GTA Mod Adds Flock Cameras—And Lets Players Destroy Them
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A Kansas City security researcher ran 31 million tests to teach a model how to paint camouflage for the algorithm age.
Flock's New AI Police Tool Can Track Drivers Without a Name or License Plate
The underlying code for "OS Investigate" has 69 preloaded AI prompts that turn Flock cameras into a super-charged surveillance system that identifies people by how they move.
SecondFi has released an update on the latest theft incident: "Isolation Mode" will be launched this week, and a secure wallet export function is planned for release next week.
PANews reported on July 8th that SecondFi, the Cardano wallet service provider, released an update on the latest theft incident, stating that an "isolation mode" will be launched this week, allowing users to check if their wallet address is involved in the incident and submit a support ticket. Next week, they plan to launch a secure wallet export function, providing a safer wallet migration path for users of different skill levels. SecondFi reiterated that it will provide potential asset recovery solutions for wallets confirmed to be affected through its process, expected to be through zero-knowledge proof-based recovery tools with defined eligibility and terms. The official statement also emphasized that they will not request private keys or seed phrase, and users should only operate through the official website support and designated checking tools.
Opinion: Open source models account for only 10% of enterprise large-scale model spending, but mature production environments will be dominated by open source models.
According to Beating's monitoring, while public opinion often touts that open-source large models are dominating everything, enterprise spending data presents the opposite picture. Jesse Zhang, co-founder and CEO of Decagon, an enterprise-level AI customer service platform, points out that the share of open-source models in total enterprise spending has now dropped to 11%. This decline stems from the fact that most enterprises' AI applications are still in the early, undefined exploratory stage, thus defaulting to reliance on closed-source models. However, he emphasizes that once application scenarios mature, open-source models will take over production environments with their advantages of extremely low latency and deep fine-tuning. In Decagon's own production environment, 90% of calls have already switched to open-source weighted models. The core driver of this transformation is interaction speed and customization capabilities, not cost savings. In customer service scenarios, a single conversation that takes 8 seconds to finish will completely destroy the product experience. Since leading closed-source labs do not allow fine-tuning of flagship models, and small closed-source models cannot be deeply customized, small-sized open-source models, through fine-tuning for specific tasks, have become the only option to support high-frequency real-time interactions. The future of enterprise AI will see a division of labor: leading closed-source labs will continue to dominate the exploration and discovery of new fields, while open-source weighted models will increasingly take over the actual production of mature businesses. Because model fine-tuning requires extremely high levels of data and talent, the migration from closed-source to open-source will be a slow process lasting several years, during which both will experience sustained growth.
Critini Analyst: The token price war has bottomed out; Chinese AI "open source" players are raising prices or shifting to closed source.
According to Beating's monitoring, Jukan, an analyst at Critini Research, stated that Chinese AI "open source" players are also raising prices or gradually shifting towards a more closed-source model. He believes the token price war in China has bottomed out. Zhipu, the platform behind GLM-5.2, has also raised its price multiple times this year. Large-scale model developers in China cannot ignore return on investment forever; open source does not equate to cheap API pricing. --------------------------------- Click the original link below to join Beating's AI news channel on Lark, monitoring global AI hotspots and news 24/7.
Keling AI secures nearly $3 billion in funding, setting a new record for the largest funding round for a global video model company.
On July 2nd, Kuaishou's video generation big data model, Keling AI, secured nearly $3 billion in funding, with a post-investment valuation expected to reach $18 billion. This funding round sets a new record for the largest funding round ever for a global video big data model company, marking the official start of its independent commercialization process. The round was jointly led by CPE Capital, Guofang Venture Capital, BlueFive, Tencent, Zhongguancun Science City Fund (joint venture capital), and CITIC Securities, with participation from dozens of leading institutions. It is understood that this round of financing brought together top-tier industry capital such as Alibaba Cloud and Baidu, with active participation from leading entertainment industry players such as Huace Film & TV and Mango Industry Investors (Houwei Capital).