RT Rahul | Aerius Labs (@rahulghangas)LFG! S-Two is now accelerated and is performant on Apple Metal.Metal benchmarks are already beating highly optimized simd implementation for trace sizes as low as `log_n=17`, while still remaining competitive with smaller trace sizes.Major metal kernels implemented:– M31/QM31 field ops– Circle FFT / IFFT– FRI fold + decompose– Merkle (BLAKE2s) hashing– Quotient accumulation– Fiat–Shamir channel mix/draw– Constraint VM row eval– MLE folds + circle eval ...

Model Performance & Benchmarks - Gemini 3 surpasses previous Frontier models in benchmarks, demonstrating significant advancements in AI capabilities [1] - Gemini 3 achieves 458% with code execution and search on Humanity's last exam, compared to Gemini 25% Pro at 21%, Cloud Sonnet 45% at 13%, and GBT 51% at 265% [2] - On the Vending Bench benchmark, Gemini 3's net worth reached $547816%, significantly outperforming Cloud Sonnet 45% at $3800 [4] - Gemini 3 Deep Think scores 41% on Humanity's Last Exam, compared to Gemini 3 Pro at 375%, Claude Sonnet 45% at 13%, GPT5 Pro at 30%, and GPT 51% at 265% [9][10] - Gemini 3 Deepthink achieves 451% on Arc AGI2 visual reasoning puzzles, a 10x improvement over Gemini 25% Pro [12] Enterprise Applications & Features - Boxcom's benchmark shows a 22-point performance increase for Gemini 3 Pro versus Gemini 25% Pro, with scores of 85% and 63% respectively [6] - Industry subsets in Boxcom's benchmark show significant performance jumps: Healthcare and Life Sciences (45% to 94%), Media and Entertainment (47% to 92%), and Financial Services (51% to 60%) [6] - Gemini 3 excels in complex multi-step reasoning and task automation, as highlighted by Box's new benchmark [7] - Gemini 3 supports multiple modalities, including text, images, video, audio, and code, with a unique focus on video understanding [12] - Gemini 3 can analyze YouTube videos frame by frame, understanding the content in detail [13] Google Integration & New Products - Gemini 3 is integrated into Google Search, dynamically generating user interfaces based on user queries [17] - Google launched anti-gravity, a VS Code fork coding platform that supports Gemini models and other models like GPTOSS and Anthropic's Sonnet [20] - The updated Gemini app features Gemini Agent capability, enabling the AI to complete real tasks on the user's behalf and create dynamic UIs [24] Model Architecture & Specifications - Gemini 3 is a brand new foundation model, not a modification of a prior model [27] - The model accepts text, images, audio, and video files as inputs, with a token context window of up to 1 million and output tokens of 64000 [28] - Gemini 3 is a sparse mixture of experts model built on Google's custom TPU architecture for both pre-training and inference [28]

Five benchmarks can help you determine how well you're progressing toward financial goals. Here's what you need to measure to evaluate success. https://t.co/xJGUV3tDqu ...

Core Insights - S&P Global's CEO, Martina Cheung, will participate in J.P. Morgan's 2025 Ultimate Services Investor Conference on November 18, 2025, in New York, with a scheduled speaking time from 9:00 a.m. to 9:30 a.m. EST [1] - The conference session will be webcasted, and may include forward-looking information [1][2] - S&P Global provides essential intelligence to governments, businesses, and individuals, enabling informed decision-making across various sectors, including sustainability and energy transition [3] Company Developments - S&P Global has successfully completed the acquisition of ORBCOMM's Automatic Identification System (AIS) business, enhancing its capabilities in the market [5] - The company has added Robert Moritz to its Board of Directors, effective March 1, further strengthening its leadership [6]

Benchmarking Philosophy - Benchmarks are designed to build trust, not inflate numbers [1] - BNB Chain aims for transparent and representative benchmarks [1] Methodology - Benchmarks reflect how traders actually use the chain [1]

Transparency and Trust - BNB Chain emphasizes transparent and representative benchmarks to build trust [1] - Benchmarks reflect actual usage by traders on the BNB Chain [1] Benchmarking Focus - Benchmarks are designed to avoid inflating numbers [1]

Performance Metrics - Trading-focused chains' performance isn't solely defined by TPS (transactions per second) [1] - Benchmarks should mirror actual workloads like swaps, liquidity movements, and NFT mints [1] - BNB Chain designs transparent, representative benchmarks [1]

Benchmarking & Performance Evaluation - MLPerf and IO500 are trusted, third-party benchmarks that provide clarity for making informed decisions about AI and HPC infrastructure [1] - These benchmarks simulate real-world workloads to measure speed, scalability, and efficiency [1] - The session aims to equip decision-makers with the knowledge to evaluate storage solutions for AI and HPC environments confidently [1] Key Learning Objectives - Identify the most relevant benchmark results for AI & HPC decision-makers [1] - Understand what MLPerf and IO500 tests entail and their significance [1] - Translate performance and scalability metrics into tangible business outcomes [1] DDN's Position - DDN demonstrates leadership in AI performance, offering benefits to users [1] Expertise - The session features technical experts from DDN, including Joel Kaufman, Jason Brown, and Louis Douriez [1]

Model Performance & Benchmarks - GPT5 demonstrates varied performance across different reasoning effort configurations, ranging from frontier levels to GPT-4.1 levels [6] - GPT5 achieves a score of 68 on the artificial intelligence index, setting a new standard [7] - Token usage for GPT5 varies significantly, with high reasoning effort using 82 million tokens compared to minimal reasoning effort using only 3.5 million tokens [8] - LM Arena ranks GPT5 as number one across the board, with an ELO score of 1481, surpassing Gemini 2.5 Pro at 1460 [19][20] - Stage Hand's evaluations indicate GPT5 performs worse than Opus 4.1 in both speed and accuracy for browsing use cases [25] - XAI's Grok 4 outperforms GPT5 in the ARC AGI benchmark [34][51] User Experience & Customization - User feedback indicates a preference for the personality and familiarity of GPT-4.0, even if GPT5 performs better in most ways [2][3] - OpenAI plans to focus on making GPT5 "warmer" to address user concerns about its personality [4] - GPT5 introduces reasoning effort configurations (high, medium, low, minimal) to steer the model's thinking process [6] - GPT5 was launched with a model router to route to the most appropriate flavor size of that model speed of that model depending on the prompt and use case [29] Pricing & Accessibility - GPT5 is priced at $1.25 per million input tokens and $10 per million output tokens [36] - GPT5 is more than five times cheaper than Opus 4.1 and greater than 40% cheaper than Sonnet [39]

DeFi发展 - 可靠的基准实施可能会开启DeFi的下一次进化，摆脱投机驱动，转向结构化、可扩展和机构级基础设施[1]