All tags
Topic: "prompt-engineering"
not much happened today
chatgpt o3 o4 bagel-7b medgemma acereason-nemotron-14b codex gemini openai bytedance google nvidia sakana-ai-labs deep-learning-ai gemini agenticseek anthropic agentic-systems multimodality reasoning code-generation prompt-engineering privacy ethical-ai emergence synthetic-data speech-instruction-tuning low-resource-languages humor scaling01 mervenoyann sakananailabs _philschmid omarsar0 teortaxestex andrewlampinen sedielem cis_female
OpenAI plans to evolve ChatGPT into a super-assistant by 2025 with models like o3 and o4 enabling agentic tasks and supporting a billion users. Recent multimodal and reasoning model releases include ByteDance's BAGEL-7B, Google's MedGemma, and NVIDIA's ACEReason-Nemotron-14B. The Sudoku-Bench Leaderboard highlights ongoing challenges in AI creative reasoning. In software development, OpenAI's Codex aids code generation and debugging, while Gemini's Context URL tool enhances prompt context. AgenticSeek offers a local, privacy-focused alternative for autonomous agents. Ethical concerns are raised about AGI development priorities and Anthropic's alignment with human values. Technical discussions emphasize emergence in AI and training challenges, with humor addressing misconceptions about Gemini 3.0 and async programming in C. A novel synthetic speech training method enables instruction tuning of LLMs without real speech data, advancing low-resource language support.
Promptable Prosody, SOTA ASR, and Semantic VAD: OpenAI revamps Voice AI
gpt-4o-transcribe gpt-4o-mini-tts o1-pro kokoro-82m openai replicate speech-to-text text-to-speech voice-activity-detection prompt-engineering real-time-processing model-release api function-calling structured-outputs model-performance juberti sama reach_vb kevinweil omarsar0
OpenAI has launched three new state-of-the-art audio models in their API, including gpt-4o-transcribe, a speech-to-text model outperforming Whisper, and gpt-4o-mini-tts, a text-to-speech model with promptable prosody allowing control over timing and emotion. The Agents SDK now supports audio, enabling voice agents. OpenAI also updated turn detection for real-time voice activity detection (VAD) based on speech content. Additionally, OpenAI's o1-pro model is available to select developers with advanced features like vision and function calling, though at higher compute costs. The community shows strong enthusiasm for these audio advancements, with a radio contest for TTS creations underway. Meanwhile, Kokoro-82M v1.0 emerges as a leading open weights TTS model with competitive pricing on Replicate.
not much happened today
jamba-1.6 mistral-ocr qwq-32b o1 o3-mini instella llama-3-2-3b gemma-2-2b qwen-2-5-3b babel-9b babel-83b gpt-4o claude-3-7-sonnet ai21-labs mistral-ai alibaba openai amd anthropic hugging-face multimodality ocr multilinguality structured-output on-prem-deployment reasoning benchmarking api open-source model-training gpu-optimization prompt-engineering function-calling
AI21 Labs launched Jamba 1.6, touted as the best open model for private enterprise deployment, outperforming Cohere, Mistral, and Llama on benchmarks like Arena Hard. Mistral AI released a state-of-the-art multimodal OCR model with multilingual and structured output capabilities, available for on-prem deployment. Alibaba Qwen introduced QwQ-32B, an open-weight reasoning model with 32B parameters and cost-effective usage, showing competitive benchmark scores. OpenAI released o1 and o3-mini models with advanced API features including streaming and function calling. AMD unveiled Instella, open-source 3B parameter language models trained on AMD Instinct MI300X GPUs, competing with Llama-3.2-3B and others. Alibaba also released Babel, open multilingual LLMs performing comparably to GPT-4o. Anthropic launched Claude 3.7 Sonnet, enhancing reasoning and prompt engineering capabilities.
