim is shaky. Reads more like buying time.
https://mempool.space/tx/83825b2135dd0abac12c9dfe17f29ab81b3427e1ae864947b0bebce5e47c3c4b
🧠 Impact
▪️ Hit: Liquid Network / Federation BTC reserve
▪️ Loss: 3,996.01834922 BTC (~$320M at the time)
▪️ Reserve left: ~197.4719 BTC. ~95% of the stack walked
▪️ Bitcoin L1: not exploited. Mainnet just executed a Federation-signed payout
▪️ SideSwap: used as the peg-out rail. Official word is PAK + systems were not breached
▪️ Other Liquid assets: USDT, DePix, RWAs were not weirdly minted, but the pause still froze transfers + liquidity
▪️ Recovery: principal still sits on the collection address. No CEX, no mixer, no bridge. Better recovery odds than a washed drain — until it’s actually returned, treat it as unrealized loss
▪️ Attacker label: self-claimed whitehat, unknown actor. Parking nine figures and then asking to talk is not standard responsible disclosure.
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How does this turn into a PvE cycle?
To be clear, I don't actually think we're really there. I don't believe retail is fully here like they were back in 2021/2024 and I think that it's still mostly the same hot ball of money moving around. There are signs that some normies are coming onboard w/ social apps and some of these onchain ceilings, but I don't think we've really seen insane mania yet. It feels a bit like the early stages of a bull market....like October 2020 or November 2020 or something around there.
I actually don't think we'll see insane mania like we did back in 2021 or 17 (I hope I'm wrong there). A cycle equal to 2024 would be great to see but I do think that onchain won't be as insane as we saw back then (again, I hope I'm wrong).
With that said, what would actually change this? What would turn us to actual PvE (player vs. environment), where normies are coming in huge and buying our bags? (I think any combination of the below can happen fwiw)
IMO:
1) BTC cracks ATH with strength and is on a moon mission to 200k+. This one is obvious and doesn't need much explanation. Maybe this cycle is different where we don't actually need bitcoin to do huge numbers since retail flow has mostly always been about altcoins and the market is just structurally different as time has gone by. But even still, this is the easiest answer and it's been the solution for every past bull market. BTC bottoms and extra new money flows in.
2) AI x Crypto is real. That money flows into crypto from a narrative perspective and we get a lot of flow from wall street and AI investors. We saw glimpses of this in 2024, where the AI agent wave with GOAT and ai16z brought about a lot of tech junkies who were experimenting onchain. Ofc all of this was larp but it brought in real outside money. AI has been the story for all of 2025/26 in stocks and those have had insane moves - if even a fraction of that $ comes over, we will be partying.
3) Robinhood is real and we actually get tons of retail flow. This is the one that makes the most sense to me personally and the relationship is clear to me. There are dozens of posts written about this already but the stock x meme combo is really intriguing and I wouldn't be surprised to see the next wave of interesting DeFi tokens spawn from this chain / cycle. We haven't had true innovation in that area since 2020 IMO, let's see if that changes.
4) Something new gets built that brings about huge retail investors. In the past, this was sold as 'cutting edge tech' and being on the frontier. These days, I think that most of the tech happens onchain (investable tech that is) and everything else (perps, privacy, prediction markets, stables) are bigger infrastructure projects that will mostly take over the past ones (big L1s, AAVE forks, etc). I actually don't have the answer for this one because I don't see it yet but there probably will be something. In 2024 it was more pumpfun and all of the onchain madness, in 2021 we had a variety of things (economic stimulus, gaming, new L1s, etc). Innovation has largely diminished with each cycle IMO (which makes sense because anything new or exciting was thought of in previous cycles). But there's probably going to be something.
If we do get PvE, where does that $ flow? IMO onchain. Nobody is really interested in buying these huge fdv infrastructure tech projects right now. Maybe that changes and maybe we see an insane bid for Monad or something along those lines...but I don't personally see it. People are in crypto to get rich and I think everyone knows the gig at this point and they aren't interested in buying this high fdv dogshit anymore. Unless something materially changes with these token structures, I'm mega bearish on all of those.
Should be a fun cycle regardless. Still think we're in the early stages
55·BLong
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meme9/7meme
Meritz Securities (Korean sell side): GPT-6 Astra launch and implications for the memory stock rebound
On September 3, OpenAI unveiled GPT-6 Astra. As interpretations of this model became a hot topic, semiconductor stocks rebounded on September 4 even as the broader US market fell on rising rates following a jobs surprise, with the DRAM ETF up 6.6% versus the prior day.
Astra's implication is unlikely to be simply whether AGI has been achieved. What drew the most attention was the score of 99.9% on ARC-AGI-3, a benchmark used to judge AGI, a huge improvement over the previous model (Sol at 7.8%). This benchmark is not a knowledge test; it evaluates a model's ability to learn on its own in an abstract environment it has never seen before, and this is where the improvement over the previous model was large. General intelligence, as measured by AAII or Humanity's Last Exam, did not improve much.
The differentiated strength improved in Astra is "the ability to acquire skills that humans learn in an unfamiliar environment as efficiently as a human does." Where AI until now found the answer by pressing this and that 100 times, Astra has started to behave more like a human: observing the phenomenon, inferring the rules, and executing right away.
