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Topic: "model-comparison"
DeepSeek-R1-0528 - Gemini 2.5 Pro-level model, SOTA Open Weights release
deepseek-r1-0528 gemini-2.5-pro qwen-3-8b qwen-3-235b deepseek-ai anthropic meta-ai-fair nvidia alibaba google-deepmind reinforcement-learning benchmarking model-performance open-weights reasoning quantization post-training model-comparison artificialanlys scaling01 cline reach_vb zizhpan andrewyng teortaxestex teknim1 lateinteraction abacaj cognitivecompai awnihannun
DeepSeek R1-0528 marks a significant upgrade, closing the gap with proprietary models like Gemini 2.5 Pro and surpassing benchmarks from Anthropic, Meta, NVIDIA, and Alibaba. This Chinese open-weights model leads in several AI benchmarks, driven by reinforcement learning post-training rather than architecture changes, and demonstrates increased reasoning token usage (23K tokens per question). The China-US AI race intensifies as Chinese labs accelerate innovation through transparency and open research culture. Key benchmarks include AIME 2024, LiveCodeBench, and GPQA Diamond.
not much happened today
gpt-4.1 o3 o4-mini grok-3 grok-3-mini o1 tpuv7 gb200 openai x-ai google nvidia samsung memory model-release hardware-accelerators fp8 hbm inference ai-conferences agent-collaboration robotics model-comparison performance power-consumption sama
OpenAI teased a Memory update in ChatGPT with limited technical details. Evidence suggests upcoming releases of o3 and o4-mini models, alongside a press leak about GPT-4.1. X.ai launched the Grok 3 and Grok 3 mini APIs, confirmed as o1 level models. Discussions compared Google's TPUv7 with Nvidia's GB200, highlighting TPUv7's specs like 4,614 TFLOP/s FP8 performance, 192 GB HBM, and 1.2 Tbps ICI bandwidth. TPUv7 may have pivoted from training to inference chip use. Key AI events include Google Cloud Next 2025 and Samsung's Gemini-powered Ballie robot. The community is invited to participate in the AI Engineer World's Fair 2025 and the 2025 State of AI Engineering survey.
not much happened today
gpt-4.5 gpt-4 gpt-4o o1 claude-3.5-sonnet claude-3.7 claude-3-opus deepseek-v3 grok-3 openai anthropic perplexity-ai deepseek scaling01 model-performance humor emotional-intelligence model-comparison pricing context-windows model-size user-experience andrej-karpathy jeremyphoward abacaj stevenheidel yuchenj_uw aravsrinivas dylan522p random_walker
GPT-4.5 sparked mixed reactions on Twitter, with @karpathy noting users preferred GPT-4 in a poll despite his personal favor for GPT-4.5's creativity and humor. Critics like @abacaj highlighted GPT-4.5's slowness and questioned its practical value and pricing compared to other models. Performance-wise, GPT-4.5 ranks above GPT-4o but below o1 and Claude 3.5 Sonnet, with Claude 3.7 outperforming it on many tasks yet GPT-4.5 praised for its humor and "vibes." Speculation about GPT-4.5's size suggests around 5 trillion parameters. Discussions also touched on pricing disparities, with Perplexity Deep Research at $20/month versus ChatGPT at $200/month. The emotional intelligence and humor of models like Claude 3.7 were also noted.
OpenAI Voice Mode Can See Now - After Gemini Does
gemini-2.0-flash claude claude-3.5-sonnet llama-3-70b llama-3 mistral-large gpt-4o openai google-deepmind anthropic togethercompute scale-ai meta-ai-fair mistral-ai multimodality real-time-streaming roleplay prompt-handling model-comparison model-training creative-writing model-censorship code-execution developer-ecosystem ai-humor bindureddy
OpenAI launched Realtime Video shortly after Gemini, which led to less impact due to Gemini's earlier arrival with lower cost and fewer rate limits. Google DeepMind released Gemini 2.0 Flash featuring enhanced multimodal capabilities and real-time streaming. Anthropic introduced Clio, a system analyzing real-world usage of Claude models. Together Computing acquired CodeSandbox to launch a code interpreter tool. Discussions highlighted Meta's Llama 3.3-70B for its advanced roleplay and prompt handling abilities, outperforming models like Mistral Large and GPT-4o in expressiveness and censorship. The AI community also engaged in humorous takes on AI outages and model competition, with ChatGPT adding a Santa mode for holiday interactions. "Anthropic is capturing the developer ecosystem, Gemini has AI enthusiast mindshare, ChatGPT reigns over AI dabblers" was a noted observation from the community.