not much happened today
chatgpt-4o deepseek-r1 o3 o3-mini gemini-2-flash qwen-2.5 qwen-0.5b hugging-face openai perplexity-ai deepseek-ai gemini qwen metr_evals reasoning benchmarking model-performance prompt-engineering model-optimization model-deployment small-language-models mobile-ai ai-agents speed-optimization _akhaliq aravsrinivas lmarena_ai omarsar0 risingsayak
Smolagents library by Huggingface continues trending. ChatGPT-4o latest version
chatgpt-40-latest-20250129 released. DeepSeek R1 671B sets speed record at 198 t/s, fastest reasoning model, recommended with specific prompt settings. Perplexity Deep Research outperforms models like Gemini Thinking, o3-mini, and DeepSeek-R1 on Humanity's Last Exam benchmark with 21.1% score and 93.9% accuracy on SimpleQA. ChatGPT-4o ranks #1 on Arena leaderboard in multiple categories except math. OpenAI's o3 model powers Deep Research tool for ChatGPT Pro users. Gemini 2 Flash and Qwen 2.5 models support LLMGrading verifier. Qwen 2.5 models added to PocketPal app. MLX shows small LLMs like Qwen 0.5B generate tokens at high speed on M4 Max and iPhone 16 Pro. Gemini Flash 2.0 leads new AI agent leaderboard. DeepSeek R1 is most liked on Hugging Face with over 10 million downloads. Gemini (Experimental-1114) retakes #1 LLM rank with 1344 Elo
claude-3-sonnet gpt-4 gemini-1.5 claude-3.5-sonnet anthropic openai langchain meta-ai-fair benchmarking prompt-engineering rag visuotactile-perception ai-governance theoretical-alignment ethical-alignment jailbreak-robustness model-releases alignment richardmcngo andrewyng philschmid
Anthropic released the 3.5 Sonnet benchmark for jailbreak robustness, emphasizing adaptive defenses. OpenAI enhanced GPT-4 with a new RAG technique for contiguous chunk retrieval. LangChain launched Promptim for prompt optimization. Meta AI introduced NeuralFeels with neural fields for visuotactile perception. RichardMCNgo resigned from OpenAI, highlighting concerns on AI governance and theoretical alignment. Discussions emphasized the importance of truthful public information and ethical alignment in AI deployment. The latest Gemini update marks a new #1 LLM amid alignment challenges. The AI community continues to focus on benchmarking, prompt-engineering, and alignment issues.
Common Corpus: 2T Open Tokens with Provenance
qwen-2.5-coder claude-3.5-sonnet janusflow-1.3b ocronos-vintage pleais huggingface langchainai deepseek alibaba anthropic provenance ocr multilingual-datasets prompt-engineering multimodality image-generation code-generation quantization model-scaling inference-efficiency tim-dettmers tom-doerr omarsar0 swyx madiator reach_vb
Pleais via Huggingface released Common Corpus, the largest fully open multilingual dataset with over 2 trillion tokens including detailed provenance information. They also introduced OCRonos-Vintage, a 124M-parameter OCR correction model that efficiently fixes digitization errors on CPU and GPU, unlocking knowledge from PDFs. On AI tools, LangChainAI launched Prompt Canvas for collaborative prompt engineering, while DeepSeek released JanusFlow 1.3B, a unified multimodal LLM integrating autoregressive and rectified flow models for enhanced image understanding and generation. Alibaba Cloud announced Qwen2.5-Coder, a code-focused LLM with advanced coding capabilities, and Claude 3.5 Sonnet was highlighted for superior code generation. Discussions on quantization challenges and scaling laws for precision by Tim Dettmers and others emphasized the impact of low-precision training on model scalability and inference efficiency. "Scaling Laws for Precision" paper insights and alternative efficiency methods were also noted.
not much happened today
smollm2 llama-3-2 stable-diffusion-3.5 claude-3.5-sonnet gemini openai anthropic google meta-ai-fair suno-ai perplexity-ai on-device-ai model-performance robotics multimodality ai-regulation model-releases natural-language-processing prompt-engineering agentic-ai ai-application model-optimization sam-altman akhaliq arav-srinivas labenz loubnabenallal1 alexalbert fchollet stasbekman svpino rohanpaul_ai hamelhusain
ChatGPT Search was launched by Sam Altman, who called it his favorite feature since ChatGPT's original launch, doubling his usage. Comparisons were made between ChatGPT Search and Perplexity with improvements noted in Perplexity's web navigation. Google introduced a "Grounding" feature in the Gemini API & AI Studio enabling Gemini models to access real-time web information. Despite Gemini's leaderboard performance, developer adoption lags behind OpenAI and Anthropic. SmolLM2, a new small, powerful on-device language model, outperforms Meta's Llama 3.2 1B. A Claude desktop app was released for Mac and Windows. Meta AI announced robotics advancements including Meta Sparsh, Meta Digit 360, and Meta Digit Plexus. Stable Diffusion 3.5 Medium, a 2B parameter model with a permissive license, was released. Insights on AGI development suggest initial inferiority but rapid improvement. Anthropic advocates for early targeted AI regulation. Discussions on ML specialization predict training will concentrate among few companies, while inference becomes commoditized. New AI tools include Suno AI Personas for music creation, PromptQL for natural language querying over data, and Agent S for desktop task automation. Humor was shared about Python environment upgrades.
