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Does the forecast market with monthly turnover of 44.8 billion US dollars need a main broker?

Does the forecast market with monthly turnover of 44.8 billion US dollars need a main broker?

Source: Fintech Blueprint Compiled and edited by BitPushNewsBetterment recently published its 2026 retail investor survey. The main conclusion is that 26% of Gen Z investors see sports betting as part of their long-term financial strategy, and 52% have invested the money they originally intended to invest into it last year. The survey of 1000 US retail investors in early April showed that proportion rapidly declined as people grew older — 31% and 14% for millennials, 10% and 6% for Gen X, and 4% and 1% for Baby Boomers. Betterment CEO Sarah Levy put it bluntly: The problem comes when a prediction market or sports betting platform starts to feel like a retirement strategy. The combined monthly trading volume of Kalshi and Polymarket reached $44.8 billion in June, which is more than three times the average monthly transaction volume of approximately $14 billion for all US legal sports betting in 2025. Source: Bloomberg/Betterment Let's explore whether this transaction volume is huge enough to support the dedicated agency hierarchy below. Earlier this month, River Markets raised $8.5 million in seed funding to build what it calls “the first institutional-grade execution and prime broker platform for the prediction market.” Led by Haun Ventures, Y Combinator, Coinbase Ventures, Qube Research & Technologies, and Cherry Ventures participated, in addition to angel investors from Citadel, HRT, J.P. Morgan, Nvidia, and Google. The company has been online with trading clients since May 1 and has publicly listed five client names: Chimera Capital Management, Game Point Capital, Cleat Street, Skywalk, and 646 Equity. It claims to own three of the top ten traders on Kalshi and Polymarket, as well as several quantitative funds running on its API. The problems they are solving are real and unremarkable. The liquidity of the prediction market is distributed across multiple trading sites, which may have different quotes on the results of the same event, involving separate accounts, separate balances, independent APIs, and no uniform view of risk. A trader who trades the same event on Kalshi and Polymarket actually manually manipulates the two books and then reconcile the accounts. River integrates these sites into a single terminal and an API, uses a unified code system, adds execution algorithms (iceberg orders, linked orders, stop-loss orders, take-profit orders) not native to the exchange, and routes eligible orders to the best prices in the online ledger. It's live on Kalshi, Polymarket, and Polymarket US, and is integrating Novig and Crypto.com. Today, it's more like an order and execution management system than a Prime Broker (PB) — a boundary drawn by River itself. Its FAQ states that the real-time platform covers execution, routing, data, and profit and loss, that customer funds are kept in venue accounts rather than centrally pooled, and that companies are invited to contact them about financing, collateral, and cross-market requirements. Source: Allium predicts that the cumulative historical trading volume of the market exceeded 150 billion US dollars in May. Kalshi alone reached 31.5 billion US dollars in June, while Polymarket was 10.8 billion US dollars. Kalshi is currently in final negotiations to finance at least $750 million, with a valuation of $40 billion; Polymarket is financing at a valuation of $15 billion, after ICE had already committed $2 billion in two instalments. Kalshi's annualized revenue surpassed $4 billion in July, roughly double the $2 billion annualized pace two months ago. At the peak of the World Cup,...

4d agoBitpushNews#HYPERLIQUID #Kalshi #Ondo

Ethereum's EIP-12188 Proposal to Reduce Consensus-Layer Block Retention Window Receives Developer Support

In comparison, Ethereum developer Kevaundray submitted a EIP-12188 proposal on GitHub, recommending reducing the consensus layer (CL) block retention window to reduce the storage pressure on nodes. The proposal is currently under public review and has received support from some Ethereum client developers. Developer dapplion expressed support for the idea, and Lighthouse client contributor Michael Sproul believes that the tweak will not cause significant issues with Lighthouse's operation. The proposal points out that as Ethereum's historical data requirements change, reducing the retention time of historical blocks in the consensus layer can optimize the use of node resources. The discussion mentioned that execution layer (EL) historical data clipping may affect some long-term running nodes to provide old block data, but the developers believe this will not threaten network security or the normal operation of the node. Currently, EIP-12188 has not been merged and is subject to further review and community discussion.

4d ago
After eight years of investment, why did Ethereum abandon Poseidon?

After eight years of investment, why did Ethereum abandon Poseidon?

