# Manipulation İlgili Makaleler

HTX Haber Merkezi, kripto endüstrisindeki piyasa trendleri, proje güncellemeleri, teknoloji gelişmeleri ve düzenleyici politikaları kapsayan "Manipulation" hakkında en son makaleleri ve derinlemesine analizleri sunmaktadır.

Embodied Intelligence 'Gaokao' is Insanely Hard, Humans Score 100, Best Model Only 12.8

Embodied AI Faces a Daunting "Everest": New Benchmark Reveals Huge Gap Between Models and Humans A comprehensive new benchmark for robotic manipulation, RoboDojo, has been released, painting a stark picture of the current state of embodied AI. It serves as a unified evaluation platform covering both simulation and real-world robot tasks. The benchmark assesses five core capabilities: Generalization (adapting to new scenes/objects), Memory, Precision manipulation, Long-Horizon multi-step tasks, and Open semantic understanding. It includes 42 simulation tasks and 18 standardized real-world tasks across three dual-arm robot platforms. The results are sobering. In simulation, the best-performing generalist robot policy achieved an average success rate of only 8.80%. Performance in the real world was slightly higher but still low, with the top model succeeding 12.8% of the time on average. In stark contrast, human experts scored 76.03% in simulation and 100% in real-world tests. The benchmark highlights significant, uneven gaps in current models' abilities. While some excel in specific areas like visual recognition or simple actions, they struggle with reliability, especially in long-horizon tasks where errors accumulate and in open-ended semantic instructions. The low scores, particularly in real-world deployment with physical uncertainties like camera noise and contact dynamics, underscore that today's models are far from being robust, general-purpose operational robots. RoboDojo is more than just a ranking; it's an infrastructure designed for fair, reproducible comparison. Its companion system, XPolicyLab, standardizes the interface for different models to be evaluated. Maintained by an academic consortium without commercial ties, it aims to provide a community-wide "altitude meter" to track genuine progress toward reliable and generalizable robot manipulation.

marsbit07/08 11:49

Embodied Intelligence 'Gaokao' is Insanely Hard, Humans Score 100, Best Model Only 12.8

marsbit07/08 11:49

Behind ANSEM's 300% Weekly Surge: The Recovery and Traps of Solana Meme Coins

The meme coin ANSEM surged nearly 299% in a week, driving a resurgence in Solana-based meme token activity. Data from DeFiLlama shows Pump.fun's weekly DEX volume reached $5.33 billion, with July 4th marking the platform's first $1 billion daily volume since April. This revival saw a spike in new token launches and heightened trading activity, with memes again accounting for over 20% of Solana's weekly transaction volume. However, industry reports highlight significant risks. The average meme coin holding time has plummeted to around 100 seconds, and sophisticated bots often front-run retail investors, acquiring large portions of supply at launch before dumping. Research analyzing thousands of projects indicates widespread market manipulation, with a majority of top-gaining tokens showing signs of wash trading and pool manipulation. While meme coins effectively attract new users and generate hype for the Solana ecosystem, the current rally raises the critical question of whether this cycle can break free from the established pattern where late-arriving retail traders become exit liquidity for early bots and coordinated groups. The market's future trajectory hinges on whether the momentum can be sustained or if it will fade, leading traders back to major assets like SOL.

Foresight News07/08 11:09

Behind ANSEM's 300% Weekly Surge: The Recovery and Traps of Solana Meme Coins

Foresight News07/08 11:09

Robots Learn Operations by Watching Videos: Berkeley First to Bridge the Gap from Internet Videos to Real Dexterous Hand Deployment

UC Berkeley researchers introduce "Do as I Do," an end-to-end pipeline enabling robots to learn dexterous manipulation directly from everyday monocular RGB videos. The system overcomes key bottlenecks in scaling robot learning by first reconstructing 4D hand-object interactions from noisy web videos using a guided diffusion-based tracking method that outperforms existing approaches. It then robustly retargets these trajectories—which are often discontinuous or physically implausible—to a 22-DoF Sharpa Wave dexterous hand. The method incorporates a dynamics-aware optimizer with adaptive contact modeling and multi-stage refinement to handle trajectory noise, improving real-world retargeting success from 25% to 71%. Validated across 20 complex action categories (e.g., stirring, hammering, writing), the pipeline generated 500 executable trajectories and was successfully deployed at 50Hz on a dual-UR3e arm and dual-Sharpa Wave hand platform for 10 real-world tasks. The work establishes a crucial link, transforming the vast repository of human video data into actionable robot policies for anthropomorphic hands.