Creating a LLM-as-a-Judge
claude-3.5-sonnet claude-3.5 notebooklm simpleqa recraft-v3 anthropic openai deepmind apple zep perplexity-ai github critique-shadowing llm-judging domain-experts dataset-creation prompt-engineering error-analysis temporal-knowledge-graphs memory-layer ai-agent-memory hallucination-reduction integration hamel-husain swyx
Anthropic released details on Claude 3.5 SWEBench+SWEAgent, while OpenAI introduced SimpleQA and DeepMind launched NotebookLM. Apple announced new M4 Macbooks, and a new SOTA image model, Recraft v3, emerged. Hamel Husain presented a detailed 6,000-word treatise on creating LLM judges using a method called critique shadowing to align LLMs with domain experts, addressing the problem of untrusted and unused data in AI teams. The workflow involves expert-reviewed datasets and iterative prompt refinement. Additionally, Zep introduced a temporal knowledge graph memory layer to improve AI agent memory and reduce hallucinations. Anthropic also integrated Claude 3.5 Sonnet with GitHub Copilot, expanding access to Copilot Chat users.
not much happened today
aria o1-preview o1-mini gemini-1.5-pro gemini-1.5-flash gemini-1.5 claude-3.5-sonnet rhymes-ai openai anthropic google meta-ai-fair oxylabs multimodality mixture-of-experts long-context retrieval-augmented-generation benchmarking software-engineering llm-evaluation prompt-engineering web-scraping python production-applications mervenoyann osanseviero dbrxmosaicai ylecun ofirpress clefourrier omarsar0 rohanpaul_ai svpino finbarrtimbers _philschmid
Rhymes AI released Aria, a new 25.3B parameter multimodal MoE model supporting text, code, image, and video with a 64k token context window and Apache-2.0 license. OpenAI's o1-preview and o1-mini models show consistent improvement over Anthropic and Google Gemini 1.5 Pro/Flash on long context RAG benchmarks up to 128k tokens, while Google Gemini 1.5 models excel at extreme context lengths up to 2 million tokens. Meta AI expanded rollout to 21 countries with new language support but remains unavailable in the EU. The one-year anniversary of SWE-bench benchmark for software engineering tasks was celebrated, alongside the introduction of SWE-bench Multimodal. New AI tools include OxyCopilot by Oxylabs for web scraping, Taipy for Python-based production apps, and Latitude for prompt engineering. Industry insights highlight changing AI funding dynamics and OpenAI's strategic focus on consumer products like ChatGPT. "all recaps done by Claude 3.5 Sonnet, best of 4 runs."
not much happened today + AINews Podcast?
superforecaster-ai llama-3 reflection-70b glean sambanova cerebras stanford google apple hugging-face lmsys prompt-engineering research-ideas inference-speed retrieval-augmented-generation evaluation-methods visual-intelligence on-device-ai model-performance benchmarking novelty-detection danhendrycks benjamin-clavie bclavie bindureddy swyx borismpower corbtt drjimfan clementdelangue rohanpaul_ai
Glean doubled its valuation again. Dan Hendrycks' Superforecaster AI generates plausible election forecasts with interesting prompt engineering. A Stanford study found that LLM-generated research ideas are statistically more novel than those by expert humans. SambaNova announced faster inference for llama-3 models, surpassing Cerebras. Benjamin Clavie gave a notable talk on retrieval-augmented generation techniques. Strawberry is reported to launch in two weeks. Google Illuminate offers AI-generated podcast discussions about papers and books. Apple unveiled new AI features in iOS 18, including visual intelligence and improved Siri, with on-device and cloud processing for camera-based event additions. The Reflection 70B model sparked controversy over performance claims. Experts highlighted the unreliability of traditional benchmarks like MMLU and HumanEval, recommending alternative evaluation methods such as LMSys Chatbot Arena and Hugging Face's open-sourced Lighteval suite. The AI research community continues to explore AI's role in generating novel research ideas and improving benchmarking.