Author: ChandlerZ, Foresight News Original title: After eight years of sharp turns, why did Ethereum suddenly abandon Poseidon? On August 13, Ethereum researcher Justin Drake wrote on X that the Ethereum Fund decided to abandon the SNARK-friendly hash algorithm Poseidon at the L1 layer and instead use traditional hash functions such as SHA2 or BLAKE2. Behind this decision is eight years of research, the accumulation of tens of millions of dollars, and a major revision to the post-quantum cryptography roadmap. Since its launch in 2019, Poseidon has been regarded as an ideal hashing scheme for applications such as zkRollup and zKVM. Its structure makes it cheaper and more efficient than traditional binary-based hash functions in SNARK circuits. But when post-quantum security became a hard requirement for Ethereum, Poseidon's limitations began to be exposed. Justin Drake said that this shift is due to groundbreaking SNARK design progress, that is, the performance of traditional hash functions in SNARK circuits is comparable to that of Poseidon, which was previously designed specifically for SNARK optimization. A single laptop can verify about 1 million traditional hash calls per second. According to the article, Poseidon has been the mainstream SNARK-friendly hashing scheme since its launch in 2019, providing security guarantees for applications such as zkRollup and zKVM. Justin Drake said that the plan shows that production-grade LeanVM is expected to be launched in 2027, the relevant deployment of the consensus layer, data layer and execution layer is expected to be completed in 2028, and the quantum team is also accelerating research related to the binary domain after the Ethereum Foundation. Why now? Traditional hashes have been difficult to enter SNARK for a long time, and the main obstacle comes from differences in computational languages. SHA2, BLAKE2s, and Keccak make extensive use of Boolean operations such as XOR and shift. Traditional SNARK usually processes arithmetic on large prime numbers, and simulating every bit operation can incur high constraint costs. Poseidon is designed directly around prime field arithmetic, with fewer constraints in exchange for higher proof speed. The cost is that the algorithm has a short history and requires continuous cryptographic analysis. The binary domain switches the underlying math to the smallest element domain containing only 0 and 1, and uses the binary domain extension to carry larger data. As a result, bit computation can directly enter the proof system. SNARK began to adapt to traditional hashes, and the technical focus changed from designing SNARK-friendly hashes to designing hash-friendly SNARKs. Binius, proposed by Jim Posen and Benjamin Diamond in 2023, shows the binary tower domain SNARK path. The Flock paper by Benedikt Bünz, Ron Rothblum, and William Wang was uploaded to arXiv on July 29, 2026. Its M4 Max benchmark is that a single core proves 82,000 times of BLAKE3 compression and 42,000 SHA- cycles per second With 256 compression and 30,000 Keccak replacements, the 10-core BLAKE3 has a throughput of over 660,000 times. According to Drake, the laptop can prove about 1 million traditional hash calls per second, which is about 100 times the cost of native CPU Boolean calculations; SNARK.fast reached 1.8 million BLAKE3 per second on M3 Max a few days ago. LeanVM in 2027, the 2028 three-tier deployment Another key reason for the abandonment of Poseidon is that the post-quantum security timeline is accelerating. “The Quantum Threat to Blockchains - 2026 Report” published by Project Eleven points out that the rapid development of quantum computers poses a serious threat to blockchain security. Once a “cryptographics-related quantum computer” (CRQC) appears, the Shor algorithm can quickly crack asymmetric cryptography such as ECDSA (used by Bitcoin and most public chains) and RSA. It is expected that Q-Day (quantum decryption day) may be between 2030 and 203...

5d agoForesight News#L1 #Ethereum

Ethereum Foundation launches Platåberget testnet for Glamsterdam to upgrade early testing

Comparatively, the Ethereum Foundation Protocol DevOps team announced the launch of the Platåberget testnet as an early public testing environment for the Glamsterdam (Gloas+ Amsterdam) upgrade. The testnet is open to the community and is scheduled to run for several months to provide developers with a stable testing platform to find and fix issues before upgrading to long-term test networks such as Sepolia and Hoodi. The Glamsterdam hard fork is scheduled to be activated on this testnet on August 20. The Glamsterdam upgrade covers a number of major changes in the consensus layer and execution layer, including built-in proposer-builder separation (ePbS), block-level access lists (BARs), gas repricing targeting approximately 200 million gas, increasing the maximum contract deployment size from 24 KiB to 64 KiB, increasing the initcode limit from 48 KiB to 128 KiB, and forward-compatible consensus data structures. The relevant EIPs are summarized in meta EIP-7773. Gas repricing will affect wallets, indexers, and gas estimation tools. Any tool with a hardcoded maximum gas limit will need to be updated; EIP-8037 also introduces an independent state gas dimension, and new accounts created or written to a new storage slot will be billed based on status bytes. The Platåberget validator set is small and allows the public to join, and supports submitting validator or builder deposits through the Dora browser. The testnet provides one-click addition of network, faucet, and client image resources. The community can provide feedback on the Ethereum R&D Discord and related specification repositories. This article is sponsored by GENG, Build Your Fortune on GENG (https://geng.one)

