David Sacks回应中国AI模型Kimi K3登顶代码评测：美国监管束缚或削弱竞争力
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David Sacks strongly supports Palantir CEO's criticism of AI labs: True enterprise AI security lies in controlling one's own data, models, and computing power.
According to Beating, David Sacks, co-chair of the U.S. President's Council of Advisors on Science and Technology, published an article supporting Palantir CEO Alex Karp's sharp criticism of cutting-edge AI labs, stating that the mainstream media's portrayal of his interview as a "disastrous outburst" precisely demonstrates that Karp hit the nail on the head. Sacks points out that true "AI security" in a corporate environment is not abstract "alignment research" or government-led certification systems, but rather the ability to control one's own data, model weights, and computing power—preventing cutting-edge labs from "absorbing" a company's proprietary knowledge and turning it into the next product. He quotes Karp as saying, "They want to own their means of production, not hand them over to others." Sacks cites the conflict between Figma and Anthropic as a prime example: three days before the release of Claude Design, Anthropic's Chief Product Officer was still a member of Figma's board of directors, and Figma's founder stated that Anthropic "hadn't always been honest with them"; subsequently, Figma's stock price plummeted while Anthropic's valuation soared. He further listed products such as Claude Science, Claude Security, Claude Legal, and Claude Code, pointing out that Anthropic consistently targets vertical sectors originally served by companies that relied on its models, following a consistent pattern: "Observe where value is created first, then jump in." Sacks believes that the perception of open-source models as "dangerous" is not true for companies—retaining choice at the model layer and deciding who can use their core strengths is the real bottom line for corporate security. Previously, Palantir partnered with NVIDIA to deploy Nemotron's open AI models in sovereign environments, serving the US government and critical infrastructure customers, helping organizations train and deploy AI locally while maintaining complete control over data and intellectual property. Palanitir CEO Alex Karp recently gave a scathing interview on CNBC's "Squawk Box," criticizing leading AI model companies as "completely wrong" in their approach to selling AI. Karp emphasized that companies are currently dissatisfied with "cutting-edge labs" like OpenAI and Anthropic, believing they only pursue token maximization, wasting companies' time and money while handing over proprietary value and intellectual property. Karp stated that companies are "angry" and will strive to own their own AI production resources rather than relying on third parties. On June 29th, Palantir partnered with Nvidia to deploy Nvidia Nemotron open AI models in a sovereign environment, primarily serving the US government and critical infrastructure.
David Sacks responds to Anthropic “security controversy” triggering regulation: The core issue is the unpatched vulnerabilities.
Odaily Odaily reports that David Sacks, co-chair of the U.S. President's Council of Advisors on Science and Technology, responded to the regulatory crackdown on Anthropic due to its "security controversy." He stated that he has communicated with various parties regarding the current situation of Anthropic and summarized that the core of the current incident lies in the security controversy caused by its newly released model "Fable" (a commercial version of the Mythos-like model). Although Anthropic stated in its public statement that the vulnerability is "not serious," the U.S. government and the testing parties disagree with this assessment, believing that it is sufficient to affect the security of the model and even involves the risk of "cyber weapon operability." David Sacks further criticized Anthropic, stating that while it has consistently emphasized "security first," this time it seems more inclined to maintain the consumer version's continued availability rather than prioritizing security fixes. He argued that this matter should not be confused with other previous defense or regulatory controversies, adding that the US government still recognizes Anthropic's technical capabilities and that the current issue "could have been resolved quickly; the initiative was with Anthropic."