Reflection 70B, by Matt from IT Department
llama-3.1-70b llama-3 claude-3.5-sonnet hyperwrite glaive fine-tuning chain-of-thought instruction-following synthetic-data quantization model-evaluation prompt-engineering matt-shumer sahil-chaudhary
Reflection Tuning technique has been used by a two-person team from Hyperwrite and Glaive to finetune llama-3.1-70b, showing strong performance improvements with minimal synthetic data. The approach builds on the concept of adding
thinking and reflection steps to outputs, related to the Chain of Thought method. Despite some criticisms like contamination concerns, worse coding performance, and reliance on system prompts, the model has received positive reception and comparisons to claude-3.5-sonnet. The work highlights efficient instruction tuning and synthetic data generation for large models. 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 2B + Scope + Shield
gemma-2b gemma-2-9b gemma-2-27b llama-3-1-405b sam-2 gpt-3.5 vicuna alpacaeval g-eval google-deepmind anthropic meta-ai-fair openai perplexity-ai nvidia lmsys knowledge-distillation leaderboards model-interpretability finetuning harm-detection video-segmentation voice publishers-program robotics-data-scaling quantization llm-evaluation prompt-engineering
Gemma 2B, a 2 billion parameter model trained on 2 trillion tokens and distilled from a larger unnamed LLM, has been released by Google DeepMind and shows strong leaderboard performance despite weaknesses in math. The Gemma series, including 9B and 27B models, has gained popularity since its June release. The team also released 400 SAEs for interpretability, inspired by Anthropic's research. A finetuned classifier called ShieldGemma outperforms Meta's LlamaGuard in harm detection. Meanwhile, Meta AI announced Llama-3.1-405B reaching #3 on the Overall Arena leaderboard, and released SAM 2, a video and image segmentation model with significant speed improvements. OpenAI is rolling out an advanced Voice Mode to Plus users. Perplexity AI launched a Publishers Program with major media partners and a status page. NVIDIA introduced Project GR00T for scaling robot data using Apple Vision Pro and generative simulation. Interest in quantization for compressing LLMs is growing, and LLM-as-a-Judge implementations from Vicuna, AlpacaEval, and G-Eval highlight the effectiveness of simple prompts and domain-specific evaluation.
Problems with MMLU-Pro
mmlu-pro llama-3-8b-q8 gpt4all-3.0 chatgpt claude llama gemini mobilellm runway-gen-3-alpha meta-3d-gen huggingface meta-ai-fair salesforce runway nomic-ai pineapple argil-ai benchmarking prompt-engineering model-evaluation model-performance multimodality automated-dataset-generation video-generation open-source-models ai-assistants text-to-3d deepfake transformers reasoning wenhu-chen danhendrycks clementine ylecun adcock_brett svpino rohanpaul_ai
MMLU-Pro is gaining attention as the successor to MMLU on the Open LLM Leaderboard V2 by HuggingFace, despite community concerns about evaluation discrepancies and prompt sensitivity affecting model performance, notably a 10-point improvement in Llama-3-8b-q8 with simple prompt tweaks. Meta's MobileLLM research explores running sub-billion parameter LLMs on smartphones using shared weights and deeper architectures. Salesforce's APIGen introduces an automated dataset generation system for function-calling tasks outperforming larger models. Runway Gen-3 Alpha launches an AI video generator for paid users creating realistic 10-second clips. Nomic AI's GPT4All 3.0 offers an open-source desktop app supporting thousands of local models. AI assistants with multimodal capabilities and affordable access to multiple LLMs like ChatGPT, Claude, Llama, and Gemini are emerging. Meta 3D Gen advances text-to-3D asset generation, while Argil AI enables deepfake video creation from text threads. Research on transformer grokking and reasoning highlights advances in robust reasoning capabilities.
Not much happened today
gemini-1.5-flashmodel gemini-pro mixtral mamba-2 phi-3-medium phi-3-small gpt-3.5-turbo-0613 llama-3-8b llama-2-70b mistral-finetune twelve-labs livekit groq openai nea nvidia lmsys mistral-ai model-performance prompt-engineering data-curation ai-safety model-benchmarking model-optimization training sequence-models state-space-models daniel-kokotajlo rohanpaul_ai _arohan_ tri_dao _albertgu _philschmid sarahcat21 hamelhusain jachiam0 willdepue teknium1
Twelve Labs raised $50m in Series A funding co-led by NEA and NVIDIA's NVentures to advance multimodal AI. Livekit secured $22m in funding. Groq announced running at 800k tokens/second. OpenAI saw a resignation from Daniel Kokotajlo. Twitter users highlighted Gemini 1.5 FlashModel for high performance at low cost and Gemini Pro ranking #2 in Japanese language tasks. Mixtral models can run up to 8x faster on NVIDIA RTX GPUs using TensorRT-LLM. Mamba-2 model architecture introduces state space duality for larger states and faster training, outperforming previous models. Phi-3 Medium (14B) and Small (7B) models benchmark near GPT-3.5-Turbo-0613 and Llama 3 8B. Prompt engineering is emphasized for unlocking LLM capabilities. Data quality is critical for model performance, with upcoming masterclasses on data curation. Discussions on AI safety include a Frontier AI lab employee letter advocating whistleblower protections and debates on aligning AI to user intent versus broader humanity interests.
