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Institutional Adoption of Prediction Markets Stuck at the Third Stage

Prediction markets are transitioning from niche platforms focused on elections and sports to mainstream financial tools, as highlighted at Kalshi Research's inaugural conference. While sports still dominate trading volume (around 80%), non-sports categories like macroeconomics, politics, and entertainment are growing faster, signaling a shift from entertainment-based trading to information and risk management tools. Institutions, including Wall Street firms, are increasingly using prediction markets for data reference (Stage 1 adoption), with some progressing to system integration (Stage 2). However, full-scale trading (Stage 3) is limited due to the lack of margin trading, requiring full collateral for positions—a barrier for leverage-dependent entities. Kalshi is working with regulators to introduce margin mechanisms. Key insights from participants like Goldman Sachs and CNBC emphasize the value of real-time pricing for events (e.g., Fed decisions, tariffs), providing benchmarks previously unavailable. The path to maturity mirrors historical financial instruments like options, with expectations that prediction markets will become institutional staples within five years. Political leaders, including Trump and Schumer, now cite Kalshi odds, underscoring its growing influence. The platform rewards domain expertise over traditional finance backgrounds, attracting diverse participants from fields like music and poker. Ultimately, prediction markets are evolving into critical infrastructure for pricing uncertainty.

marsbit2 дня назад 02:27

Institutional Adoption of Prediction Markets Stuck at the Third Stage

marsbit2 дня назад 02:27

Institutional Adoption of Prediction Markets Stuck at the Third Stage

Prediction markets are transitioning from niche platforms focused on elections and sports to mainstream tools for information and risk management. While events like the Super Bowl still dominate trading volume, non-sports categories—such as macroeconomics, politics, and entertainment—are growing faster and attracting institutional interest. Key drivers include the need for real-time benchmarks on uncertain events (e.g., election outcomes or policy changes), which traditional markets lack. Institutions like Goldman Sachs and CNBC are already using prediction market data for decision-making, though most remain in the early stages of adoption. The path to full institutional integration involves three phases: data integration, system compliance, and active trading. The current barrier to large-scale trading is the lack of margin trading, requiring full collateral for positions—a limitation platforms like Kalshi are working to address. Experts compare prediction markets to the early days of options trading, anticipating they will become a standard, if mundane, financial infrastructure. Political leaders and institutions are increasingly referencing these markets, signaling their growing credibility. The future lies in their evolution from speculative arenas to essential tools for hedging and pricing uncertainty.

Odaily星球日报2 дня назад 02:22

Institutional Adoption of Prediction Markets Stuck at the Third Stage

Odaily星球日报2 дня назад 02:22

Robotics' "ChatGPT Moment": AI Moves into the Physical World, Blockchain Accelerates the Arrival of the Machine Economy

The integration of AI and robotics is accelerating the shift from digital intelligence to physical AI, enabling machines to perceive, reason, and act in real-world environments. Companies like Figure, Tesla, and Skild AI are driving advancements in humanoid and specialized robots, supported by significant investments—such as Skild’s $14B and Figure’s $10B+ funding rounds. Key enablers include declining hardware costs (actuators, sensors, batteries), edge computing (e.g., NVIDIA Jetson), and AI "world models" that learn physical intuition from video data rather than programmed instructions. Despite progress, challenges remain: collecting real-world robotic training data is slow and costly, and simulation-to-reality gaps persist. Blockchain and tokenization offer solutions by incentivizing decentralized data contribution and enabling robots to function as economic agents—earning, spending, and distributing profits autonomously. By 2030, physical AI could transform industries and households, with robots operating via standardized platforms and skill-based "app stores." The convergence of affordable hardware, advanced AI, decentralized coordination, and edge compute promises a future where intelligent robots become ubiquitous assistants in daily life and high-risk applications.