not much happened to end the week
gemini deepseek-r1 o1 chatgpt gpt-4 claude-3.5-sonnet o1-preview o1-mini gpt4o qwq-32b google-deepmind deeplearningai amazon tesla x-ai alibaba ollama multimodality benchmarking quantization reinforcement-learning ai-safety translation reasoning interpretability model-comparison humor yoshua-bengio kevinweil ylecun
AI News for 11/29/2024-11/30/2024 covers key updates including the Gemini multimodal model advancing in musical structure understanding, a new quantized SWE-Bench for benchmarking at 1.3 bits per task, and the launch of the DeepSeek-R1 model focusing on transparent reasoning as an alternative to o1. The establishment of the 1st International Network of AI Safety Institutes highlights global collaboration on AI safety. Industry updates feature Amazon's Olympus AI model, Tesla's Optimus, and experiments with ChatGPT as a universal translator. Community reflections emphasize the impact of large language models on daily life and medical AI applications. Discussions include scaling sparse autoencoders to gpt-4 and the need for transparency in reasoning LLMs. The report also notes humor around ChatGPT's French nickname.
not much happened today
gpt-4o claude-3.5-sonnet phi-3.5-mini phi-3.5-moe phi-3.5-vision llama-3-1-405b qwen2-math-72b openai anthropic microsoft meta-ai-fair hugging-face langchain box fine-tuning benchmarking model-comparison model-performance diffusion-models reinforcement-learning zero-shot-learning math model-efficiency ai-regulation ai-safety ai-engineering prompt-engineering swyx ylecun
OpenAI launched GPT-4o finetuning with a case study on Cosine. Anthropic released Claude 3.5 Sonnet with 8k token output. Microsoft Phi team introduced Phi-3.5 in three variants: Mini (3.8B), MoE (16x3.8B), and Vision (4.2B), noted for sample efficiency. Meta released Llama 3.1 405B, deployable on Google Cloud Vertex AI, offering GPT-4 level capabilities. Qwen2-Math-72B achieved state-of-the-art math benchmark performance with a Gradio demo. Discussions included model comparisons like ViT vs CNN and Mamba architecture. Tools updates featured DSPy roadmap, Flux Schnell improving diffusion speed on M1 Max, and LangChain community events. Research highlights zero-shot DUP prompting for math reasoning and fine-tuning best practices. AI ethics covered California's AI Safety Bill SB 1047 and regulatory concerns from Yann LeCun. Commentary on AI engineer roles by Swyx. "Chat with PDF" feature now available for Box Enterprise Plus users.
Gemma 2 tops /r/LocalLlama vibe check
gemma-2-9b gemma-2-27b llama-3 mistral-7b phi-3 qwen gemma llamaindex mistral-ai cohere deepseek-ai nous-research eureka-labs model-comparison local-llms multilinguality model-efficiency fine-tuning ai-education ai-teaching-assistants andrej-karpathy
Gemma 2 (9B, 27B) is highlighted as a top-performing local LLM, praised for its speed, multilingual capabilities, and efficiency on consumer GPUs like the 2080ti. It outperforms models like Llama 3 and Mistral 7B in various tasks, including non-English text processing and reasoning. The community discussion on /r/LocalLlama reflects strong preference for Gemma 2, with 18 mentions, compared to 10 mentions for Llama 3 and 9 mentions for Mistral. Other models like Phi 3 and Qwen also received mentions but are considered surpassed by Gemma 2. Additionally, Andrej Karpathy announced the launch of Eureka Labs, an AI+Education startup aiming to create an AI-native school with AI Teaching Assistants, starting with the LLM101n course to teach AI training fundamentals. This initiative is seen as a significant development in AI education.