Ten Commandments for Deploying Fine-Tuned Models
claude-3-opus claude-3 gpt-4o anthropic google openai fine-tuning prompt-engineering model-evaluation feature-alteration benchmarking model-performance open-source-models kyle-corbitt bindureddy alexalbert__
Gemini-in-Google-Slides is highlighted as a useful tool for summarizing presentations. Kyle Corbitt's talk on deploying fine-tuned models in production emphasizes avoiding fine-tuning unless necessary, focusing on prompting, data quality, appropriate model choice, and thorough evaluation. Anthropic showcased feature alteration in Claude AI, demonstrating control over model behavior and increased understanding of large language models. Open-source models like GPT-4o are approaching closed-source performance on benchmarks like MMLU for simple tasks, though advanced models remain necessary for complex automation.
GPT-4o: the new SOTA-EVERYTHING Frontier model (GPT4T version)
gpt-4o gpt-3.5 llama-3 openai hugging-face nous-research eleutherai hazyresearch real-time-reasoning coding-capabilities fine-tuning knowledge-distillation hardware-optimization quantization multimodality mixture-of-experts efficient-attention model-scaling depth-upscaling transformer-architecture gpu-optimization prompt-engineering
OpenAI launched GPT-4o, a frontier model supporting real-time reasoning across audio, vision, and text, now free for all ChatGPT users with enhanced coding capabilities and upcoming advanced voice and video features. Discussions cover open-source LLMs like Llama 3, fine-tuning techniques including knowledge distillation for GPT-3.5, and hardware optimization strategies such as quantization. Emerging architectures include multimodal integrations with ChatGPT voice and Open Interpreter API, Mixture of Experts models combining autoregressive and diffusion approaches, and novel designs like the YOCO architecture and ThunderKittens DSL for efficient GPU use. Research advances in efficient attention methods like Conv-Basis using FFT and model scaling techniques such as depth upscaling were also highlighted.
Quis promptum ipso promptiet?
llama-3-70b llama-3-120b llama-3 llama-cpp anthropic openai zoominfo neuralink prompt-engineering chain-of-thought rag quantization cuda-graphs gpu-optimization thought-controlled-devices modeling-consciousness conference sama gdb bindureddy svpino rohanpaul_ai alexalbert__ abacaj
Anthropic released upgrades to their Workbench Console, introducing new prompt engineering features like chain-of-thought reasoning and prompt generators that significantly reduce development time, exemplified by their customer Zoominfo. OpenAI teased a "magic" new development coming soon, speculated to be a new LLM replacing GPT-3.5 in the free tier or a search competitor. The open-source community highlighted Llama 3 70B as "game changing" with new quantized weights for Llama 3 120B and CUDA graph support for llama.cpp improving GPU performance. Neuralink demonstrated a thought-controlled mouse, sparking interest in modeling consciousness from brain signals. The ICLR 2024 conference is being held in Asia for the first time, generating excitement.
Anime pfp anon eclipses $10k A::B prompting challenge
command-r-plus-104b stable-diffusion-1.5 openai ollama huggingface quantization model-optimization streaming prompt-engineering self-prompting image-composition character-lora-training model-size open-source-licenses memes humor victor-taelin futuristfrog
Victor Taelin issued a $10k challenge to GPT models, initially achieving only 10% success with state-of-the-art models, but community efforts surpassed 90% success within 48 hours, highlighting GPT capabilities and common skill gaps. In Reddit AI communities, Command R Plus (104B) is running quantized on M2 Max hardware via Ollama and llama.cpp forks, with GGUF quantizations released on Huggingface. Streaming text-to-video generation is now available through the st2v GitHub repo. WD Tagger v3 was released for mass auto-captioning datasets with a WebUI. Lesser-known prompting techniques like self-tagging and generational frameworks produced thought-provoking outputs in OpenAI discussions, including experiments with self-evolving system prompts. Stable Diffusion users discussed image composition importance for training character LoRAs and best checkpoints for video game character generation. Discussions also covered scarcity of 5B parameter models and open(ish) licenses for open source AI. Memes included jokes about ChatGPT and Gemini training data differences.
