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First @tedlieu. Now @RepGraceMeng. Both Taiwanese American Democrats. The racial cover isn't even subtle. Rep. Grace Meng calls the @nvidia chip sales a "five alarm fire" and demands full transparency. Fine. Let's start with her. Let voters see how the Washington machine really works. The checks: Three @AnthropicAI employees gave her $17,000 this cycle. The PAC of Americans for Responsible Innovation (@americans4ri) added $2,000. The same donors: Those same three Anthropic employees also funded ARI's PAC—$85,000 in total. One gave Meng $3,000, then nearly $1M to Public First, an AI super PAC network. The same operative: ARI and Public First share a founder: former Democratic congressman Brad Carson (@bradrcarson). Anthropic gave Public First Action $20M, and Dario Amodei (@DarioAmodei) added $1M of his own. The same agenda: Two days after the midterms, ARI led 52 groups urging Democrats to hand out committee chairs based on AI safety positions. The seat and power: With Democrats taking the House, ARI is pushing hard for Grace Meng to chair the Commerce, Justice, Science (CJS) Appropriations subcommittee— the panel that funds the Department of Commerce (@CommerceGov). Commerce runs AI chip export controls and @NIST's AI safety work: Anthropic's top two priorities in Washington. Now she's going after NVIDIA—Anthropic's fiercest rival on export controls—and Commerce, the very agency she'll fund. Same donors. Same operative. Same agenda. Same subcommittee. No law needs to be broken. Interests find power. Power finds interests. That's the five-alarm fire. The real one. Congresswoman, you asked for full transparency. Here it is.

😂白宫AI会结束，Dario面对记者那19秒我反复看了8遍。 眉毛乱跳、嘴角偷笑、眼神飘忽，最后还害羞地低头。 这不是Anthropic CEO，这是被校长叫去谈话后、出来还在消化“我们签了自我监管协议”的优等生。 安全派做到这个份上，谁还分得清他是在对齐人类，还是在对齐我的心动。 #DarioAmodei# #白宫AI会议# #Anthropic# #微表情名场面# #安全派也可以很可爱# #Claude#

The AI Business model trap: LLMs want cash flow to fund the race to AGI or the next model. Enter free consumer AI - they are losing a lot of money on the breadth of models to serve consumers for free! They are caught in the post training data trap, free consumer usage feeds post training needs, it can't be right to stop serving customers for free? But they need money for the compute: The monetization challenge is being pointed to Enterprises. Phase 1 - seemed easy, value capture in coding, the most bottom up motion in enterprise - with low customization per customer. Developers continue to train coding, tasks and eventually will train flawless skills. Phase 2 is where the challenge lies, showing true enterprise value. The promise of efficiency, accuracy, elimination of resources - that requires a different approach, build depth with harnesses, context, memory, solving for edge cases with deterministic guardrails! Build skill libraries - enter FDEs. Yes,FDEs will train the enterprise Waymos of the world. The risk - high token pricing for enterprises while consumers for free! Yes for consumer distribution businesses (aka Google, Meta, Apple, etc) it makes sense to hold on the distribution with free AI. If you want to win enterprise, you should be forward pricing tokens. The cheaper the tokens for enterprises it will allow for experimentation, workflow reimagination - instead CIOs are busy restricting AI use and working on making the use more efficient! Paradox: They still haven't fully understood and embraced the value of AI in the enterprise. If I were them: 1. Cut token pricing now, else send enterprises to secure opensource and end up with friction filled routing layers. 2. Show me how enterprises can use their context, training and data as their competitive advantage. 3. Build tools for rapid edge case learning and reducing false positives. @HarryStebbings @sama @DarioAmodei @demishassabis