The key point is "an expanded scope for replacing human intelligence and human work." If existing AI was an AI that told you what to do, Astra is closer to an AI that, given only a goal, uses the computer directly and produces the result all the way to the end. In other words, an easy to use OpenAI model has begun to handle on its own part of the agent orchestration layer that had been the domain of less accessible tools such as OpenClaw. For users, the barrier to entry for AI agents has been lowered, meaning more work can be handed over.
Expansion of AI workloads
Astra naturally also comes with efficiency gains that lower the token cost per task versus the previous model. This is a trend across the AI industry as a whole, and if AI workloads were fixed, demand for AI data centers would have to plunge.
The reason Jevons paradox continues to operate even after token price declines became a trend following the rise of Chinese models is that AI technological progress also expands the workload. What Astra's technological progress means is that where humans used to hand five minute, ten minute, and twenty minute tasks to AI, as AI performance improves and token prices get cheaper there is more to hand over, such as one hour and 24 hour tasks.
Just as news flow about rising GPU rental prices has spread since Astra's arrival, it must be understood that falling AI token prices do not necessarily shrink or slow the AI hardware TAM. Rather, one should recognize that the emergence of a model like Astra can create another inflection point for the AI industry and structurally grow AI demand.
Our understanding is that since early July, as the pace of GPU rental price increases slowed and token prices fell, a long IGV (software) / short SOX (semiconductors) pair trade has persisted in the US. This is because falling token prices were interpreted as positive for software, where tokens are a cost, but negative for infrastructure.
If progress in models like Astra structurally spreads AI workloads and GPU rental prices begin to respond again, the perception that falling token prices are bad news for AI infrastructure companies could weaken (on 9/4 the DRAM ETF rebounded while IGV fell).
As we have argued consistently, the issues accumulating in the AI industry since June (the proliferation of open models, this GPT-6 Astra release, and so on) are, in our interpretation, positive catalysts that generate new demand for AI infrastructure and hardware that did not exist before. We think that in a phase where rates are rising overall and liquidity is becoming scarce, these accumulated positives are not being reflected.
The stock market in September is still uncomfortable with high rates, and within the Korean market there remain hurdles to get through, including digesting a round of earnings estimate cuts driven by the sharp won appreciation before the 3Q26 preview season. There is still discomfort standing in the way of the accumulated positives being reflected in a sustained trend. Overall, we continue to view the market conservatively.
Even so, as emphasized in our September strategy, we believe one should not substantially empty out positions in core AI infrastructure stocks centered on memory. Positive catalysts not reflected in share prices are accumulating. While our baseline is conservative through mid October, one should keep the upside risk open that the trend, led by AI and semiconductor leaders, could turn at any time, even before October.
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OpenAI became the underdog and delivered with Astra. Underdog mode is a flow state.
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Enhance Your DeFi Strategy with Bonzo Finance's Innovations on Hedera
Recap, a look back at an earlier Hedera session. If you're navigating the exciting world of Decentralized Finance (DeFi), you've certainly come across the essential role of managing liquidity. With current market conditions testing many protocols, Bonzo Finance's recent session offered eye-opening insights into how their innovative solutions are evolving liquidity management. Bonzo Vaults stand as a beacon, surpassing $1 million in Total Value Locked (TVL), showing remarkable resilience and growth. Here's everything you need to know to stay ahead and use these tools effectively. 🔗 Key Links 📺 Watch the full livestream → Building AI Agents on Bonzo Finance (https://www.youtube.com/watch?v=P5Iw0XCr1UY) 📄 Explore Hedera Docs → Hedera Documentation (https://docs.hedera.com) 🛠� Engage with the Community → Hedera Discord (https://hedera.com/discord) 📌 TL;DR Bonzo Finance strengthened Hedera's DeFi suite with a $60M TVL in favorable markets. Bonzo Vaults exceeded $1M in TVL; the beta test is ongoing. Yield on USD-HBAR vault shows potential with up to 92.2% 30-day APY. LayerZero Stargate integration for cross-chain liquidity is forthcoming. Developers are equipped to optimize market strategies using these advancements. Bonzo Finance on Hedera: Unveiling Opportunities A New Era for DeFi Protocols Bonzo Finance's session was a testament to its continual growth in the DeFi landscape on the Hedera network, underscoring the pivotal role their solutions play in amplifying liquidity. At the heart, Bonzo Lend, their flagship lending protocol, soared with over $60 million in TVL during favorable market conditions, maintaining a solid $19 million today. Even amid market volatility, Bonzo Vaults' performance is impressive, consistently topping $1 million in TVL. This achievement reflects a strong community backing and an endorsement of the platform's capacity for optimizing returns. Bonzo Vaults: Architectural Innovation Bonzo Vaults stand out with their non-traditional approach that goes beyond the conventional ERC-4626 standard, introducing a dual-layer architecture. This strategy separates 'vault' contracts managing deposits from 'strategy' contracts that handle external engagements, providing unmatched flexibility to align strategies with market dynamics. A significant innovation came through their concentrated liquidity management strategy. Unlike the traditional methods of constant rebalancing, Bonzo Finance smartly opts for adjustments only when market shifts necessitate it, reducing resource use without sacrificing output. This approach is vital for developers looking to enhance efficiency and maximize returns strategically. Project Demo: Yield Optimization During a live demo, Bonzo Finance showcased how smart contracts in Bonzo Vaults activate yield-generating strategies. This demonstration highlighted interactions where deposits are strategized dynamically, tailored for various asset classes. Key performance metrics drove the point home: DOVU single asset vault: Offers a 7-day APY of 35%. USD-HBAR dual asset vault: Provides dual returns, with a 7-day APY of 61.9% and an impressive 30-day APY reaching 92.2%. These figures serve as powerful proof of concept and motivation for developers to delve into yield optimization strategies backed by cutting-edge technology. Key takeaway: Bonzo Vaults' architecture innovates liquidity management, reducing unnecessary actions while amplifying profitability.