Evals-based AI Engineering
jamba bamboo qwen-1.5-moe grok-1.5 llama2-7b openai mistral-ai x-ai llamaindex evaluation fine-tuning prompt-engineering voice-cloning quantization model-optimization code-generation context-windows hamel-husain alec-radford
Hamel Husain emphasizes the importance of comprehensive evals in AI product development, highlighting evaluation, debugging, and behavior change as key iterative steps. OpenAI released a voice engine demo showcasing advanced voice cloning from small samples, raising safety concerns. Reddit discussions introduced new models like Jamba (hybrid Transformer-SSM with MoE), Bamboo (7B LLM with high sparsity based on Mistral), Qwen1.5-MoE (efficient parameter activation), and Grok 1.5 (128k context length, surpassing GPT-4 in code generation). Advances in quantization include 1-bit Llama2-7B models outperforming full precision and the QLLM quantization toolbox supporting GPTQ/AWQ/HQQ methods.
World_sim.exe
gpt-4 gpt-4o grok-1 llama-cpp claude-3-opus claude-3 gpt-5 nvidia nous-research stability-ai hugging-face langchain anthropic openai multimodality foundation-models hardware-optimization model-quantization float4 float6 retrieval-augmented-generation text-to-video prompt-engineering long-form-rag gpu-optimization philosophy-of-ai agi-predictions jensen-huang yann-lecun sam-altman
NVIDIA announced Project GR00T, a foundation model for humanoid robot learning using multimodal instructions, built on their tech stack including Isaac Lab, OSMO, and Jetson Thor. They revealed the DGX Grace-Blackwell GB200 with over 1 exaflop compute, capable of training GPT-4 1.8T parameters in 90 days on 2000 Blackwells. Jensen Huang confirmed GPT-4 has 1.8 trillion parameters. The new GB200 GPU supports float4/6 precision with ~3 bits per parameter and achieves 40,000 TFLOPs on fp4 with 2x sparsity.
Open source highlights include the release of Grok-1, a 340B parameter model, and Stability AI's SV3D, an open-source text-to-video generation solution. Nous Research collaborated on implementing Steering Vectors in Llama.CPP.
In Retrieval Augmented Generation (RAG), a new 5.5-hour tutorial builds a pipeline using open-source HF models, and LangChain released a video on query routing and announced integration with NVIDIA NIM for GPU-optimized LLM inference.
Prominent opinions include Yann LeCun distinguishing language from other cognitive abilities, Sam Altman predicting AGI arrival in 6 years with a leap from GPT-4 to GPT-5 comparable to GPT-3 to GPT-4, and discussions on the philosophical status of LLMs like Claude. There is also advice against training models from scratch for most companies.
The Dissection of Smaug (72B)
smaug-72b qwen-1.0 qwen-1.5 gpt-4 mistral-7b miqumaid wizardlm_evol_instruct_v2_196k openhermes-2.5 abacus-ai hugging-face nous-research laion thebloke lm-studio intel nvidia elevenlabs fine-tuning model-merging quantization web-ui model-conversion hardware-setup privacy image-generation optical-character-recognition prompt-engineering bindureddy
Abacus AI launched Smaug 72B, a large finetune of Qwen 1.0, which remains unchallenged on the Hugging Face Open LLM Leaderboard despite skepticism from Nous Research. LAION introduced a local voice assistant model named Bud-E with a notable demo. The TheBloke Discord community discussed model performance trade-offs between large models like GPT-4 and smaller quantized models, fine-tuning techniques using datasets like WizardLM_evol_instruct_V2_196k and OpenHermes-2.5, and challenges in web UI development and model merging involving Mistral-7b and MiquMaid. The LM Studio Discord highlighted issues with model conversion from PyTorch to gguf, hardware setups involving Intel Xeon CPUs and Nvidia P40 GPUs, privacy concerns, and limitations in image generation and web UI availability.
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.