ByteDance Seed 2.1 Pro preview released: Breaking into the top eight front-end developers on Code Arena, closing in on Claude Opus 4.6
According to Beating's monitoring, the benchmark platform Arena.ai officially released the evaluation results of ByteDance's unreleased new model, Seed 2.1 Pro Preview. In the Code Arena: Frontend benchmark test, which specifically evaluates AI's ability to build real-world web applications and collaboratively modify multiple files, the model ranked 8th globally with a score of 1539, comparable to Anthropic's flagship model, Claude Opus 4.6. The model demonstrated exceptional strength in React development and front-end UI interaction design, ranking in the top 10 globally in 5 out of 7 subcategories (including 7th in React, 14th in HTML, 6th in Brand & Marketing, 9th in Content Creation Tools & Data Analysis, and 10th in Reference-Based Design & Consumer Products). In these strong areas, only a very few top models, such as Anthropic's Claude series and Zhipu AI's newly open-sourced GLM-5.2, outranked it. According to official sources, Seed 2.1 Pro will be officially released to the public in the coming weeks. This is ByteDance's latest progress in the fields of code generation and intelligent agent construction, following the launch of Seed 2.0 Pro in mid-February this year.
Kimi releases and open-sources its programming model, Kimi-K2.7-Code.
According to Foresight News , Kimi (the Dark Side of the Moon) has released and open-sourced its latest programming model, Kimi-K2.7-Code. Compared to K2.6, this model offers a 21.8% performance improvement on Kimi Code Bench v2, an 11.0% improvement on Program Bench, and a 31.5% improvement on MLS Bench Lite. It also reduces inference token usage by 30% and improves instruction compliance and end-to-end success rate for long-chain programming tasks. The model is now available through the Kimi API and Kimi Code, with a 6x faster mode coming soon. On the same day, Kimi also launched the Kimi Code Beta program, allowing users to apply for early access to unreleased models and features.
Code Arena: Alibaba's 1000 Questions 3.7 programming capabilities surpass GPT and Gemini, second only to the Claude series.
According to Mars Finance, on the morning of May 26, the global third-party programming leaderboard Code Arena released its rankings. Alibaba's latest flagship model, Qwen3.7-Max, scored 1541, surpassing models such as GPT-5.5 and Gemini-3.5-Flash, and ranking second only to the Claude series among major model manufacturers worldwide.
The Dark Side of the Moon rewrites the terminal intelligent agent and renames it kimi-code, fully aligning it with the Claude Code architecture.
According to Beating's monitoring, kimi-cli, an open-source terminal AI coding agent under Moonlit Dark Side, is quietly undergoing a repository migration and architecture rewrite, and has been officially renamed kimi-code. To address the bottlenecks in interactive response and execution efficiency of the original Python version, the development team fully adopted the technical approach of Anthropic's terminal tool Claude Code, completing a complete architecture refactoring based on TypeScript and the Bun runtime, achieving millisecond-level cold start and a smooth terminal user interface (TUI). This architectural adjustment signifies that Kimi has completely abandoned its original Python terminal technology stack, fully aligning with and introducing Claude Code's mature solution. The tool uses the Commander.js standard command parsing and replaces Rich and prompt-toolkit with React Ink to implement a brand-new responsive TUI interface. The refactoring involves 166 TypeScript source files, with a code increment of over 38,000 lines. In the SWE-bench Verified benchmark test, the TypeScript refactored version based on the kimi-k2.5 model successfully solved 317 out of 500 development tasks (63.4% resolution rate). While maintaining the performance level of the original Python version, its operational stability and network layer anti-interference capabilities were significantly improved. In addition to benchmarking the underlying architecture, kimi-code has focused on refining the human-computer collaboration experience. The new version not only supports dragging and dropping video assets such as screen recordings into the terminal for multimodal analysis, but also deeply replicates several benchmark designs from Claude Code, including a "planning mode" supporting cursor-interactive editing, commonly used Emacs shortcuts, a safe design for quick exit with double-clicking Ctrl + C, and support for connecting to automated workflows through custom lifecycle hooks. Regarding multi-model ecosystem compatibility, kimi-code allows for custom integration of third-party large model APIs, making the tool not only limited to the Kimi family but also usable as a unified terminal programming gateway across models.