The Technical Backbone of the Bonzo Ecosystem Bonzo Lend and Vaults: The Mechanics Deep within Bonzo's workings, custom smart contracts govern the functionality of Bonzo Lend and Vaults. They capitalize on automated mechanisms to optimize asset allocation strategy, maximizing the operational efficiency tied to returns. While specific APIs and contract addresses were not shared, Bonzo's session illuminated smart contract methodologies. You can adjust contract parameters regarding amount, frequency, and employed strategies, ensuring that they retain a high degree of adaptability and responsiveness. AI-Driven Rebalancing Strategies Elevating their platform, Bonzo Finance integrates advanced AI to enhance asset management. This innovation automates decision-making using real-time market data, which is a significant advancement for managing numerous liquidity positions with accuracy. Through market predictors, you can simulate and implement optimal strategies to increase yield without needing manual tweaks. This predictive AI application crafts an insightful roadmap, helping anticipate potential market maneuvers. Preparing for Cross-Chain Expansion Embracing the future, Bonzo Finance is set to integrate LayerZero Stargate, extending its liquidity capabilities across chains. This move empowers developers to orchestrate liquidity beyond Hedera's ecosystem, marking a pivotal step toward multi-chain yield optimization strategies. When this becomes reality, expect heightened interoperability through bridge contracts. This could redefine cross-chain liquidity and asset exchanges, paving the way for a new era of expansive risks and opportunities. Key takeaway: Bonzo Finance's AI strategies coupled with cross-chain expansion avenues empower you with pioneering tools for managing assets and liquidity more effectively.
Your Building Blocks on Hedera Using Bonzo's Platform for Innovation Bonzo Finance offers fertile ground for you to devise, structure, and launch novel financial services on Hedera. Here are pathways you can explore: Yield Optimization Models: Using Bonzo Vaults, you can craft sophisticated models to boost yields even in fluctuating markets. Existing strategies act as a template, while you adapt to market shifts to maximize high-yield opportunities. Cross-Chain Liquidity Solutions: As LayerZero Stargate materializes, use Hedera as a principal node in your DeFi endeavors, expanding beyond traditional boundaries into a cross-chain liquidity flow system. AI-Powered Rebalancing: Bonzo equips you with AI tools that streamline rebalancing efforts, reducing costs while addressing liquidity drifts. Design a decentralized protocol that adapts its strategies automatically. Efficient Building with Bonzo's Features Kickstart your DeFi projects on Bonzo Finance with these tactical steps: Conduct an in-depth review of Bonzo's smart contract structures to absorb best vault creation practices. Use performance data from operational vaults to polish your strategy, especially focusing on untapped assets and their combinations. Develop a prototype using Bonzo's strategies, ensuring you draw on comprehensive yield optimization potential. Gear up your infrastructure for the imminent cross-chain capabilities to exploit liquid access and performance gains. With Bonzo's development landscape, rapid deployment is facilitated through pre-fabricated layers, minimizing setup times and allowing you to bolster functionality that directly impacts user interaction. Key takeaway: Engaging Bonzo's ecosystem offers dynamic possibilities for crafting innovative DeFi solutions anchored in Hedera's ever-evolving infrastructure. Resources to Deepen Your Engagement Hedera Documentation: Explore Technical Guides (https://docs.hedera.com) Join the Hedera Community: Connect on Discord (https://hedera.com/discord) Official Livestream Source: Building AI Agents on Bonzo Finance (https://www.youtube.com/watch?v=P5Iw0XCr1UY) Are you using Bonzo Finance's advanced capabilities in your Hedera project? We'd love to hear how you're building on this transformative DeFi platform. Showcase your projects and join the conversation. Understanding Bonzo Finance's Ecosystem Components of the Bonzo Ecosystem The Bonzo Finance ecosystem is robust and strategically designed to enhance liquidity on the Hedera distributed ledger. As a builder, understanding the core components of Bonzo will empower you to use its tools for your decentralized applications. The ecosystem includes: Bonzo Lend Protocol: This protocol is central to Bonzo's offerings, enabling lending and borrowing within the Hedera ecosystem. It was developed by forking the Aave V2 protocol, a well-established lending protocol in the Web3 space. The team had to modify the contracts for compatibility with Hedera Token Service (HTS) and ensure seamless integration with SaucerSwap and other Hedera-native services. Bonzo Vaults: These provide automated yield optimization through liquidity provisioning on platforms like SaucerSwap. The vaults employ harvester bots for automatic rebalancing and yield compounding, allowing users to maximize their returns effortlessly. Bonzo Bridge: Integrating with LayerZero's Stargate protocol, Bonzo Bridge aims to facilitate cross-chain liquidity. This feature is expected to be a game-changer for Hedera, allowing liquidity to flow seamlessly between chains and expanding the reach of your DeFi applications. Understanding these components will help you optimize your strategies and build more efficient decentralized solutions on Hedera. The Role of Harvester Bots One of the standout features of Bonzo Finance is its use of harvester bots within the Bonzo Vaults. These bots are crucial for maintaining and maximizing your yield in a hands-off manner. Here's how they work: Automated Yield Compounding: Harvester bots automatically compound the yield derived from liquidity pools, ensuring that your returns are continually reinvested to maximize profitability. Continuous Rebalancing: The bots monitor market conditions and perform continuous rebalancing of assets within the vaults. This means your investment remains optimized for the highest possible returns without manual intervention. Seamless User Experience: With the automation provided by harvester bots, you can focus on other aspects of your DeFi strategy. The bots handle the complexity of yield farming, so you don't have to. By leveraging harvester bots, Bonzo Finance simplifies the yield optimization process, making it accessible to both novice and experienced DeFi participants.