5d agoburnking

Ethereum L1 abandons Poseidon's hashing algorithm and shifts to the quantum cryptography route after SHA2 or BLAKE2

In comparison, Justin Drake, a core researcher at the Ethereum Foundation, announced in an article on the X platform that Ethereum L1 will no longer use Poseidon, the SNARK-friendly hash function that has dominated since 2019, and switch to traditional hash functions such as SHA2 or BLAKE2s. The adjustments are based on developments in the SNARK design field, and the focus is shifting from “SNARK-friendly hashing” to “hash-friendly SNARK.” By natively aligning boolean operations in traditional hashes in the binary domain, the proven performance of traditional hashes in SNARK has reached 1 million times per second, and the cost is about 100 times higher. Research such as Binius and Flock has fueled related developments. The Ethereum Foundation's post-quantum team is advancing this route, and the roadmap includes deploying production-grade LeanVM in 2027 and deployment at the consensus layer, execution layer, and data processing layer in 2028. Justin Drake also said that the enhanced ability of AI in cryptographic analysis has caused HAWK and the homologous solution SQISign to be hit one after another recently, and the hash-based scheme is being used for post-blockchain quantum signatures. The trend of open source automated research is also accelerating, and SNARK.fast has achieved 1.8 million BLAKE3 proofs per second.

9d ago
Behind Hermes' rise to the top: A Web3 team's path to advancement

Behind Hermes' rise to the top: A Web3 team's path to advancement

Author: Jacob Zhao Original title: IOSG Weekly Brief | Behind Hermes's rise to the top: A Web3 team's path to advancement The phenomenal growth of #340Hermes did not stem from OpenClaw's exclusive technology that cannot be replicated in principle, but because it most accurately closed a “challenger growth system” during the critical window of individual agent category formation: taking over OpenClaw's already educated and mature user pool to establish “delegability” ( (Incurable Trust) This difference in experience is more real than the “self-evolution” narrative. As professional execution agents become more and more powerful, users still need a manager who is online for a long time and is worth entrusting. Open OpenRouter's public application rankings. Hermes Agent ranked first on all platforms with 30.5 trillion token usage, and also ranked first in the four categories of Productivity, Coding Agents, Personal Agents, and CLI Agents, leading well-known agents such as OpenClaw and Claude Code in a cliff-style manner. ▲ Figure 1 · Hermes Agent's historical data snapshot on OpenRouter (taken on August 4, 2026, dynamic page data will change over time) Although OpenRouter's statistical caliber cannot cover industry-wide token consumption directly connected to official APIs (such as Claude or Codex native subscriptions), as the world's largest AI model routing and aggregation platform, its list has strong “weather vane” significance. Although at the level of high-end professional tasks, the core business workflows of many users — complex code generation, architecture design, and high-value data analysis — still flow to Claude Code and ChatGPT, Hermes maintains an advantage in use scenarios such as back-office automation, message entry response, long-term online monitoring, and lightweight task scheduling. As an Agent product created by the Web 3 team, Hermes has achieved far more successful dissemination, community, and usage intensity than expected. We can't help but pay attention to: · Why can Hermes surpass OpenRouter inference calls? · What is the real field between it and OpenClaw? · How does Hermes maintain “differentiated coexistence” rather than “head-on competition” in the relationship with Claude Code and Codex? From development frameworks to personal AI systems — the path of OpenClaw why did the early Agent framework not produce consumer products. Before the advent of OpenClaw, the agent field had mature infrastructure, but there were fundamental limitations: the unit used was a “development project enterprise workflow” rather than an “individual user.” The common characteristics of early frameworks were developer-facing, outputting code, or configuration—they built the Agent's infrastructure, but did not deliver the Agent itself. Too high engineering thresholds have always been stuck in the “developer tool” stage, there is a lack of a closed loop of commercialization that transforms technology into “personal assets”, and the “personal agent product layer” directly aimed at end users is almost empty. ▲ Figure 1 · Six-layer structure of the Agent technology stack (model layer → protocol layer → SDK development framework layer → execution infrastructure layer → deployment governance layer) ▲ Figure 1 · Historical data snapshot of Hermes Agent in OpenRouter (taken on August 4, 2026, dynamic page data will change over time) What did OpenClaw really change? OpenClaw did not reinvent Agent Loop or task scheduling technology at the bottom. Its core contribution is systematic packaging at the product level. LangChain solved “how to build an agent”, while OpenClaw solved “how to own an agent”. It skips the middle layer of the technology stack, integrates scattered framework capabilities into a complete product that individuals can directly configure and use for a long time, and realizes a fundamental shift in adoption units from “development projects” to “individuals”...

