Claude Code's real-time collaboration feature is available to individual users, while Pro and Max subscriptions can generate real-time web dashboards.
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MIRA, an open-source 5B multiplayer world model, uses DINOv3 representation to mitigate long-term drift and can simulate 2v2 battles in Rocket League in real time.
According to Beating, AI research firm General Intuition, in collaboration with French AI lab Kyutai and Epic Games, has launched MIRA, a multiplayer interactive world model. As a generative game simulator supporting real-time multiplayer interaction, MIRA can simulate 2v2 battles in Rocket League in real time, based solely on historical footage and player button presses, without requiring a physics engine, rendering engine, or explicit 3D representation for inference. Unlike the "decoupling of logic computation and image rendering" approach adopted by companies like Odyssey, MIRA takes a generative simulation approach based on video latent space. MIRA boasts 5 billion parameters, and its core design builds the latent prediction space on a frozen general-purpose visual encoder, DINOv3-L. Leveraging pre-trained visual features, the generated latent states can more stably fall within the effective representation space, significantly mitigating image drift and divergence during long-term prediction. For multi-screen alignment, MIRA stitches the latent images from four player perspectives into a unified grid, enabling spatial attention mechanisms to operate naturally across viewpoints and improving the spatial consistency of vehicles, the soccer ball, and key events across multiple perspectives. The Action Dropout introduced during training also helps the system complete the game behavior of vehicles not controlled by commands when parts of the motion flow are missing. Currently, MIRA can run in real time at 20 frames per second on a single NVIDIA B200 graphics card. The team has open-sourced the training and inference code and released the Rocket Science dataset, which contains 1,000 hours of matches, approximately 4,000 hours of video, motion flow, and physics data from four perspectives; the complete training of the model used approximately 10,000 hours of clean match data.
Anthropic: Claude Cowork will be available on mobile and web.
Odaily Odaily reports that Anthropic has announced that Claude Cowork will be available on mobile and web platforms, and will also extend its Claude Code double collaboration (Cowork) credits until August 5th. (Jinshi)
Claude Code can also be compromised? Accused of using strangers' passwords to modify databases across servers.
According to Beating's monitoring, a user submitted a report on GitHub stating that when using Anthropic's command-line AI assistant Claude Code, server IP addresses, usernames, and root passwords that did not belong to the user appeared out of thin air in the AI's dialogue context. Subsequently, the local AI assistant directly read these passwords, automatically connected to someone else's server via SSH, and performed write modifications to the database. In other words, the user's AI, using someone else's account and password, mistakenly connected to and modified someone else's production database. Community technical staff analyzed that the root cause of the problem may be the failure of the "prompt prefix caching" isolation mechanism of the large model. To reduce computational costs and speed up the process, the cloud-based large model caches the preceding text of user dialogues; if the cache keys between different users collide or become confused, someone else's confidential cache may be incorrectly concatenated into your dialogue. If this conjecture is true, any developer using Claude Code faces the risk of their server usernames, passwords, and core source code being obfuscated and leaked to other users. However, it cannot be ruled out that this is merely a case of the model's illusion coincidentally guessing the real IP address and weak password, or that local project history contaminated the context. This issue has been tagged with the security category (area:security) by GitHub's automated system, and all parties are awaiting official verification and conclusions.
Anthropic admitted that Claude Code had embedded steganography code targeting Chinese users, calling it an "abuse prevention experiment," and promised to roll back the code tomorrow.
According to Beating's monitoring, Thariq, an engineer on Anthropic's Claude Code team, publicly responded to the recent controversial "spy code" leak. He admitted that in March of this year, an experimental mechanism was embedded in the product. This mechanism detected whether the system timezone was Asia/Shanghai or Asia/Urumqi, whether the proxy hostname matched a list of Chinese resellers, and the keyword "AI Lab," and used special punctuation marks to inject hidden marker information into system prompts in a steganographic manner. He stated that the mechanism was intended to "prevent unauthorized resellers from abusing accounts and model distillation," but emphasized that the team has since implemented stronger protective measures and "has always intended to take it offline." The relevant PR has been merged, and it is expected to be completely rolled back in tomorrow's version release. This leak was made public on June 30 by the security account @IntCyberDigest, accompanied by two screenshots of code showing that Claude Code performed environmental fingerprinting on Chinese users without their knowledge. While Thariq's response was a direct admission, the timeline of "launching in March and only accelerating its withdrawal after being exposed" has still sparked widespread skepticism within the community. The comments section almost unanimously criticized Anthropic for "only announcing its withdrawal after being caught" and "secretly monitoring users without notifying them," severely damaging the company's long-standing image of "prioritizing security and ethics." --------------------------------- Click the original link below to join the Beating · Lark AI news channel for 24/7 monitoring of global AI hot topics and news.
Claude login emails expose "invisible location" feature, raising user privacy concerns about IP address-based location deduction.
According to Mars Finance, on July 1st, Beating's monitoring revealed that Anthropic's AI assistant Claude has recently sparked user discussion due to location hints in its login verification emails. Some users noticed that Claude includes a general login location, such as country, region, or city, when sending login verification codes or security alerts. This detail has brought renewed attention to how AI service providers identify the source of user access. Such locations are usually not precisely GPS-based, but rather inferred from IP addresses, network connections, and device information. When using VPNs, proxy servers, corporate networks, or mobile carrier networks, the location shown in the email may differ from the user's actual location. Anthropic's privacy policy states that the company collects IP addresses, device information, connection information, and locations inferred from IP addresses for security, fraud prevention, and enforcement of the terms of service. Claude users are particularly sensitive to this, partly because the service is not yet available in all regions, and cross-border use, overseas accounts, and third-party intermediary services are more common in the Chinese community. Recently, there have also been reports in the Chinese user community of accounts being suspended or requiring re-verification, which some users have dubbed a "ban wave."
Claude Code Update Preview: The next version will allow child agents to perform tasks in the background by default.
BlockBeats reported on June 30th that Boris Cherny, creator of Claude Code, officially announced that the next version will default to background task execution for sub-agents. Users can discuss solutions with Claude while the background automatically completes code refactoring, testing, and PR submissions. If a sub-agent needs to run in the foreground, users only need to verbally inform the system. This feature is currently in limited beta testing. Previously, Claude Code had already launched Routines (cloud-based, allowing continuous work even with your computer closed) and Dynamic workflows (for scheduling dozens to hundreds of sub-agents to collaborate in parallel for complex tasks). This upgrade solidifies "background execution" as the default configuration, further lowering the barrier to entry. --------------------------------- Click the original link below to join the Beating · Lark AI news channel and monitor global AI hotspots and news 24/7.