Building AI Agents with Bonzo Finance Integrating AI Agents in DeFi Bonzo Finance's integration with AI agents represents a forward-looking approach to decentralized finance. As a developer, you can enhance your DeFi applications by incorporating AI-driven strategies that automate decision-making and optimize financial interactions. Contextual AI Prompts: When building AI agents, it's crucial to provide contextual prompts. For instance, using Bonzo's comprehensive data on liquidity and yield, AI agents can make informed decisions that align with market trends and user preferences. Agentic Coding Frameworks: Tools like Claude code and Codex allow for the development of smart AI agents that can interact with Bonzo's protocols. These frameworks help automate complex tasks, such as optimizing liquidity pools or executing strategic trades based on predictive analytics. Enhanced User Engagement: AI agents can enhance user engagement by providing personalized financial advice and real-time insights into their investment activities. This leads to a more interactive and educational DeFi experience. By embedding AI agents within your DeFi solutions, you can offer users a smarter, more dynamic financial ecosystem that adapts to their needs and the evolving market landscape. Practical Steps to Implement AI Agents If you're ready to integrate AI agents with Bonzo Finance, here's a practical guide to get started: Understand Bonzo's Protocols: Gain a deep understanding of Bonzo's lending, vault, and bridge protocols. This knowledge will inform your AI agent's decision-making process. Select an AI Framework: Choose an agentic coding framework like Claude code or Codex that aligns with your project requirements. Ensure the framework supports seamless integration with Hedera's ecosystem. Develop Contextual Prompts: Create prompts that provide your AI agents with the necessary context to make informed decisions. This includes data on liquidity, yield rates, and market conditions. Test and Iterate: Begin by testing your AI agents in a controlled environment within the Bonzo ecosystem. Gather feedback and iterate on the prompts and algorithms to enhance performance. Deploy and Monitor: Once satisfied with your AI agents' performance, deploy them within your DeFi application. Continuously monitor their interactions and make adjustments as needed to ensure they align with user goals and market changes. By following these steps, you can successfully deploy AI agents that add value to your DeFi applications and provide users with a more innovative financial experience.
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Sponsored By Design
How Sonic is expanding transaction sponsorship with V2.2. A user bridges assets to Sonic. They have USDC, ETH, or another asset they want to use, but no S to pay the network fee. Despite already having funds onchain, their first interaction can stop before it starts. Sonic introduced protocol-level transaction sponsorship with v2.1.2, allowing applications to cover network fees for their users. V2.2 takes that model further. Network-sponsored transactions can remove the fee entirely for qualifying activity, while successful-only sponsorship gives applications more control over when their sponsorship budget is spent. The result is a broader model for transaction execution: the user can pay, an application can pay, or for selected transactions, nobody has to pay at all. Sponsorship At The Protocol Level Sponsored Transactions on Sonic do not rely on an offchain relayer forwarding transactions for users. Sonic's transaction processing recognises sponsorship requests directly, while an onchain Subsidies Registry holds deposited S and defines which transactions those funds can cover. A transaction requests sponsorship by setting its gas price, or fee cap for newer transaction types, to zero. The node checks the Subsidies Registry and, if an eligible fund has sufficient balance, accepts the transaction for sponsored execution. The user still signs through the normal wallet flow. Sponsorship therefore changes who pays for execution, not who authorises the action. Apps Choose What They Pay For Sonic allows sponsors to define which activity they are willing to cover rather than paying for every transaction a user makes. Sponsorship can apply to transactions from a particular account, interactions with a particular contract, or calls to a specific contract function. Sponsors can narrow this further to a particular account calling a particular function. There are also dedicated mechanisms for ERC-20 approvals and bootstrap sponsorship, which can cover the first few transactions from a new account. A DEX could cover the approval required before a swap without paying for unrelated wallet activity. A lending market could cover interactions with its contracts, while another application could sponsor a new user's first few actions. Before execution, Sonic checks that sponsorship is still available. If it is, the user's transaction executes and an internal transaction charges the selected sponsorship fund for the gas consumed. This means the network fee still exists. It simply comes from the sponsor's deposit rather than the user's wallet. What If The Fund Runs Out? Sponsorship coverage can change while a transaction waits in the pool. A transaction might qualify when submitted but lose its backing if other transactions consume the available balance first. Sonic rechecks pending sponsored transactions and can remove those that are no longer covered. Sponsored transactions also carry an effective tip of zero, giving them the lowest transaction-pool priority. Under high network load, transactions offering a positive tip are prioritised ahead of