9d agoburnking#agent #Hermes #WEB3

Pi restructured the Agent execution layer: long tasks began to run continuously

In comparison, according to monitoring, Pi is reworking Agent Harness. The latest Harness v3 specification has been written and is undergoing a final audit. It has redone task execution and storage, so the Agent can continue where it left off even if half of the process crashes, or even if Harness upgrades itself. Pi is an open source Agent Harness created by Mario Zechner, and was first introduced by OpenClaw. The project was acquired by Earendil this year, and Mario also joined the company to continue to be responsible for development. Now Pi has over 60,000 GitHub Stars, and MiniMax's latest MiniMax Code also clearly builds Harness based on OpenCode and Pi. v3 has directly redone the underlying architecture this time. The execution state is saved before model requests and tool calls, and the results are written after completion. After rebooting, Pi knows what has been done, what can be restarted, and what has side effects that cannot be executed again. Dialogues, operating status, and token costs have also been changed to be stored separately, and cross-version state migration has been added. Claude Code and Codex are pushing agents to longer tasks. OpenAI has specialized in how to keep Codex working for a long time, and Anthropic, also known as Claude Code, is increasingly being used for long-running agent tasks. After the Agent can run continuously for a few hours, the first few hours can't be completely dried up because of a single crash.

11d ago

The DeepSeek version of Claude Code is getting closer, and the Harness team opens an official public account

Comparative news, according to monitoring, the DeepSeek Harness team has opened an independent WeChat account and obtained corporate certification. Previously, the team mainly appeared to the public through recruitment information and members' personal accounts. Harness is an agent execution layer outside of the model, responsible for context, tool calls, and task execution. When the official version of DeepSeek V4-Flash was released on July 31, the DeepSeek Harness minimal mode was used to open the Code Agent benchmark, and indicated that it would be released soon. The team also recently began publicly recruiting Harness beta users. Applicants are required to have relevant open source project experience and submit a GitHub ID and representative work.

11d ago

VeChain launches Interstellar phase, VIP-255 upgrade proposal starts voting on August 10th

Comparing news, the VeChain Foundation published an article announcing Interstellar's entry into the next phase of the Renaissance roadmap. Previously, Galactica had completed the EVM infrastructure upgrade, and Hayabusa completed consensus and token economy transformation. Interstellar aims to deepen VeChainThor's EVM compatibility with the Ethereum ecosystem and expand developer capabilities. The first upgrade proposal, VIP-255, will introduce execution layer improvements compatible with versions of Ethereum such as Cancun, Prague, and Osaka, including transient storage, MCOPY instructions, and BLS12-381 and secp256r1 cryptography support. Voting will take place from August 10, 2026 at 00:00 UTC to August 17 at 00:00 UTC via the vEVote platform, and validators and eligible Stargate NFT holders can participate. The upgrade does not affect the VET and VTHO token economies, and no action is required for ordinary holders.

14d ago

Ethereum Foundation Recruits Protocol Security Researchers to Focus on AI-Assisted Vulnerability Mining and Hard Fork Reviews

Comparatively, the Ethereum Foundation (Ethereum Foundation) released recruitment information for Protocol Security Researchers (Protocol Security Researchers), which is part of the Protocol Security Team, which is responsible for identifying security vulnerabilities at the execution layer, consensus layer, network layer, specification and client implementation. The work covers AI-assisted security research and automated vulnerability mining, hard fork review, fuzzy testing tool construction, manual audit of protocol changes, and coordinated vulnerability disclosure. The team requires candidates to have deep experience with the Ethereum protocol. Priority is given to engineers who are already actively involved in protocol development and are familiar with execution or consensus layer specifications. Common programming languages include Go, Rust, Java, C #、Nim, and Python. They work remotely, and are open to European and global candidates.

16d ago#On-chain dynamics