marsbit07/06 07:19

Robots Learn Operations by Watching Videos: Berkeley First to Bridge the Gap from Internet Videos to Real Dexterous Hand Deployment

marsbit07/06 07:19

Memecore reclaims $1, but these factors may cap the rally

Memecore (M) surged 54% in 24 hours, reclaiming the key psychological level of $1 and pushing its market cap back over $1 billion. Despite this rally, the broader memecoin sector underperformed Bitcoin, with market cap losses of 8.9% versus BTC's 2.9%. Skepticism persists due to the token's high valuation paired with thin on-chain liquidity, evidenced by an 80% price crash last week on only $21 million in volume. Past allegations of market manipulation and insider supply distribution further cloud its outlook. Technical analysis on the 1-day chart remains bearish, with key indicators like the Awesome Oscillator below zero. While price is back above $1, the $1.20-$1.30 zone—a former support area from late 2025—now presents a significant resistance barrier. Given the extreme volatility, accusations of manipulation, and persistent selling pressure, the summary advises traders to avoid buying. Speculative traders might watch the $1.20-$1.30 area for potential new sell-offs, while risk-averse participants are recommended to stay sidelined.

ambcrypto07/01 22:32

Memecore reclaims $1, but these factors may cap the rally

ambcrypto07/01 22:32

NVIDIA Team Enables Programming Agent to Take Over Real Robot Experiments, Achieves 99% Success Rate

NVIDIA's ENPIRE project demonstrates fully automated robotic research where AI agents, given only high-level goals, autonomously manage the entire loop—from literature search and code development to training, deployment, and hardware iteration—on a fleet of physical robots. The system achieves 99% success rates on dexterous real-world tasks like cable tying and peg sorting. Key insights include the discovery of a "physical scaling law" where more parallel robots speed up task resolution, and the observation that resetting an environment is often easier than the main task. The framework introduces metrics like Mean Robot Utilization (MRU) to measure efficiency, with robots often idle half the time, waiting for agent decisions. The long-term vision is a lab that runs autonomously, even without human oversight. The project will be open-sourced, allowing developers to build similar systems.

marsbit06/18 00:35

NVIDIA Team Enables Programming Agent to Take Over Real Robot Experiments, Achieves 99% Success Rate

marsbit06/18 00:35

For the First Time, Pure Human Video Pretrained VLA for Dexterous Manipulation: Deployable with Minimal Fine-Tuning Data

For the first time, a purely human-video-pretrained Vision-Language-Action (VLA) model for dexterous manipulation requires only a small amount of data for fine-tuning to achieve successful real-world deployment. Achieving human-level dexterous manipulation remains a core challenge in robotics. While multi-fingered hands offer hardware potential, Visual-Language-Action (VLA) models lag behind due to the high cost of collecting diverse, high-quality robot data. A novel framework, VITRA, developed by Microsoft Research Asia and Tsinghua University, addresses this by automatically transforming massive, unlabeled real-world human activity videos into a structured V-L-A training dataset. Key innovations include precise 3D hand motion annotation from monocular video, atomic action segmentation based on hand-speed minima, and automated instruction generation using VLMs combined with 3D trajectory visualization. This process created a massive dataset of 1 million clips. Pretrained exclusively on this human video data, the VLA model (combining a VLM backbone with a Diffusion Transformer action expert) demonstrates strong zero-shot hand motion prediction in unseen environments. Crucially, it requires minimal fine-tuning (~1.2k demonstrations) on real robot data to achieve high-success-rate dexterous manipulation tasks like grasping, placing, pouring, and sweeping on hardware like the Realman robot with the XHAND1 dexterous hand. The model shows exceptional generalization to novel objects and environments. The research also observes promising scaling behavior, where performance improves with more pretraining data, paving the way for more generalized embodied intelligence.

marsbit06/08 08:54

For the First Time, Pure Human Video Pretrained VLA for Dexterous Manipulation: Deployable with Minimal Fine-Tuning Data

marsbit06/08 08:54

Can a Hair Dryer Earn $34,000? Deciphering the Reflexivity Paradox in Prediction Markets

An individual manipulated a weather sensor at Paris Charles de Gaulle Airport with a portable heat source, causing a Polymarket weather market to settle at 22°C and earning $34,000. This incident highlights a fundamental issue in prediction markets: when a market aims to reflect reality, it also incentivizes participants to influence that reality. Prediction markets operate on two layers: platform rules (what outcome counts as a win) and data sources (what actually happened). While most focus on rules, the real vulnerability lies in the data source. If reality is recorded through a specific source, influencing that source directly affects market settlement. The article categorizes markets by their vulnerability: 1. **Single-point physical data sources** (e.g., weather stations): Easily manipulated through physical interference. 2. **Insider information markets** (e.g., MrBeast video details): Insiders like team members use non-public information to trade. Kalshi fined a剪辑师 $20,000 for insider trading. 3. **Actor-manipulated markets** (e.g., Andrew Tate’s tweet counts): The subject of the market can control the outcome. Evidence suggests Tate’sociated accounts coordinated to profit. 4. **Individual-action markets** (e.g., WNBA disruptions): A single person can execute an event to profit from their pre-placed bets. Kalshi and Polymarket handle these issues differently. Kalshi enforces strict KYC, publicly penalizes insider trading, and reports to regulators. Polymarket, with its anonymous wallet-based system, has historically been more permissive, arguing that insider information improves market accuracy. However, it cooperated with authorities in the "Van Dyke case," where a user traded on classified government information. The core paradox is reflexivity: prediction markets are designed to discover truth, but their financial incentives can distort reality. The more valuable a prediction becomes, the more likely participants are to influence the event itself. The market ceases to be a mirror of reality and instead shapes it.