them. These constraints are part of the trade-off. Sponsorship removes a payment requirement from the user, but the network still has to account for the execution and ensure someone is covering its cost. When Nobody Pays V2.2 extends the existing system with network-sponsored transactions. With a regular transaction, the user pays. With a sponsored transaction, an application or another sponsor pays from deposited S. With a network-sponsored transaction, a qualifying transaction can be processed without a token payment at all. No S is consumed, burned or rewarded to validators for its execution. Network sponsorship builds on the existing Gas Subsidies infrastructure rather than introducing a separate transaction system. The Subsidies Registry's chooseFund logic can return a special NETWORK_SPONSORED identifier, telling Sonic that the transaction qualifies to be processed without payment. The network can still be selective about what qualifies. Criteria could identify a particular stablecoin contract, restrict sponsorship to its transfer function, require a minimum transfer amount, or introduce additional conditions around senders and receivers. The user experience remains similar to existing sponsorship. An application creates a qualifying transaction with its gas price or gas-fee cap set to zero, the user signs it, and the transaction is submitted to Sonic. The difference comes during execution. Regular sponsorship requires an internal transaction to charge the sponsor's fund. A network-sponsored transaction has no sponsor to charge, so that payment transaction is not inserted. Sponsoring Successful Transactions V2.2 also introduces successful-only sponsorship, changing the economics for applications covering their users' network fees. Sponsorship applies only when the transaction succeeds. If an application sponsors a user's first deposit and the deposit completes, the application covers the network fee. If execution fails, the failed attempt does not consume its sponsorship budget. That distinction becomes important at scale. Instead of spending its budget on every attempted interaction, an application can direct sponsorship toward completed user activity. For protocols using sponsorship as part of onboarding or product UX, this makes the cost much easier to control. From sponsored transactions to sponsored workflows Sponsorship becomes more useful when it can compose with the other execution primitives arriving with V2.2. Bundled Transactions allow related transactions to execute with fate-sharing and no interleaving between their steps. A workflow can require every transaction to succeed or have the sequence rolled back rather than leaving the user with a partially completed operation. Consider a flow where a user needs to approve an asset, deposit it and perform another action. Sponsorship can remove the requirement to acquire S before beginning, while bundles can coordinate the related transactions so the workflow does not end in a partially executed state. Sponsored transactions can also be included within bundles. This creates a more flexible execution model. Sonic can separate who authorises a transaction, who pays for it, whether a qualifying transaction requires payment at all, and how related transactions execute together. The user still signs what they do. Applications decide what they subsidise. For selected activities, the network can remove the fee entirely. And with bundles, sponsored transactions can become part of coordinated multi-step workflows. Sponsorship is no longer just a way to pay someone else's gas. With V2.2, it becomes part of how applications are designed.
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Sponsored By Design
How Sonic is expanding transaction sponsorship with V2.2.
A user bridges assets to Sonic. They have USDC, ETH, or another asset they want to use, but no S to pay the network fee. Despite already having funds onchain, their first interaction can stop before it starts.
Sonic introduced protocol-level transaction sponsorship with v2.1.2, allowing applications to cover network fees for their users. V2.2 takes that model further. Network-sponsored transactions can remove the fee entirely for qualifying activity, while successful-only sponsorship gives applications more control over when their sponsorship budget is spent.
The result is a broader model for transaction execution: the user can pay, an application can pay, or for selected transactions, nobody has to pay at all.
Sponsorship At The Protocol Level
Sponsored Transactions on Sonic do not rely on an offchain relayer forwarding transactions for users. Sonic's transaction processing recognises sponsorship requests directly, while an onchain Subsidies Registry holds deposited S and defines which transactions those funds can cover.
A transaction requests sponsorship by setting its gas price, or fee cap for newer transaction types, to zero. The node checks the Subsidies Registry and, if an eligible fund has sufficient balance, accepts the transaction for sponsored execution. The user still signs through the normal wallet flow.
Sponsorship therefore changes who pays for execution, not who authorises the action.
Apps Choose What They Pay For
Sonic allows sponsors to define which activity they are willing to cover rather than paying for every transaction a user makes.
Sponsorship can apply to transactions from a particular account, interactions with a particular contract, or calls to a specific contract function. Sponsors can narrow this further to a particular account calling a particular function. There are also dedicated mechanisms for ERC-20 approvals and bootstrap sponsorship, which can cover the first few transactions from a new account.