RWKV "Eagle" v5: Your move, Mamba
rwkv-v5 mistral-7b miqu-1-70b mistral-medium llama-2 mistral-instruct-v0.2 mistral-tuna llama-2-13b kunoichi-dpo-v2-7b gpt-4 eleutherai mistral-ai hugging-face llamaindex nous-research rwkv lmsys fine-tuning multilinguality rotary-position-embedding model-optimization model-performance quantization speed-optimization prompt-engineering model-benchmarking reinforcement-learning andrej-karpathy
RWKV v5 Eagle was released with better-than-mistral-7b evaluation results, trading some English performance for multilingual capabilities. The mysterious miqu-1-70b model sparked debate about its origins, possibly a leak or distillation of Mistral Medium or a fine-tuned Llama 2. Discussions highlighted fine-tuning techniques, including the effectiveness of 1,000 high-quality prompts over larger mixed-quality datasets, and tools like Deepspeed, Axolotl, and QLoRA. The Nous Research AI community emphasized the impact of Rotary Position Embedding (RoPE) theta settings on LLM extrapolation, improving models like Mistral Instruct v0.2. Speed improvements in Mistral Tuna kernels reduced token processing costs, enhancing efficiency. The launch of Eagle 7B with 7.52B parameters showcased strong multilingual performance, surpassing other 7B class models.
GPT4Turbo A/B Test: gpt-4-1106-preview
gpt-4-turbo gpt-4 gpt-3.5 openhermes-2.5-mistral-7b-4.0bpw exllamav2 llama-2-7b-chat mistral-instruct-v0.2 mistrallite llama2 openai huggingface thebloke nous-research mistral-ai langchain microsoft azure model-loading rhel dataset-generation llm-on-consoles fine-tuning speed-optimization api-performance prompt-engineering token-limits memory-constraints text-generation nlp-tools context-window-extension sliding-windows rope-theta non-finetuning-context-extension societal-impact
OpenAI released a new GPT-4 Turbo version, prompting a natural experiment in summarization comparing the November 2023 and January 2024 versions. The TheBloke Discord discussed troubleshooting model loading errors with OpenHermes-2.5-Mistral-7B-4.0bpw and exllamav2, debates on RHEL in ML, dataset generation for understanding GPT flaws, and running LLMs like Llama and Mistral on consoles. LangChain fine-tuning challenges for Llama2 were also noted. The OpenAI Discord highlighted GPT-4 speed inconsistencies, API vs web performance, prompt engineering with GPT-3.5 and GPT-4 Turbo, and DALL-E typo issues in image text. Discussions included NLP tools like semantic-text-splitter and collaboration concerns with GPT-4 Vision on Azure. The Nous Research AI Discord focused on extending context windows with Mistral instruct v0.2, MistralLite, and LLaMA-2-7B-Chat achieving 16,384 token context, plus alternatives like SelfExtend for context extension without fine-tuning. The societal impact of AI technology was also considered.
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.
1/13-14/2024: Don't sleep on #prompt-engineering
The OpenAI Discord community engaged in diverse discussions including prompt engineering techniques like contrastive Chain of Thought and step back prompting, and explored model merging and mixture-of-experts (MoE) concepts. Philosophical debates on AI consciousness and the ethics of AI-generated voices highlighted concerns about AI sentience and copyright issues. Technical clarifications were made on hyperdimensional vector space models used in modern AI embeddings. Users also discussed customizing GPT with personality profiles and prompt personalization to overcome token limits, and proposed a universal translator feature for multilingual Discord interactions. Key contributors included longtime regular MadameArchitect and community members such as @darthgustav and @metaldrgn.
1/11/2024: Mixing Experts vs Merging Models
gpt-4-turbo gpt-4-0613 mixtral deepseekmoe phixtral deepseek-ai hugging-face nous-research teenage-engineering discord mixture-of-experts model-merging fine-tuning rag security discord-tos model-performance prompt-engineering function-calling semantic-analysis data-frameworks ash_prabaker shacrw teknium 0xevil everyoneisgross ldj pramod8481 mgreg_42266 georgejrjrjr kenakafrosty
18 guilds, 277 channels, and 1342 messages were analyzed with an estimated reading time saved of 187 minutes. The community switched to GPT-4 turbo and discussed the rise of Mixture of Experts (MoE) models like Mixtral, DeepSeekMOE, and Phixtral. Model merging techniques, including naive linear interpolation and "frankenmerges" by SOLAR and Goliath, are driving new performance gains on open leaderboards. Discussions in the Nous Research AI Discord covered topics such as AI playgrounds supporting prompt and RAG parameters, security concerns about third-party cloud usage, debates on Discord bots and TOS, skepticism about Teenage Engineering's cloud LLM, and performance differences between GPT-4 0613 and GPT-4 turbo. The community also explored fine-tuning strategies involving DPO, LoRA, and safetensors, integration of RAG with API calls, semantic differences between MoE and dense LLMs, and data frameworks like llama index and SciPhi-AI's synthesizer. Issues with anomalous characters in fine-tuning were also raised.
