From 51 items, 7 important content pieces were selected

1. Russia charges Telegram founder Pavel Durov with aiding terrorism ⭐️ 9.0/10
2. Firm covering $60M crypto losses from AI trade ⭐️ 9.0/10
3. Wall Street Giants Back Clarity Act ⭐️ 8.0/10
4. OpenAI Report: AI Agents Accelerate Scientific Computing ⭐️ 8.0/10
5. Ionic Digital surges 26% on Nasdaq debut ⭐️ 7.0/10
6. Mythos Preview Uses Chain-of-Thought to Discover AES Möbius Bridge ⭐️ 7.0/10
7. Claude AI identifies cryptographic weaknesses ⭐️ 7.0/10

Russia charges Telegram founder Pavel Durov with aiding terrorism ⭐️ 9.0/10

Russia has formally filed terrorism-related charges against Telegram founder Pavel Durov, alleging that the platform facilitated terrorist activities. This legal action could severely impact Telegram’s operations in Russia and potentially worldwide, affecting millions of users who rely on the platform for private communications and cryptocurrency-related activities. The charges specifically cite aiding terrorism and could lead to significant penalties including imprisonment, potentially forcing changes in Telegram’s privacy policies or its presence in Russia.

rss · CoinDesk · Jul 29, 17:10

Background: Telegram is a widely-used encrypted messaging app known for its strong privacy features, and it is particularly popular among cryptocurrency communities for enabling secure communications and hosting crypto-related channels. Pavel Durov, the founder, has been a vocal advocate for digital privacy and has resisted government pressure to grant backdoor access to user data.

Tags: #regulation, #privacy, #security, #geopolitics, #crypto

Firm covering $60M crypto losses from AI trade ⭐️ 9.0/10

A company that executed an AI-driven trade causing $60 million in cryptocurrency liquidations has announced it will fully compensate all affected users. This incident highlights the risks of AI-powered trading in volatile crypto markets, and the company’s decision to cover losses sets a precedent for accountability in automated trading. The trade reportedly triggered cascading liquidations across multiple exchanges, affecting leveraged positions in major cryptocurrencies like Bitcoin and Ethereum.

rss · CoinDesk · Jul 29, 14:03

Background: In cryptocurrency trading, liquidation occurs when a leveraged position is force-closed due to insufficient margin, often during rapid price movements. AI trading bots use algorithms to execute trades autonomously, analyzing market data and generating signals. While they can enhance efficiency, they also carry risks of unintended large-scale impacts, especially in illiquid markets.

Tags: #AI, #crypto liquidations, #trading, #risk management

Wall Street Giants Back Clarity Act ⭐️ 8.0/10

BlackRock, Fidelity, and other major Wall Street firms have publicly endorsed the Clarity Act, a U.S. bill that aims to establish a unified regulatory framework for digital assets. This endorsement signals strong institutional support for regulatory clarity, which could accelerate crypto adoption by traditional finance and reduce legal uncertainty for market participants. The Clarity Act (Digital Asset Market Clarity Act of 2025) is intended to delineate jurisdiction between the SEC and CFTC over the digital asset market, but it remains stalled in the Senate.

rss · CoinDesk · Jul 29, 00:08

Background: Currently, U.S. crypto regulations are fragmented, with no clear boundary between SEC and CFTC authority. The Clarity Act seeks to resolve this by creating a transparent and predictable regulatory framework, which would allow businesses to build compliance programs with confidence.

Tags: #regulation, #institutional adoption, #policy, #Clarity Act

OpenAI Report: AI Agents Accelerate Scientific Computing ⭐️ 8.0/10

OpenAI published a field report showing how scientists are using AI coding agents to modernize scientific computing, significantly speeding up software development and discovery in genomics and other fields. This demonstrates a practical, high-impact application of agentic AI beyond chatbots, potentially transforming how scientific research is conducted by automating complex coding tasks. The report focuses on real-world use cases in genomics, where AI agents handle tasks like pipeline development and data analysis, reducing development time from months to days.

rss · OpenAI Blog · Jul 29, 01:00

Background: Agentic AI refers to AI systems that can autonomously pursue goals, use tools, and take actions within defined constraints. AI coding agents are a specific type that can write, debug, and optimize code, enabling researchers to focus on higher-level scientific questions rather than routine programming.