A DEX could cover the approval required before a swap without paying for unrelated wallet activity. A lending market could cover interactions with its contracts, while another application could sponsor a new user's first few actions.
Before execution, Sonic checks that sponsorship is still available. If it is, the user's transaction executes and an internal transaction charges the selected sponsorship fund for the gas consumed.
This means the network fee still exists. It simply comes from the sponsor's deposit rather than the user's wallet.
What If The Fund Runs Out?
Sponsorship coverage can change while a transaction waits in the pool. A transaction might qualify when submitted but lose its backing if other transactions consume the available balance first. Sonic rechecks pending sponsored transactions and can remove those that are no longer covered.
Sponsored transactions also carry an effective tip of zero, giving them the lowest transaction-pool priority. Under high network load, transactions offering a positive tip are prioritised ahead of them.
These constraints are part of the trade-off. Sponsorship removes a payment requirement from the user, but the network still has to account for the execution and ensure someone is covering its cost.
When Nobody Pays
V2.2 extends the existing system with network-sponsored transactions.
With a regular transaction, the user pays. With a sponsored transaction, an application or another sponsor pays from deposited S. With a network-sponsored transaction, a qualifying transaction can be processed without a token payment at all. No S is consumed, burned or rewarded to validators for its execution.
Network sponsorship builds on the existing Gas Subsidies infrastructure rather than introducing a separate transaction system. The Subsidies Registry's chooseFund logic can return a special NETWORK_SPONSORED identifier, telling Sonic that the transaction qualifies to be processed without payment.
The network can still be selective about what qualifies. Criteria could identify a particular stablecoin contract, restrict sponsorship to its transfer function, require a minimum transfer amount, or introduce additional conditions around senders and receivers.
The user experience remains similar to existing sponsorship. An application creates a qualifying transaction with its gas price or gas-fee cap set to zero, the user signs it, and the transaction is submitted to Sonic.
The difference comes during execution. Regular sponsorship requires an internal transaction to charge the sponsor's fund. A network-sponsored transaction has no sponsor to charge, so that payment transaction is not inserted.
Sponsoring Successful Transactions
V2.2 also introduces successful-only sponsorship, changing the economics for applications covering their users' network fees.
Sponsorship applies only when the transaction succeeds. If an application sponsors a user's first deposit and the deposit completes, the application covers the network fee. If execution fails, the failed attempt does not consume its sponsorship budget.
That distinction becomes important at scale. Instead of spending its budget on every attempted interaction, an application can direct sponsorship toward completed user activity.
For protocols using sponsorship as part of onboarding or product UX, this makes the cost much easier to control.
From sponsored transactions to sponsored workflows
Sponsorship becomes more useful when it can compose with the other execution primitives arriving with V2.2.
Bundled Transactions allow related transactions to execute with fate-sharing and no interleaving between their steps. A workflow can require every transaction to succeed or have the sequence rolled back rather than leaving the user with a partially completed operation.
Consider a flow where a user needs to approve an asset, deposit it and perform another action. Sponsorship can remove the requirement to acquire S before beginning, while bundles can coordinate the related transactions so the workflow does not end in a partially executed state. Sponsored transactions can also be included within bundles.
This creates a more flexible execution model. Sonic can separate who authorises a transaction, who pays for it, whether a qualifying transaction requires payment at all, and how related transactions execute together.
The user still signs what they do. Applications decide what they subsidise. For selected activities, the network can remove the fee entirely. And with bundles, sponsored transactions can become part of coordinated multi-step workflows.
Sponsorship is no longer just a way to pay someone else's gas. With V2.2, it becomes part of how applications are designed.
10·CNeutral
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news9/3news
One year ago this month, the SEC issued a No-Action Letter confirming that DoubleZero's solana:J6pQQ3FAcJQeWPPGppWRb4nM8jU3wLyYbRrLh7feMfvd token can flow in the protocol as designed.
It was one of the first NALs the SEC has granted to a crypto project since 2020, and the most significant one yet, because it lays out a clear framework other projects could follow.
The best regulatory outcomes come from regulators and innovators working closely together. 🤝
80·ALong
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SpaceX Highlights Starbase Ambitions, & More
This week's newsletter covers Starbase Louisiana, OpenAI Jalapeño results, and Figure AI's Index app.
1. SpaceX Highlights Starbase Ambitions By: Brett Winton | Chief Futurist | @wintonARK Last week, SpaceX and Governor Jeff Landry announced Starbase Louisiana, a $100 billion commitment to build one of the largest infrastructure projects in history on roughly 125,000 acres at Pecan Island in Vermilion Parish.[1] The greenfield investment includes five complexes, each with two Starship towers, with ten pads at the outset, and eventually more than a dozen towers supporting ~30 flights per day. The land will include not only a launch site, but also onsite propellant production, power generation, deep-water shipping, vehicle processing, employee housing, and likely an airport. Construction will begin in 2027, with first launches no earlier than 2029. Two geographic features were the deciding factors. Launch corridors facing south over the Gulf will give SpaceX efficient access to the polar orbits for its space-based compute constellation, and natural gas in Louisiana will power the methane-fueled rockets. Gwynne Shotwell was clear about the motivation: the company's existing infrastructure—two pads at Starbase in Texas and three soon-to-be in Florida—cannot support the ambitious plans for Starship’s flight cadence.[2] For perspective on the scope of the project, Brazil’s 14 gigawatt (GW) Itaipu hydropower plant, the closest completed contemporary analog, cost ~$90 billion in today’s dollars, and California’s much delayed and uncompleted high-speed rail project is projected to cost ~$125 billion, as shown below.