Snowflake Arctic: Fully Open 10B+128x4B Dense-MoE Hybrid LLM
snowflake-arctic phi-3 llama-3-70b llama-3 stable-diffusion-3 sd3-turbo gpt-3.5-turbo snowflake databricks deepseek deepspeed nvidia stable-diffusion adobe apple llamaindex lmsys openai mixture-of-experts curriculum-learning model-release image-generation video-upscaling quantization inference-speed benchmarking model-comparison open-source on-device-ai
Snowflake Arctic is a notable new foundation language model released under Apache 2.0, claiming superiority over Databricks in data warehouse AI applications and adopting a mixture-of-experts architecture inspired by DeepSeekMOE and DeepSpeedMOE. The model employs a 3-stage curriculum training strategy similar to the recent Phi-3 paper. In AI image and video generation, Nvidia introduced the Align Your Steps technique improving image quality at low step counts, while Stable Diffusion 3 and SD3 Turbo models were compared for prompt understanding and image quality. Adobe launched an AI video upscaling project enhancing blurry videos to HD, though with some high-resolution artifacts. Apple released open-source on-device language models with code and training logs, diverging from typical weight-only releases. The Llama-3-70b model ties for first place on the LMSYS leaderboard for English queries, and Phi-3 (4B params) outperforms GPT-3.5 Turbo in the banana logic benchmark. Fast inference and quantization of Llama 3 models were demonstrated on MacBook devices.
Perplexity, the newest AI unicorn
llama-3-8b llama-3-70b llama-3 llava-llama-3-8b-v1_1 phi-3 gpt-3.5 perplexity-ai meta-ai-fair hugging-face groq context-length fine-tuning quantization instruction-following model-comparison multimodality benchmarking memory-optimization model-performance daniel-gross aravind-srinivas
Perplexity doubles its valuation shortly after its Series B with a Series B-1 funding round. Significant developments around Llama 3 include context length extension to 16K tokens, new multimodal LLaVA models outperforming Llama 2, and fine-tuning improvements like QDoRA surpassing QLoRA. The Llama-3-70B model is praised for instruction following and performance across quantization formats. Phi-3 models by Meta AI released in multiple sizes show competitive benchmark results, with the 14B model achieving 78% on MMLU and the 3.8B model nearing GPT-3.5 performance.
Multi-modal, Multi-Aspect, Multi-Form-Factor AI
gpt-4 idefics-2-8b mistral-instruct apple-mlx gpt-5 reka-ai cohere google rewind apple mistral-ai microsoft paypal multimodality foundation-models embedding-models gpu-performance model-comparison enterprise-data open-source performance-optimization job-impact agi-criticism technical-report arthur-mensch dan-schulman chris-bishop
Between April 12-15, Reka Core launched a new GPT4-class multimodal foundation model with a detailed technical report described as "full Shazeer." Cohere Compass introduced a foundation embedding model for indexing and searching multi-aspect enterprise data like emails and invoices. The open-source IDEFICS 2-8B model continues Google's Flamingo multimodal model reproduction. Rewind pivoted to a multi-platform app called Limitless, moving away from spyware. Reddit discussions highlighted Apple MLX outperforming Ollama and Mistral Instruct on M2 Ultra GPUs, GPU choices for LLMs and Stable Diffusion, and AI-human comparisons by Microsoft Research's Chris Bishop. Former PayPal CEO Dan Schulman predicted GPT-5 will drastically reduce job scopes by 80%. Mistral CEO Arthur Mensch criticized the obsession with AGI as "creating God."
Cohere Command R+, Anthropic Claude Tool Use, OpenAI Finetuning
c4ai-command-r-plus claude-3 gpt-3.5-turbo gemini mistral-7b gemma-2 claude-3-5 llama-3 vicuna cohere anthropic openai microsoft stability-ai opera-software meta-ai-fair google-deepmind mistral-ai tool-use multilingual-models rag fine-tuning quantum-computing audio-generation local-inference context-windows model-size-analysis model-comparison
Cohere launched Command R+, a 104B dense model with 128k context length focusing on RAG, tool-use, and multilingual capabilities across 10 key languages. It supports Multi-Step Tool use and offers open weights for research. Anthropic introduced tool use in beta for Claude, supporting over 250 tools with new cookbooks for practical applications. OpenAI enhanced its fine-tuning API with new upgrades and case studies from Indeed, SK Telecom, and Harvey, promoting DIY fine-tuning and custom model training. Microsoft achieved a quantum computing breakthrough with an 800x error rate improvement and the most usable qubits to date. Stability AI released Stable Audio 2.0, improving audio generation quality and control. The Opera browser added local inference support for large language models like Meta's Llama, Google's Gemma, and Vicuna. Discussions on Reddit highlighted Gemini's large context window, analysis of GPT-3.5-Turbo model size, and a battle simulation between Claude 3 and ChatGPT using local 7B models like Mistral and Gemma.