Tags: #AI, #scientific computing, #agentic AI, #genomics, #OpenAI

Ionic Digital surges 26% on Nasdaq debut ⭐️ 7.0/10

Ionic Digital, a bitcoin miner formed from Celsius Mining assets, began trading on the Nasdaq via a direct listing on July 28, 2026, under ticker IOND, and its shares jumped 26% on the first day. This provides Celsius Network claimholders with a liquid exit route to sell shares they received as part of the bankruptcy settlement, potentially recovering value from their claims. The reference price was set at $53, and the stock opened at $66.80, giving Ionic Digital a market capitalization of approximately $2.5 billion. The company was created from Celsius Mining, a subsidiary of the bankrupt Celsius Network.

rss · CoinDesk · Jul 29, 17:22

Background: Celsius Network filed for bankruptcy in July 2022 after freezing customer withdrawals. As part of its restructuring plan, Celsius Mining assets were spun off into Ionic Digital, and shares were distributed to claimholders. Ionic Digital’s direct listing on Nasdaq allows those shares to be traded publicly, providing a means for creditors to exit.

Tags: #Celsius, #Ionic Digital, #IPO, #Nasdaq, #Crypto Mining

Mythos Preview Uses Chain-of-Thought to Discover AES Möbius Bridge ⭐️ 7.0/10

Anthropic revealed that its Mythos Preview model employed chain-of-thought reasoning to uncover the AES Möbius Bridge, a novel algebraic structure in the AES S-box that enables faster cryptanalysis. The discovery led to up to 800x speedup in 7-round AES-128 meet-in-the-middle attacks. This demonstrates that advanced AI models can autonomously discover complex mathematical structures, advancing both AI reasoning and cryptographic analysis. It could lead to stronger defenses or improved attacks on AES. The AES Möbius Bridge is an invariant fingerprint that exploits the algebraic structure of the AES S-box, eliminating a 256-way guessing step. Mythos Preview’s chain-of-thought process allowed it to derive this bridge without human guidance.

rss · Anthropic News · Jul 29, 01:28

Background: The Advanced Encryption Standard (AES) is a widely used symmetric encryption algorithm whose security depends on the S-box, a nonlinear substitution component. Chain-of-thought reasoning is a technique where AI models break down complex problems into step-by-step reasoning, enhancing their problem-solving abilities. The Möbius Bridge refers to a mathematical structure that reveals weaknesses in AES’s algebraic design.

Tags: #AI, #cryptography, #chain-of-thought, #Anthropic, #research

Claude AI identifies cryptographic weaknesses ⭐️ 7.0/10

Anthropic has announced that its AI model Claude successfully identified novel attacks against cryptographic schemes submitted to international standardization efforts. The findings were reviewed and validated by human experts. This demonstrates that frontier AI systems can assist in discovering previously unknown cryptographic vulnerabilities, potentially accelerating security research and improving encryption standards. It highlights AI’s role in augmenting human expertise rather than replacing it. Claude identified attacks on cryptographic schemes that were part of international standardization efforts, not just trivial weaknesses. The research was conducted by Anthropic and the results were validated by human cryptographers.

rss · Anthropic News · Jul 29, 01:17

Background: Anthropic’s Claude is a large language model trained to be helpful, honest, and harmless. Cryptographic weaknesses are flaws in encryption algorithms that could be exploited by attackers. Traditionally, finding such weaknesses requires deep expertise and manual analysis. This research shows AI can assist in that process.

Tags: #AI Safety, #Cryptography, #Claude, #Security

From 63 items, 11 important content pieces were selected

1. Moonshot Releases 2.8T Parameter Kimi K3 Open-Weight Model ⭐️ 9.0/10
2. Morgan Stanley launches ETH, SOL exchange-traded products ⭐️ 8.0/10
3. Core Scientific signs AMD AI deal, exits bitcoin mining ⭐️ 8.0/10
4. Apple Sued Over Fake Bitcoin Wallet After $875K Theft on App Store ⭐️ 8.0/10
5. Coinbase to Suspend ACX Trading July 28, 2026 ⭐️ 8.0/10
6. First Implicit Tactile World Action Model Trained on 500k Hours of Video ⭐️ 8.0/10
7. World’s First Agentic Diffusion Model with 128K Context ⭐️ 8.0/10
8. A $500 RL Fine-Tune of 9B Open Model Beats Frontier Models ⭐️ 8.0/10
9. Anthropic Publishes Stance on Open-Weights AI Models ⭐️ 8.0/10
10. Documentation for self-contained Python builds ⭐️ 8.0/10
11. macOS Tahoe 26.6 Security Content Released ⭐️ 7.0/10