What Explains The Size Of This SpaceX Investment? SpaceX needs the capacity because the payloads-in-waiting are worth potentially trillions of dollars a year, starting with billions for its Starlink communications constellation and, we believe, trillions for its Starmind constellation. Based on ARK’s projection of SpaceX’s monetization rate per communications satellite, a single reusable rocket filled with Starlink satellites could generate ~$4 billion in lifetime net cashflow relative to the $1 billion in combined launch, satellite manufacture, ground station installation, and customer acquisition costs. Importantly, the towers at Pecan Island should be able to catch Starship. Indeed, if Starship launches its tenth fully reusable commercial rocket successfully in 2027, as we anticipate, the post-tax IRR (Internal Rate of Return) would approach 100% at an annual rate, as shown below.
With that kind of return, the constraint on SpaceX will not be capital but the physical capacity to deploy it. The company should maintain similarly healthy, albeit moderately diminishing, returns even as it scales through hundreds of Starlink-carrying Starship flights. Though the Starlink opportunity will eventually saturate, the galaxy is the limit for SpaceX’s AI opportunity. By its 100th AI satellite launch ARK’s research suggests all-in costs to manufacture and launch its satellites will already run roughly half that of terrestrial datacenter developers. At that time ARK’s research anticipates that SpaceX will still be spending substantially on research and development (R&D) and will mostly monetize its orbital constellation by renting out capacity as an infrastructure-as-a-service provider while it seeks to catch up to the performance frontier currently occupied by Anthropic and OpenAI. Even with those constraints, its early Starmind launches should be able to yield IRRs in the high 20s as can be seen below.
As the buildout expands, datacenter economics on the ground are likely to get worse as developers cope with local opposition and have to find exponentially increasing amounts of power. Meanwhile, SpaceX should become increasingly expert at manufacturing its satellites and packing more satellites into each launch; its economics should get better. Its 1000th launch could enjoy upfront costs at less than 40% those of the terrestrial benchmark. The volume of compute that SpaceX will command simultaneously suggests that it should be able to catch up with the performance frontier, pull back on research and development use of its constellation, and deliver higher-monetizing AI software to end-customers. By its 1000th launch, the prospective IRRs of Starmind could double those of Starlink at its peak, even as SpaceX invests much larger dollar volumes into the AI constellation.
What Will Be The Macroeconomic Impact Of This Investment? Based on Louisiana's ~$344 billion in nominal gross domestic product (GDP),[3] a capital commitment of $100 billion, no matter how phased, will move the needle, especially because it will impact a parish of fewer than 60,000 people. Compared to the state’s GDP per capita of ~$56,000, its fact sheet on this project projects 3,000 direct new jobs and ~8,100 indirect jobs with salaries averaging $92,600 per year over ten years. Landry put the historical contrast in stark relief: for generations, industry has extracted oil, gas, and petrochemicals from Louisiana, taking their share of state GDP down from ~25% in 1999 to less than 20% today.[4] SpaceX is entering Louisiana not to extract, but to build. Chronically underestimated in macro forecasts, disruptive innovation does more than displace the existing capital stock: it increases the expected return on new capital enough to incentivize physical infrastructure that otherwise would not be built. In 2015, no company would have considered investing $100 billion in an industrial complex on Pecan Island to serve the rocket launch business. Rocket reusability changed the expected return on capital on such a project, which summoned the capital. Now, the capital is buying propellant plants, power generation, and port infrastructure in a parish that had none. More important than the initial investment will be the second-order impact. Infrastructure built to accommodate a technology on a steep cost-decline curve should generate a higher return on capital than the legacy stock it displaces, delivering productivity—cheaper access to orbit, always-on connectivity, cheaper compute per watt—that redeploys labor, energy, and land at the margin for more productive uses cases. That supply-side expansion is the reason the growth associated with disruptive technology is much larger than consensus models have incorporated.
2. OpenAI’s Jalapeño Could Accelerate The Shift Toward Custom AI Silicon By: Karim Mattar | Research Associate, AI & Cloud | @MattarARK Last week, OpenAI published the first results for Jalapeño, its first custom inference chip developed with Broadcom. â� Relative to Kimi K2.5, the largest public model tested, OpenAI reported ~1.5 times higher peak performance per watt and 3.4 times lower latency, as shown below.[5] Across Kimi K2.5, DeepSeek R1, and GPT-OSS 120B, Jalapeño achieved the performance-latency frontier despite being OpenAI’s first attempt.