marsbit2 дня назад 01:16

Robotics' "ChatGPT Moment": AI Moves into the Physical World, Blockchain Accelerates the Arrival of the Machine Economy

marsbit2 дня назад 01:16

Is SWIFT Integrating XRP For Payments? The Code Might Hold The Answer

Crypto pundit SMQKE has speculated that SWIFT may be integrating XRP for payments, citing code from the R3 Corda codebase that links XRP to ISO 20022 and SWIFT network. The code includes modules named XrpPayment and SWIFTPaymentStatusType, suggesting technical compatibility. While XRP is ISO 20022-ready, enabling potential connections with SWIFT-enabled institutions, SWIFT has not confirmed any integration. Currently, the only known link is through Ripple Treasury, a SWIFT connectivity partner, though SWIFT does not use XRP for payments. In related news, X (formerly Twitter) has added XRP to its cashtags feature, increasing its visibility. XRP is trading at around $1.40, up 3% in 24 hours.

bitcoinist04/16 22:02

Is SWIFT Integrating XRP For Payments? The Code Might Hold The Answer

bitcoinist04/16 22:02

Cardano Founder Says Bitcoin Has Entered ‘Shitcoin Land’

Cardano founder Charles Hoskinson criticized Bitcoin's governance and response to quantum computing threats in a livestream titled "BIP 361: Welcome to ShitcoinLand, Bitcoin." He argued that Bitcoin's resistance to change has left it vulnerable, with over 34% of all Bitcoin (approximately 8 million BTC) exposed to potential theft by quantum computers due to revealed public keys. Hoskinson claimed BIP 361's proposed solution—a hard fork to freeze non-migrated coins—would render around 1.7 million BTC, including Satoshi's estimated 1.1 million, unspendable due to outdated wallet formats. He contrasted Bitcoin's rigid culture with governance models in Cardano, Polkadot, and Ethereum, which he says offer better mechanisms for protocol upgrades. Hoskinson acknowledged the quantum threat as real but argued Bitcoin's ideological inflexibility complicates a effective response.

bitcoinist04/16 18:32

Cardano Founder Says Bitcoin Has Entered ‘Shitcoin Land’

bitcoinist04/16 18:32

Behind the MiniMax 'Pseudo-Open Source' Controversy: Has Yan Junjie's Ideal Succumbed to Capital Anxiety?

The article discusses the controversy surrounding MiniMax's "pseudo-open-source" release of its flagship M2.7 model. Initially presented as open-source, the model was later released under a "Modified-MIT" license that restricts commercial use without written permission, sparking backlash from the developer community. This move is seen as a departure from true open-source principles and reflects the tension between technological idealism and commercial pressures. MiniMax, which recently went public, faces significant financial challenges, with substantial losses despite growing revenues. The company’s decision to limit commercial use is interpreted as an effort to protect its revenue streams and control how its models are deployed, especially after instances of third-party misuse affected its reputation. The incident highlights a broader industry trend where "open-weight" models are increasingly distinguished from fully open-source ones, raising concerns about trust and legal certainty for developers and enterprises. The author concludes that MiniMax’s shift represents a pragmatic, if controversial, business strategy aimed at ensuring profitability, even at the cost of community trust.

marsbit04/16 11:01

Behind the MiniMax 'Pseudo-Open Source' Controversy: Has Yan Junjie's Ideal Succumbed to Capital Anxiety?

marsbit04/16 11:01

Apple Sends Siri Staff to AI 'Cram School', Jensen Huang's Bold Prediction Begins to Materialize

Apple is reportedly sending nearly 200 engineers from its Siri team to a multi-week AI programming "boot camp" to retrain them in AI-assisted coding, just two months before its major WWDC event. This unusual move reflects Apple's urgent effort to modernize Siri’s development process amid industry-wide shifts toward AI-powered tools like Claude Code and OpenAI’s Codex. The restructured Siri team now consists of only about 60 core developers, with another 60 assigned to test Siri’s performance and safety. The reshuffle follows internal delays in launching a new AI-powered Siri, originally planned for early 2025. Under new leadership—software chief Craig Federighi and hardware veteran Mike Rockwell—Apple is pushing to integrate Google’s Gemini model to power a more conversational, multi-step capable Siri. The situation underscores a broader trend: engineers who don’t adapt to AI tools risk being sidelined, as companies like Meta and NVIDIA emphasize AI-augmented productivity. While Apple’s retraining approach is relatively supportive compared to outright layoffs, it highlights how rapidly AI is reshaping tech roles—making traditional skills less relevant and accelerating a new industrial standard for software development.

marsbit04/16 10:48

Apple Sends Siri Staff to AI 'Cram School', Jensen Huang's Bold Prediction Begins to Materialize

marsbit04/16 10:48

No More Selling Shoes, Now Selling Computing Power: Will AI Computing Power Follow the Same Path as DAT?