Moonshot Releases 2.8T Parameter Kimi K3 Open-Weight Model ⭐️ 9.0/10

Moonshot has released the weights for their 2.8 trillion parameter Kimi K3 model on Hugging Face, with the 1.56TB checkpoint now available under a new license that restricts commercial use by large Model-as-a-Service providers. OpenRouter already offers K3 from seven providers at the same pricing as Moonshot. This release represents a major milestone in open-weight AI, as a 2.8 trillion parameter model is among the largest ever made publicly available. The shift from a modified MIT license to a more restrictive one for large commercial entities may set a precedent for how future open-weight models balance openness with commercial protection. The new license for K3 requires Model-as-a-Service businesses exceeding $20 million in annual revenue to enter a separate agreement with Moonshot, whereas previous K2 license only required attribution for entities with over 100 million MAUs or $20M monthly revenue. Moonshot consistently uses the term ‘open weight’ rather than ‘open source’ to describe this release.

rss · Simon Willison · Jul 28, 07:39

Background: Model weights are the learned parameters that define how an AI model processes inputs to produce outputs, typically resulting from training on large datasets. In large language models, parameters include billions or trillions of adjustable values that encode the model’s knowledge and behavior. Open-weight models allow users to download and run the weights locally, but may come with usage restrictions that distinguish them from fully open-source software.

Morgan Stanley launches ETH, SOL exchange-traded products ⭐️ 8.0/10

Morgan Stanley is launching exchange-traded products (ETPs) for ether (ETH) and solana (SOL), following the success of its earlier bitcoin fund. This marks a significant expansion of its institutional crypto offerings. This move by a major traditional financial institution like Morgan Stanley signals growing institutional acceptance of cryptocurrencies beyond bitcoin. It could increase mainstream investor access and market legitimacy for ETH and SOL. The ETPs will provide exposure to ether and solana, allowing investors to trade them on traditional stock exchanges. The exact structure (ETF or ETN) and launch date have not been specified in the provided content.

rss · CoinDesk · Jul 28, 22:30

Background: Exchange-traded products (ETPs) are investment vehicles traded on stock exchanges that track an underlying asset. Morgan Stanley’s previous success with a bitcoin fund paved the way for expanding into other cryptocurrencies. Solana is a high-throughput blockchain platform known for fast transactions and low fees, while ether is the native token of the Ethereum network, the leading smart contract platform.

Tags: #institutional adoption, #ETP, #Morgan Stanley, #ether, #solana

Core Scientific signs AMD AI deal, exits bitcoin mining ⭐️ 8.0/10

Core Scientific has signed a deal with AMD to provide AI infrastructure, while simultaneously winding down its bitcoin mining operations. This marks a major strategic pivot for one of the largest Bitcoin miners, signaling a broader industry shift from crypto mining to AI compute. The deal involves Core Scientific’s data centers being repurposed for AMD GPU-based AI workloads, as the company phases out ASIC-based bitcoin mining.

rss · CoinDesk · Jul 28, 20:46

Background: Core Scientific was originally a major player in Bitcoin mining, operating large-scale data centers with specialized ASIC miners. However, the company has been shifting focus to AI and cloud services, leveraging its data center expertise. This deal with AMD solidifies that transition.

Tags: #bitcoin mining, #artificial intelligence, #Core Scientific, #AMD, #industry pivot

Apple Sued Over Fake Bitcoin Wallet After $875K Theft on App Store ⭐️ 8.0/10

A new lawsuit alleges that Apple kept a fake Bitcoin wallet on the App Store even after being notified of an $875,000 theft from a user. The lawsuit claims Apple was negligent in its app review process. This incident underscores critical security flaws in Apple’s App Store vetting for cryptocurrency wallets, directly causing significant financial losses. It raises urgent questions about platform liability and user protection in the crypto space. The fake wallet mimicked legitimate Bitcoin wallet apps and reportedly led to a theft of $875,000. Apple allegedly ignored reports from the victim and continued hosting the app for some time.

rss · CoinDesk · Jul 28, 19:59

Background: Fake crypto wallets are malicious apps designed to steal users’ cryptocurrency by providing a backdoor to fraudsters. Apple claims to review all apps for security, but this case shows that fraudulent apps can still bypass checks. Users often rely on App Store’s reputation for safety, making such incidents particularly damaging.

