Sad Frederick Schnook
981 posts

Sad Frederick Schnook
@FrederickS92254
Bio? I don't need a stinkin' bio


Apple is behaving in a manner that makes it impossible for any AI company besides OpenAI to reach #1 in the App Store, which is an unequivocal antitrust violation. xAI will take immediate legal action.



Alibaba’s upgraded Qwen3 235B Thinking 2507 is now the leading open weights model, beating DeepSeek R1 0528 on the Artificial Analysis Intelligence Index! Qwen3 235B 2507 (Reasoning) has jumped from the original Qwen3’s score of 62 to 69 in the Artificial Analysis Intelligence Index. This positions @Alibaba_Qwen's Qwen3 235B 2507 (Reasoning) one point above DeepSeek R1 0528: we would describe the new Qwen3 and R1 0528 as roughly equivalent in intelligence. Qwen3 235B 2507 sits only 1 point behind Gemini 2.5 Pro, o3 and o4-mini (high). Breakdown of the model’s improvement: 🧠 Intelligence increases across the board: Biggest jumps seen in LiveCodeBench (Code generation, +17 points), AIME 2024 (Competition Math, +10 points), GPQA Diamond (Scientific Reasoning, +9 points) with smaller gains across MATH-500 (Quantitative Reasoning, +6 points) and HLE (Reasoning & Knowledge, +3 points) ⚙️ Reasoning only model: Qwen3 235B 2507 (Reasoning) is a reasoning model (it is trained to ‘think’ before it answers). All of the initial release Qwen3 models were hybrid reasoning models that could be toggled to ‘think’ before answering - this version is no longer a hybrid model 🗯️ Increased token usage: Qwen3 235B 2507 (Reasoning) used 110 million tokens to run Artificial Analysis Intelligence, ~50% more than the 74 million tokens used by the original release of Qwen3 235B (Reasoning). It is equivalent to Grok4 usage and higher than DeepSeek R1 0528 (99M), Gemini 2.5 Pro (97M), o4-mini (high) (72M) and o3 (45M) 🇨🇳 China continues to lead the open-source AI race: with this release the top 3 open weights models in the world are all from Chinese labs. Key model details: ➤ Context window: 256K (May 2025 release supported 131K maximum) ➤ Total parameters: 235B (requires a minimum of ~500GB memory to run in native BF16 precision, can be run on 8xH100 node or more comfortably on an 8xH200 node) ➤ Active parameters: 22B ➤ Native BF16 training with an FP8 variant also made available by Alibaba ➤ Text only - no multimodal inputs or outputs ➤ Apache 2.0 License

Fuck Israel.






















I am going to get canceled once this hits the socialists who will ignore the fraud part to defend having multiple jobs. It was good knowing you all. 🫡 Didn’t expect it to leave tech.












