All tags
Topic: "roleplay"
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.
OpenAI Sora Turbo and Sora.com
sora-turbo o1 claude-3.5-sonnet claude-3.5 gemini llama-3-3-euryale-v2.3 mistral-large behemoth endurance-v1.1 openai google nvidia hugging-face mistral-ai text-to-video-generation quantum-computing coding-capabilities transformers algorithmic-innovation storytelling roleplay model-parameter-tuning anti-monopoly-investigation sama sundarpichai bindureddy denny_zhou nrehiew_
OpenAI launched Sora Turbo, enabling text-to-video generation for ChatGPT Plus and Pro users with monthly generation limits and regional restrictions in Europe and the UK. Google announced a quantum computing breakthrough with the development of the Willow chip, potentially enabling commercial quantum applications. Discussions on O1 model performance highlighted its lag behind Claude 3.5 Sonnet and Gemini in coding tasks, with calls for algorithmic innovation beyond transformer scaling. The Llama 3.3 Euryale v2.3 model was praised for storytelling and roleplay capabilities, with users suggesting parameter tuning to reduce creative liberties and repetition. Alternatives like Mistral-Large, Behemoth, and Endurance v1.1 were also noted. Additionally, Nvidia faces an anti-monopoly investigation in China. Memes and humor around GPU issues and embargo mishaps were popular on social media.
Stable Diffusion 3 — Rombach & Esser did it again!
stable-diffusion-3 claude-3 orca dolphincoder-starcoder2-15b stability-ai anthropic microsoft latitude perplexity-ai llamaindex tripo-ai diffusion-models multimodality benchmarking human-evaluation text-generation image-generation 3d-modeling fine-tuning roleplay coding dataset-release soumith-chintala bill-peebles swyx kevinafischer jeremyphoward akhaliq karinanguyen_ aravsrinivas
Over 2500 new community members joined following Soumith Chintala's shoutout, highlighting growing interest in SOTA LLM-based summarization. The major highlight is the detailed paper release of Stable Diffusion 3 (SD3), showcasing advanced text-in-image control and complex prompt handling, with the model outperforming other SOTA image generation models in human-evaluated benchmarks. The SD3 model is based on an enhanced Diffusion Transformer architecture called MMDiT. Meanwhile, Anthropic released Claude 3 models, noted for human-like responses and emotional depth, scoring 79.88% on HumanEval but costing over twice as much as GPT-4. Microsoft launched new Orca-based models and datasets, and Latitude released DolphinCoder-StarCoder2-15b with strong coding capabilities. Integration of image models by Perplexity AI and 3D CAD generation by PolySpectra powered by LlamaIndex were also highlighted. "SD3's win rate beats all other SOTA image gen models (except perhaps Ideogram)" and "Claude 3 models are very good at generating d3 visualizations from text descriptions."
Mistral Large disappoints
mistral-large mistral-small mixtral-8x7b gpt-4-turbo dreamgen-opus-v1 mistral-ai openai hugging-face benchmarking model-merging fine-tuning reinforcement-learning model-training tokenization model-optimization ai-assisted-decompilation performance cost-efficiency deception roleplay deep-speed dpo timotheeee1 cogbuji plasmator jsarnecki maldevide spottyluck mrjackspade
Mistral announced Mistral Large, a new language model achieving 81.2% accuracy on MMLU, trailing GPT-4 Turbo by about 5 percentage points on benchmarks. The community reception has been mixed, with skepticism about open sourcing and claims that Mistral Small outperforms the open Mixtral 8x7B. Discussions in the TheBloke Discord highlighted performance and cost-efficiency comparisons between Mistral Large and GPT-4 Turbo, technical challenges with DeepSpeed and DPOTrainer for training, advances in AI deception for roleplay characters using DreamGen Opus V1, and complexities in model merging using linear interpolation and PEFT methods. Enthusiasm for AI-assisted decompilation was also expressed, emphasizing the use of open-source projects for training data.
RIP Latent Diffusion, Hello Hourglass Diffusion
gpt-4 latent-diffusion stable-diffusion meta-ai-fair openai hugging-face diffusion-models transformers image-generation model-efficiency fine-tuning quantization prompt-engineering roleplay training-optimization katherine-crowson lucidrains
Katherine Crowson from Stable Diffusion introduces a hierarchical pure transformer backbone for diffusion-based image generation that efficiently scales to megapixel resolutions with under 600 million parameters, improving upon the original ~900M parameter model. This architecture processes local and global image phenomena separately, enhancing efficiency and resolution without latent steps. Additionally, Meta's Self Rewarding LM paper has inspired lucidrains to begin an implementation. Discord summaries highlight GPT-4's robustness against quantification tricks, discussions on open-source GPT-0 alternatives, challenges in DPO training on limited VRAM with suggestions like QLoRA and rmsprop, and efforts to improve roleplay model consistency through fine-tuning and merging. Philosophical debates on AI sentience and GPT-4 customization for markdown and translation tasks were also noted.