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Ant Group's UBTree improves speculative decoding: parallel screening of draft trees enables large models to verify more tokens at a time.

43 minutes ago

Insight Beating AI News Flash: Ant Group’s Bailing has open-sourced the large language model speculative decoding scheme UBTree. Speculative decoding lets a small model draft outputs in advance, with a large model validating multiple tokens at once to cut down on token-by-token generation computation rounds. However, drafts suffer from hit rate issues: the earlier the small model guesses wrong, the less content can be adopted directly later. Existing tech prepares multiple candidate paths, organizes them into a draft tree, and prunes low-probability branches. UBTree improves the filtering method: it first parallelly predicts possible tokens for subsequent positions, then uses a lightweight model to assess adjacent token logical coherence. Different combinations are scored simultaneously, eliminating repeated model runs along each path. It then selects promising branches to form a draft tree for the large model’s validation. The team also adjusted the filtering model’s training approach, enabling it to not only focus on highest-probability answers but also identify viable alternative paths, letting the large model accept more tokens per round. In seven Qwen3-4B tests, the average speedup ratio using the DFlash 2 selector for tree construction was 5.95x. After switching to the UBTree selector and adjusting training, this rose to 6.88x, an approximate 16% improvement over the original scheme.

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Trade.xyz Founder: 381-day-old product partners with ICE to build universal exchange.

Trade.xyz founder @sershokunin has published a lengthy article, announcing: "381 days after Trade.xyz’s first market went live on Hyperliquid, we are partnering with ICE. Upon CFTC approval, we will launch a dedicated U.S. market offering Hyperliquid-powered 24/7 perpetual contracts covering stocks, indices, commodities, forex, crypto, and other assets. U.S. users previously could not directly trade these markets; they will now gain access to innovative products paired with U.S. regulatory protection. ICE has made a strategic investment, and has invited participants including Stan Druckenmiller." In the post, @sershokunin also stressed the protocol’s vision: building a "universal exchange" that enables trading any asset anytime, anywhere. The ultimate goal is to realize the vision that "everything you own works in harmony with everything you trade" — such as using tokenized stocks as collateral, hedging indices, and trading pre-IPO companies, all completed within a single account.

10 minutes ago

Curve Finance launches on Stellar, becoming its first non-EVM native deployment.

DeFi protocol Curve Finance and the Stellar Development Foundation announced that Curve has launched on the Stellar mainnet, marking its first non-EVM native deployment. The StableSwap feature is now available, enabling users to permissionlessly create liquidity pools, swap assets, and provide liquidity. Curve founder Michael Egorov stated that the expansion to non-EVM chains is partially driven by institutional demand, adding that Stellar is relatively aligned with existing EVM usage habits. The project also plans to roll out FXSwap after an audit is completed, though no timeline has been provided. According to DeFiLlama data, Curve’s current total value locked stands at approximately $1.27 billion.

10 minutes ago

Nearly $30 million in long positions poured into HYPE within half an hour.

Intercontinental Exchange (ICE), parent company of the New York Stock Exchange, plans to launch a Hyperliquid-based perpetual futures market in the U.S. Following the news, HYPE saw a short-term rally, with large on-chain accounts building up positions en masse. According to TradingBeats' monitoring, within about half an hour after the announcement, 12 verified whales opened or rebuilt HYPE positions worth over $1 million each. Of these, 9 long positions totaled around $29.3173 million, while 3 short positions totaled around $8.0435 million, resulting in a long-to-short position value ratio of approximately 3.64:1, with a long net exposure of about $21.2738 million. The ratio of long to short accounts in this group is 3:1, with long positions accounting for roughly 78.47% of the total bilateral positions. The weighted average entry price for long positions is around $83.04, and for short positions around $82.86. Notably, an address starting with 0x9e2c opened a long position of 150,000 HYPE tokens, with an average entry price of approximately $82.47, a position value of about $12.7536 million, an unrealized profit of around $383,500, accounting for roughly 43.5% of the total long positions in this group.

10 minutes ago

Cartesia upgrades H-Net: Enables large models to autonomously learn data segmentation, boosting training efficiency by up to around 10 times.

Insight Beating AI Flash Briefing: Large language models can now learn language independently, but how text is split into tokens is usually determined by pre-trained tokenizers. This saves computing power, yet also constrains how models structure information. Fixed segmentation rules often fall short for unfamiliar words or code; skipping tokenization entirely to process raw bytes directly, however, leads to a sharp rise in computing costs. AI voice firm Cartesia introduced H-Net (Hierarchical Network) in July 2025 to resolve this tradeoff. The framework lets models read raw bytes directly and learn to segment and compress information autonomously. For example, an unfamiliar word may initially split into multiple segments; as it appears repeatedly in context, it gradually merges into fewer segments. This adjustment can occur during inference, with no retraining required. Cartesia has now unveiled a new H-Net version, with notable gains in training efficiency. In experiments with strictly controlled key conditions, computing power needed to hit the same validation loss dropped by ~22%, and computational efficiency for downstream evaluations nearly doubled. In larger-scale trials, the new H-Net matched the average score of open-source model SmolLM3 (trained on ~11 trillion tokens) across six tests using only ~1 trillion token-equivalent data, requiring roughly one-tenth the training compute of SmolLM3. This approach is not limited to text: the team trained H-Net on bacterial and archaeal genomes, finding that when processing human gene fragments, the model could automatically recognize the pattern of grouping every three bases in coding regions. Related DNA modeling experiments saw a 6–7x boost in computational efficiency. Unlike text, speech has no pre-defined word boundaries. Cartesia’s initial H-Net research was actually aimed at enabling voice models to learn phonemes and words directly from continuous audio, without relying on pre-designed segmentation rules.

10 minutes ago

HYPE continues its rally, rising more than 7% in the past hour.

According to HTX market data, HYPE continues its rally, surging over 7% in the past hour and currently trading at $85.2840. Earlier reports noted that Intercontinental Exchange (ICE), parent company of the New York Stock Exchange, plans to collaborate with Trade.xyz to introduce perpetual contract products into regulated U.S. markets.

10 minutes ago

A crypto whale opened a new crude oil long position worth approximately $18 million, and has racked up $15 million in losses recently.

According to TradingBeats monitoring, over the past two hours, a whale wallet starting with 0x30a opened a new long position in CL crude oil worth approximately $17.9554 million at an average price of $100.9, using 10x isolated leverage. The position currently has an unrealized profit of around $69,300, with a liquidation price of ~$93.19, roughly 8.07% below the current market price. The account’s equity stands at about $2.8723 million; its combined long positions in crude oil and Microsoft total around $28.846 million, with an overall leverage ratio of roughly 10.04x. Crude oil accounts for 62.45% of total holdings, while the remaining portion is a Microsoft long position worth approximately $10.832 million. Fund records show that between October 26 and 27, the account received two transfers totaling ~2.0312 million USDC from the same address. The profit curve indicates its overall net loss over the past month is around $14.9545 million. Before shifting to crude oil, the whale took profits on its long positions in Western Digital and Intel this morning after their earnings reports, generating a total trading profit of about $714,200; additionally, part of its Google long position was liquidated, leading to a total net loss of roughly $590,000 upon exiting those positions.

10 minutes ago

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