Welcome Interconnects and OpenRouter
mistral-large miqu mixtral gpt-4 mistral-7b mistral-ai openai perplexity-ai llamaindex qwen langchain model-comparison model-optimization quantization role-playing story-writing code-clarity ai-assisted-decompilation asynchronous-processing quantum-computing encoder-based-diffusion open-source hardware-experimentation rag-systems nathan-lambert alex-atallah
Discord communities analyzed 22 guilds, 349 channels, and 12885 messages revealing active discussions on model comparisons and optimizations involving Mistral AI, Miqu, and GGUF quantized models. Highlights include comparing Mistral Large with GPT-4, focusing on cost-effectiveness and performance, and exploring quantization techniques like GPTQ and QLORA to reduce VRAM usage. Advanced applications such as role-playing, story-writing, code clarity, and AI-assisted decompilation were emphasized, alongside development of tools like an asynchronous summarization script for Mistral 7b. The intersection of quantum computing and AI was discussed, including DARPA-funded projects and encoder-based diffusion techniques for image processing. Community efforts featured new Spanish LLM announcements, hardware experimentation, and open-source initiatives, with platforms like Perplexity AI and LlamaIndex noted for innovation and integration. Speculation about Mistral AI's open-source commitment and tools like R2R for rapid RAG deployment highlighted collaborative spirit.
MetaVoice & RIP Bard
mixtral nous-mixtral-dpo miqu-70b gpt-4 llama-2-70b-instruct llama-2 llama-2-70b llama-2-70b-instruct coqui metavoice google openai thebloke text-to-speech voice-cloning longform-synthesis prompt-engineering direct-preference-optimization lora-fine-tuning transformers gpu-acceleration apple-silicon content-authenticity metadata ai-censorship open-source-ai model-comparison usability model-limitations
Coqui, a TTS startup that recently shut down, inspired a new TTS model supporting voice cloning and longform synthesis from a small startup called MetaVoice. Google discontinued the Bard brand in favor of Gemini. On TheBloke Discord, discussions focused on AI training with models like Mixtral, Nous Mixtral DPO, and Miqu 70B, comparing them to OpenAI's GPT models, and debated prompt engineering, lorebooks, and removing safety features via LoRA fine-tuning on models such as Llama2 70B instruct. Technical topics included transformer layer offloading limitations and adapting LLaMa 2 for Apple Silicon. On OpenAI Discord, DALL-E images now include C2PA metadata for content authenticity, sparking debates on AI censorship, metadata manipulation, and open-source AI models versus commercial giants like GPT-4. Users discussed GPT-4 usability, limitations, and practical applications.
1/8/2024: The Four Wars of the AI Stack
mixtral mistral nous-research openai mistral-ai hugging-face context-window distributed-models long-context hierarchical-embeddings agentic-rag fine-tuning synthetic-data oil-and-gas embedding-datasets mixture-of-experts model-comparison
The Nous Research AI Discord discussions highlighted several key topics including the use of DINO, CLIP, and CNNs in the Obsidian Project. A research paper on distributed models like DistAttention and DistKV-LLM was shared to address cloud-based LLM service challenges. Another paper titled 'Self-Extend LLM Context Window Without Tuning' argued that existing LLMs can handle long contexts inherently. The community also discussed AI models like Mixtral, favored for its 32k context window, and compared it with Mistral and Marcoroni. Other topics included hierarchical embeddings, agentic retrieval-augmented generation (RAG), synthetic data for fine-tuning, and the application of LLMs in the oil & gas industry. The launch of the AgentSearch-V1 dataset with one billion embedding vectors was also announced. The discussions covered mixture-of-experts (MoE) implementations and the performance of smaller models.