Discussion: No community comments were provided in the input.

Tags: #Security, #Apple, #Fake Wallet, #Lawsuit, #Bitcoin

Coinbase to Suspend ACX Trading July 28, 2026 ⭐️ 8.0/10

Coinbase announced it will suspend trading of the ACX token on July 28, 2026, as the project team is winding down the token and offering conversion options to holders. The exchange has already moved ACX order books to limit-only mode ahead of the suspension. This suspension removes a major trading venue for ACX, affecting liquidity and access for holders who wish to trade or exit their positions. It highlights the risks of token wind-downs and the importance of following project communications for conversion opportunities. Trading on Coinbase will be suspended from July 28 to August 3, 2026, and holders must move their ACX to a self-custodial wallet to participate in the project’s conversion options. The ACX token is used for governance, staking, and fee payments within the Across Protocol ecosystem.

rss · Coinbase Status · Jul 28, 15:00

Background: The ACX token is the native token of Across Protocol, a cross-chain bridge that allows token transfers between different blockchains. It is used for governance voting, staking to become a relayer, and paying transaction fees. A token wind-down occurs when a project decides to discontinue its token, often offering holders a conversion to another asset or stablecoins. Limit-only mode means traders can only place limit orders, not market orders, which is a common step before a full trading suspension.

First Implicit Tactile World Action Model Trained on 500k Hours of Video ⭐️ 8.0/10

Researchers have trained the first implicit tactile world action model using 500,000 hours of video, enabling AI systems to understand and simulate tactile interactions. This marks a significant step in embodied AI and multimodal learning, allowing robots to manipulate objects and interact with the environment more naturally, with profound implications for automation, healthcare, and home robotics. The model employs implicit representation learning, likely combining world models with tactile sensing data, and was trained on an enormous dataset of 500,000 hours of video. Specific architectural details have not been publicly disclosed, but this is the first attempt to integrate tactile sensing into a world model.

rss · QbitAI 量子位 · Jul 28, 13:25

Background: A world model is an internal simulation of the environment that allows AI to predict consequences of actions. Tactile sensing technology aims to replicate human touch. Previous world models relied primarily on visual and textual inputs, lacking the tactile modality.

World’s First Agentic Diffusion Model with 128K Context ⭐️ 8.0/10

Researchers have released the first agentic diffusion model capable of real-time action and error correction, achieving a 128K context length that matches autoregressive models. This breakthrough extends diffusion models to long-horizon agent tasks, potentially enabling more robust and interactive AI agents that can plan and adapt without full retraining. The model supports 128K token context, matching the context window of leading autoregressive models, and incorporates an agentic loop that iteratively refines outputs.

rss · QbitAI 量子位 · Jul 28, 12:18

Background: Diffusion models traditionally excel at generating high-quality images and audio by gradually denoising random noise. Autoregressive models have dominated long-context tasks like text generation and planning. This work bridges the gap by enabling diffusion models to handle agentic tasks requiring step-by-step decision-making and error correction.

A $500 RL Fine-Tune of 9B Open Model Beats Frontier Models ⭐️ 8.0/10

A team fine-tuned a 9 billion parameter open-weight model using reinforcement learning for under $500, achieving better performance on catalog review tasks than much larger frontier models like GPT-4 or Claude. This demonstrates that small, fine-tuned models can be highly cost-effective for specific tasks, challenging the economic rationale for massive frontier models and the associated infrastructure spending. The fine-tuning process utilized reinforcement learning to optimize the model for catalog review accuracy. The specific model, dataset, and exact training cost breakdown were detailed in the blog post, though the author notes potential overfitting concerns.

hackernews · ilreb · Jul 28, 10:18 · Discussion

Background: Reinforcement learning fine-tuning (RLFT) is a technique where a language model is trained to maximize a reward signal based on its outputs, aligning it with specific goals. Catalog review involves automatically evaluating product descriptions, metadata, or listings for quality and consistency. Frontier models like GPT-4 and Claude are very large, general-purpose models that are expensive to train and run.