marsbit04/25 03:21

Can a Hair Dryer Earn $34,000? Deciphering the Reflexivity Paradox in Prediction Markets

marsbit04/25 03:21

Contract Audit Passed, Thermometer Did Not: Polymarket's 'Physical Vulnerability' Moment

According to reports, an individual manipulated temperature sensors at Paris Charles de Gaulle Airport (LFPG) on April 6th and 15th, causing brief, anomalous spikes of over 3°C. These events were allegedly orchestrated to profit from corresponding low-probability bets on the prediction market Polymarket, turning a small investment into approximately $34,000. The French national meteorological service, Météo-France, filed a criminal lawsuit after discovering signs of physical tampering. The attack required minimal technical skill; the perpetrator reportedly used a battery-powered hairdryer to briefly heat the publicly accessible sensor. Polymarket’s market for Paris temperature settles based on the day's highest recorded temperature from a data chain that runs from the physical sensor to Météo-France, to Weather Underground, and finally to its smart contract. In response, Polymarket did not void the profits or make an official statement. It silently changed the data source for its Paris market from LFPG to Le Bourget Airport (LFPB), a location with similarly unprotected sensors. This incident highlights a critical vulnerability: while the smart contracts are audited and secure, the physical data sources feeding them remain exposed and easy to manipulate.

marsbit04/23 04:39

Contract Audit Passed, Thermometer Did Not: Polymarket's 'Physical Vulnerability' Moment

marsbit04/23 04:39

Spending $200 to Buy Stars, Scamming VCs Out of Tens of Millions: The Entire GitHub Fake Star Industry Exposed

A peer-reviewed study from Carnegie Mellon University (CMU) reveals that GitHub hosts approximately 6 million fake Stars, involving 18,600 repositories and 301,000 accounts, with AI/LLM projects being the largest non-malicious category for fake engagement. The fake Star market has exploded, with prices as low as $0.03 per Star. Research shows that venture capital firms, such as Redpoint Ventures, use GitHub Star counts as a key metric for evaluating startups, with median Stars at 2,850 for seed-stage funding. For less than $200, a project can artificially meet this threshold, distorting investment landscape. Over a dozen websites openly sell GitHub Stars, and fake Star activity saw explosive growth in 2024. AI-related repositories were among the most heavily affected. Despite GitHub’s policies against fake engagement, enforcement remains inconsistent: while 90% of flagged repositories were deleted, only 57% of involved accounts were suspended. The report highlights how purchased Stars can manipulate GitHub’s Trending algorithm and influence VC funding decisions, creating a cycle where artificial metrics attract real investment.

marsbit04/21 02:59

Spending $200 to Buy Stars, Scamming VCs Out of Tens of Millions: The Entire GitHub Fake Star Industry Exposed

marsbit04/21 02:59

Are Altcoins Soaring? Is the Bull Market Back?

Recent days have seen significant volatility in altcoins while Bitcoin remained relatively stable. Some low-market-cap tokens, with circulations under $20 million, surged by several hundred percent within days—without fundamental improvements, ecosystem breakthroughs, or new institutional inflows. This is not a true altseason. The Altseason Index stands at 34, and Bitcoin dominance is at 58.5%, indicating the market is still in a "Bitcoin season." The altcoin market cap has shrunk by ~40% since its peak in December 2024, falling to around $700 billion. This severe decline has made it cheaper for large holders to accumulate significant portions of circulating supply, enabling price manipulation. A case in point is SIREN, where a single entity allegedly controlled up to 88% of the circulating supply. Such concentration allows a small group to dictate price movements. Additionally, deeply negative funding rates (as low as -0.3% every 8 hours, annualized to -328%) force short sellers to pay high fees, accelerating liquidations and further fueling upward price spikes. On-chain activity, like a 97% weekly increase in BSC DEX volume, suggests excitement, but it is largely driven by existing capital, not new inflows. Institutional flows into altcoin ETFs (like those for Solana and XRP) have been weak or negative, indicating caution rather than rotation into altcoins. This rally is a signal of structural fragility, not broad bullish momentum. Until Bitcoin dominance falls significantly and new capital enters the altcoin space, these pumps are echoes of manipulation—not the return of a true bull market.

marsbit04/17 06:24

Are Altcoins Soaring? Is the Bull Market Back?

marsbit04/17 06:24

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