12/22/2023: Anyscale's Benchmark Criticisms
gpt-4 gpt-3.5 bard anyscale openai microsoft benchmarking performance api prompt-engineering bug-tracking model-comparison productivity programming-languages storytelling
Anyscale launched their LLMPerf leaderboard to benchmark large language model inference performance, but it faced criticism for lacking detailed metrics like cost per token and throughput, and for comparing public LLM endpoints without accounting for batching and load. In OpenAI Discord discussions, users reported issues with Bard and preferred Microsoft Copilot for storytelling, noting fewer hallucinations. There was debate on the value of upgrading from GPT-3.5 to GPT-4, with many finding paid AI models worthwhile for coding productivity. Bugs and performance issues with OpenAI APIs were also highlighted, including slow responses and message limits. Future AI developments like GPT-6 and concerns about OpenAI's transparency and profitability were discussed. Prompt engineering for image generation was another active topic, emphasizing clear positive prompts and the desire for negative prompts.
12/21/2023: The State of AI (according to LangChain)
mixtral gpt-4 chatgpt bard dall-e langchain openai perplexity-ai microsoft poe model-consistency model-behavior response-quality chatgpt-usage-limitations error-handling user-experience model-comparison hallucination-detection prompt-engineering creative-ai
LangChain launched their first report based on LangSmith stats revealing top charts for mindshare. On OpenAI's Discord, users raised issues about the Mixtral model, noting inconsistencies and comparing it to Poe's Mixtral. There were reports of declining output quality and unpredictable behavior in GPT-4 and ChatGPT, with discussions on differences between Playground GPT-4 and ChatGPT GPT-4. Users also reported anomalous behavior in Bing and Bard AI models, including hallucinations and strange assertions. Various user concerns included message limits on GPT-4, response completion errors, chat lags, voice setting inaccessibility, password reset failures, 2FA issues, and subscription restrictions. Techniques for guiding GPT-4 outputs and creative uses with DALL-E were also discussed. Users highlighted financial constraints affecting subscriptions and queries about earning with ChatGPT and token costs.
12/16/2023: ByteDance suspended by OpenAI
claude-2.1 gpt-4-turbo gemini-1.5-pro gpt-5 gpt-4.5 gpt-4 openai google-deepmind anthropic hardware gpu api-costs coding model-comparison subscription-issues payment-processing feature-confidentiality ai-art-generation organizational-productivity model-speculation
The OpenAI Discord community discussed hardware options like Mac racks and the A6000 GPU, highlighting their value for AI workloads. They compared Claude 2.1 and GPT 4 Turbo on coding tasks, with GPT 4 Turbo outperforming Claude 2.1. The benefits of the Bard API for gemini pro were noted, including a free quota of 60 queries per minute. Users shared experiences with ChatGPT Plus membership issues, payment problems, and speculated about the upcoming GPT-5 and the rumored GPT-4.5. Discussions also covered the confidentiality of the Alpha feature, AI art generation policies, and improvements in organizational work features. The community expressed mixed feelings about GPT-4's performance and awaited future model updates.
12/15/2023: Mixtral-Instruct beats Gemini Pro (and matches GPT3.5)
mixtral gemini-pro gpt-3.5 gpt-4.5 gpt-4 chatgpt lmsys openai deepseek cloudflare huggingface performance context-window prompt-engineering privacy local-gpu cloud-gpu code-generation model-comparison model-usage api-errors karpathy
Thanks to a karpathy shoutout, lmsys now has enough data to rank mixtral and gemini pro. The discussion highlights the impressive performance of these state-of-the-art open-source models that can run on laptops. In the openai Discord, users compared AI tools like perplexity and chatgpt's browsing tool, favoring Perplexity for its superior data gathering, pricing, and usage limits. Interest was shown in AI's ability to convert large code files with deepseek coder recommended. Debates on privacy implications for AI advancement and challenges of running LLMs on local and cloud GPUs were prominent. Users reported issues with chatgpt including performance problems, loss of access to custom GPTs, and unauthorized access. Discussions also covered prompt engineering for large context windows and speculations about gpt-4.5 and gpt-4 future developments.