Former footwear brand Allbirds announced a pivot to AI computing infrastructure under the name NewBird AI, raising $50 million and causing its stock to surge 582% in a single day. This shift echoes last year’s trend of companies rebranding as Digital Asset Treasuries (DATs), though the AI compute model differs significantly. The move highlights a structural shortage in AI computing power. Gartner projects global AI spending to reach $2.52 trillion by 2026, with over half dedicated to infrastructure. Major tech firms like Microsoft, Google, and Amazon are ramping up capital expenditures, yet supply remains constrained due to long GPU lead times and soaring demand from both training and inference workloads. Nvidia CEO Jensen Huang predicts a $1 trillion AI chip and infrastructure market by 2027. Unlike DAT companies—which held volatile crypto assets—AI compute firms rely on physical infrastructure, operational expertise, and long-term contracts that generate recurring revenue. However, analysts caution that Allbirds’ modest funding and lack of experience may signal “AI-washing,” akin to earlier blockchain hype. While the strategy offers a potential lifeline for struggling public companies, sustainable success requires genuine operational capability and significant investment.

Odaily星球日报04/16 10:21

No More Selling Shoes, Now Selling Computing Power: Will AI Computing Power Follow the Same Path as DAT?

Odaily星球日报04/16 10:21

After the Collapse of the Believe Flywheel Myth, the 26-Year-Old Prodigy Founder Stands as Defendant in Federal Court

In March 2026, 26-year-old Australian entrepreneur Ben Pasternak and his entities B24, Inc. and Believe Foundation were sued in a New York federal court. Investors accused Pasternak of deceptive practices and false advertising through three consecutive token offerings and a forced token migration, causing hundreds of millions in losses. The case centers on Believe (formerly Clout.me), a Solana-based social token launch platform Pasternak founded. Users could create tokens via tweets, with the platform token LAUNCHCOIN reaching a peak market cap of $370 million in May 2025. Pasternak initially claimed he had "zero ownership" of his self-named token, PASTERNAK, which crashed over 95% within a week. In October 2025, Believe forced a migration from LAUNCHCOIN to a new token, BELIEVE, increasing total supply by 33.3%. New tokens were allocated to team members, investors, and the foundation, diluting existing holders. Pasternak falsely claimed no tokens were allocated to insiders for a year, while the foundation received 40 million tokens with no lock-up. The platform generated an estimated $54 million in fees from $6 billion in trading volume. Pasternak earned creator fees throughout. After the migration, significant selling occurred from top wallets. BELIEVE’s value plummeted from its peak to around $1.2 million. Pasternak, a former teen prodigy who dropped out of school at 15, had previously founded apps like Monkey and the food-tech startup NUGGS. His personal life also drew attention, including a public breakup in early 2026. Once hailed as "the next Zuckerberg," he now faces legal and reputational collapse.

marsbit04/16 09:44

After the Collapse of the Believe Flywheel Myth, the 26-Year-Old Prodigy Founder Stands as Defendant in Federal Court

marsbit04/16 09:44

Ethereum’s Staking Ecosystem Evolves As Market Cap Expands Rapidly

With the cryptocurrency market turning bullish, Ethereum's staking ecosystem is experiencing explosive growth, reaching a record $85.2 billion in market capitalization. This surge reflects increased participation from both retail and institutional investors seeking yields while enhancing network security. Ethereum now commands more staked value than all other major blockchains combined, solidifying its position as the leading decentralized security budget and a trusted settlement layer for the global on-chain economy. Meanwhile, Ethereum's price has rebounded, reclaiming the $2,300 level—a key resistance point. However, analysts caution that the current uptrend resembles a bear market relief rally rather than a structural reversal. At the time of writing, ETH was trading around $2,319, with a slight decline in price and a 13% drop in trading volume. Despite short-term volatility, the foundation of Ethereum's staking economy remains stronger than ever.

bitcoinist04/16 09:07

Ethereum’s Staking Ecosystem Evolves As Market Cap Expands Rapidly

bitcoinist04/16 09:07

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