Discussion: Commenters largely praised the cost-efficiency demonstration, with some noting that most use cases don’t need massive models. However, concerns were raised about overfitting due to lack of held-out test data and that such specialized benchmarks don’t accurately compare to frontier models’ generalized capabilities.

Anthropic Publishes Stance on Open-Weights AI Models ⭐️ 8.0/10

Anthropic published an official statement outlining its position on open-weights AI models, advocating for mandatory safety testing for all sufficiently capable models rather than a blanket ban. The statement clarifies that Anthropic has never called for banning open-weights models but emphasizes the need for regulation as capabilities advance. This statement fuels the ongoing debate between open and closed AI development, as open-weights models lower barriers to access but raise safety concerns. Anthropic’s position could influence regulatory policies, especially as governments consider how to balance innovation and risk. Anthropic’s CEO Dario Amodei wrote the statement, which also supports banning chip sales to China and cracking down on smuggling of chips to prevent advanced AI capabilities from proliferating. The statement explicitly opposes a ban on open-weights models but supports mandatory safety testing that critics argue could effectively function as a ban.

hackernews · surprisetalk · Jul 28, 06:03 · Discussion

Background: Open-weights AI models are neural network models whose trained parameters (weights and biases) are publicly released for anyone to download, modify, and run. This contrasts with closed models where only an API is accessible. The open-weights approach enables wider access and customization but also raises concerns about misuse, as developers cannot control how the model is used after release.

Discussion: Commenters largely criticized Anthropic for perceived hypocrisy, pointing out contradictions between supporting chip bans while opposing open-weights bans, and questioning the feasibility of safety testing regimes. Some accused Anthropic of virtue signaling and protecting its commercial interests under the guise of safety concerns.

Documentation for self-contained Python builds ⭐️ 8.0/10

Documentation for python-build-standalone, a set of self-contained portable Python distributions, has been published, detailing how these builds are used by tools like uv, pipx, and Hatch to provide Python installations without system dependencies. This infrastructure simplifies Python deployment across platforms, enables bundling Python into desktop applications, and reduces friction for users who need a specific Python version without system-level installation. The distributions are maintained by Astral (the company behind uv), support many platforms (Linux, macOS, Windows), and are available for multiple Python versions. They are designed to be fully relocatable and have no external dependencies.

hackernews · jcbhmr · Jul 28, 02:43 · Discussion

Background: Standard Python distributions are often tied to a specific operating system or require compiling from source. python-build-standalone provides pre-built, relocatable Python binaries that can be extracted and used anywhere, making them ideal for packaging tools like package managers or embedding in applications. They are produced using a custom build process that strips out system-specific baggage.

Discussion: Comments highlight widespread adoption: charliermarsh (uv lead) confirms uv uses these distributions and notes significant engineering effort in keeping up with CPython. simonw praises them as excellent for bundling Python into apps, and zie points out an alternative approach using Cosmopolitan cross-platform binaries. rsyring mentions PyOxy as a sister project that creates single-file executables from these distributions.

macOS Tahoe 26.6 Security Content Released ⭐️ 7.0/10

Apple released security content for macOS Tahoe 26.6, addressing multiple vulnerabilities including memory handling issues. This update is important for macOS users as it fixes critical vulnerabilities that could lead to sandbox escapes and code execution. It also highlights the ongoing challenge of memory safety in operating systems. The security content includes fixes for path parsing vulnerabilities and other issues, with many patches citing improved bounds checking and memory management.

hackernews · andor · Jul 28, 17:45 · Discussion

Background: macOS security updates are released periodically to fix vulnerabilities. Memory safety issues are common in systems programming languages like C and C++, leading to bugs such as buffer overflows. Apple’s updates often include improved memory handling to mitigate such risks.

Discussion: Commenters noted the high number of memory-related fixes, with some debating the monetary cost of using unsafe languages like C. Others observed a similar update for macOS 15 and questioned the prevalence of path parsing vulnerabilities.

Tags: #security, #macOS, #Apple, #vulnerabilities, #memory safety