SemiAnalysis independently verified Jalapeño’s InferenceX results at OpenAI’s lab and found that it outperformed Blackwell on performance per watt across nearly all of the workloads tested.[7] Its output-token throughput per megawatt also exceeded NVIDIA’s latest public Rubin results in SemiAnalysis’s testing.[8] Rubin is the more appropriate comparison, given the timing of the two chips. That said, the results are early: Jalapeño remains on engineering silicon and SemiAnalysis has yet to test it on AgentX, its benchmark for longer, multi-turn agentic workloads. Perhaps more interesting than the benchmark results is how quickly OpenAI got there. Using its own AI models during the design and optimization process, OpenAI took Jalapeño from initial Register-Transfer Level (RTL) to tapeout[9] in roughly nine months.[10] SemiAnalysis also noted that OpenAI used Codex to overcome one of the traditional disadvantages associated with custom silicon: developing kernels for Jalapeño and shortening the time necessary to build a mature software stack around new hardware. As power becomes a larger constraint on AI infrastructure, squeezing more inference from each megawatt will become increasingly valuable. â� OpenAI and Broadcom plan to deploy 10 gigawatts of OpenAI-designed accelerators through 2029,[11] giving OpenAI the volume to spread chip-development costs across an enormous inference workload. Jalapeño does not mean that OpenAI will stop buying NVIDIA graphics processing units (GPUs), particularly for training. Instead, its early performance suggests that frontier AI companies operating at sufficient scale can justify the cost of designing their own inference silicon, particularly if AI itself continues to compress chip-development timeline cycles.
3. Figure AI Unveils Index, The Largest And Most Diverse Robot Dataset In The World By: Daniel Maguire, ACA | Research Analyst, Autonomous Technology & Robotics | @DMaguireARK Last week, Figure AI came out of stealth mode with Index, a consumer app that pays people to record everyday tasks on camera, sourcing real-world physical data to train humanoid robots.[12] Over four months in stealth, the app has surpassed 264,000 downloads across 108 countries, with users uploading more than 16 million videos and earning $15 million and creating the largest and most diverse robot training dataset in the world, according to Figure AI. The company has committed more than $1 billion to data and compute over the next 12 months. Notably, to outsource the tasks, users can book Creators—a human-powered on-ramp to robots-as-a-service. The launch of Index underscores the importance of diverse real-world data, the current bottleneck for humanoid robot deployment at scale. Hardware is advancing rapidly, as demonstrated during last week’s World Humanoid Robot Games in Beijing, during which Chinese humanoids beat Usain Bolt's 100m world record.[13] Commercial deployments, however, remain few and far between. As a result, companies are beginning to collect data in-house: Tesla flagged its own data efforts on its latest earnings call,[14] and Unitree's CEO is allocating a large portion of proceeds from the company’s initial public offering (IPO) toward software development.[15] ARK's research suggests that humanoid robots are ~200,000X more complex than autonomous vehicles. That complexity is likely to create a ~$26 trillion total addressable market, split roughly evenly between household and manufacturing applications, as shown below.
The development of humanoid robots is still in early innings. We look forward to monitoring the pace of scaling over the coming years.
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[1] Louisiana Economic Development. 2026. “SpaceX Launches New Era of Commercial Spaceflight with $100 Billion Louisiana Campus.� [2] Ibid. See also SpaceX. 2026. “SpaceX Reports Second Quarter 2026 Results.� [3] Bureau of Economic Analysis. 2026. “GDP by State.� [4] Louisiana Economic Development. 2026. “SpaceX Launches New Era of Commercial Spaceflight with $100 Billion Louisiana Campus.� [5] OpenAI. 2026. “Jalapeño’s first results show industry-leading speed and efficiency in AI inference.� [6] Ibid. [7] Shan, B. et al. 2026. “OpenAI Jalapeño: Better Than Nvidia Blackwell.� SemiAnalysis. [8] Ibid. [9] The RTL to Tapeout process transforms a high-level Register-Transfer Level (RTL) hardware description into a final, manufacturable layout file delivered to a foundry. See ChipExpert. 2025. “From RTL to Tapeout : A Complete VLSI Flow Explained.� [10] OpenAI. 2026. “OpenAI and Broadcom unveil LLM-optimized inference chip.� [11] Broadcom. 2025. “OpenAI and Broadcom announce strategic collaboration to deploy 10 gigawatts of OpenAI-designed AI accelerators.� [12] FigureAI. 2026. “Introducing Index: Building The World’s Largest and Most Diverse Physical Dataset.� [13] Zhuang, Y. “2026. A Chinese Robot Beat Usain Bolt’s 100-Meter Record. Should We Be Impressed?� The New York Times. [14] Yahoo!Finance.2026. “Tesla, Inc. (TSLA) Q2 FY2026 earnings call transcript.� [15] Wang, Y. 2026. “Unitree IPO Turns 36-Year-Old Founder Into China’s First Humanoid Robot Billionaire. Forbes. [16] International Federation of Robotics. 2025. “National Robot Density.� Knutsen, R. et al. 2025. “Quadruped State of The Market - Unitree, Boston Dynamics, ANYbotics, DEEP Robotics, and The Rising Application Ecosystem.� SemiAnalysis. 36Kr European Central Station 2025 2025. “Unitree Launches Listing Guidance: Favored by Capital, but Mass Production Yet to Come.�
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US will control flow of funds from NABEP deal with Venezuela, Energy Secretary Chris Wright says