1/10/2024: All the best papers for AI Engineers
chatgpt gpt-4 dall-e-3 stable-diffusion deepseek-moe openai deepseek-ai prompt-engineering model-release rate-limiting ethics image-generation moe collaborative-workspaces data-privacy abdubs darthgustav
OpenAI launched the GPT Store featuring over 3 million custom versions of ChatGPT accessible to Plus, Team, and Enterprise users, with weekly highlights of impactful GPTs like AllTrails. The new ChatGPT Team plan offers advanced models including GPT-4 and DALL·E 3, alongside collaborative tools and enhanced data privacy. Discussions around AI-generated imagery favored DALL·E and Stable Diffusion, while users faced rate limit challenges and debated the GPT Store's SEO and categorization. Ethical considerations in prompt engineering were raised with a three-layer framework called 'The Sieve'. Additionally, DeepSeek-MoE was noted for its range of Mixture of Experts (MoE) model sizes. "The Sieve," a three-layer ethical framework for AI, was highlighted in prompt engineering discussions.
1/2/2024: Smol tweaks to Smol Talk
claude-2 bard copilot meta-ai gemini-ultra chatgpt openai meta-ai-fair perplexity-ai prompt-engineering api json yaml markdown chatbot image-generation vpn browser-compatibility personality-tuning plugin-issues
OpenAI Discord discussions highlight a detailed comparison of AI search engines including Perplexity, Copilot, Bard, and Claude 2, with Bard and Claude 2 trailing behind. Meta AI chatbot by Meta is introduced, available on Instagram and Whatsapp, featuring image generation likened to a free GPT version. Users report multiple browser issues with ChatGPT, including persistent captchas when using VPNs and plugin malfunctions. Debates cover prompt engineering, API usage, and data formats like JSON, YAML, and Markdown. Discussions also touch on ChatGPT's personality tuning and model capability variations. "Meta AI includes an image generation feature, which he likened to a free version of GPT."
1/1/2024: How to start with Open Source AI
gpt-4-turbo dall-e-3 chatgpt openai microsoft perplexity-ai prompt-engineering ai-reasoning custom-gpt performance python knowledge-integration swyx
OpenAI Discord discussions revealed mixed sentiments about Bing's AI versus ChatGPT and Perplexity AI, and debated Microsoft Copilot's integration with Office 365. Users discussed DALL-E 3 access within ChatGPT Plus, ChatGPT's performance issues, and ways to train a GPT model using book content via OpenAI API or custom GPTs. Anticipation for GPT-4 turbo in Microsoft Copilot was noted alongside conversations on AI reasoning, prompt engineering, and overcoming Custom GPT glitches. Advice for AI beginners included starting with Python and using YAML or Markdown for knowledge integration. The future of AI with multiple specialized GPTs and Microsoft Copilot's role was also explored.
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.
12/20/2023: Project Obsidian - Multimodal Mistral 7B from Nous
gpt-4 gpt-3.5 dall-e-3 nous-research teknim openai multimodality image-detection security-api bias facial-recognition healthcare-ai gpu-optimization prompt-engineering vision
Project Obsidian is a multimodal model being trained publicly, tracked by Teknium on the Nous Discord. Discussions include 4M: Massively Multimodal Masked Modeling and Reason.dev, a TypeScript framework for LLM applications. The OpenAI Discord community discussed hardware specs for running TensorFlow JS for image detection, security API ideas for filtering inappropriate images, and concerns about racial and cultural bias in AI, especially in facial recognition and healthcare. Challenges with GPT-3.5 and GPT-4 in word puzzle games were noted, along with GPU recommendations prioritizing VRAM for AI inference. Users also debated GPT-4's vision capabilities, limitations of DALL·E 3, platform access issues, and prompting strategies for better outputs.
12/19/2023: Everybody Loves OpenRouter
gpt-4 gpt-3.5 mixtral-8x7b-instruct dolphin-2.0-mistral-7b gemini openai mistral-ai google hugging-face performance memory-management api prompt-engineering local-language-models translation censorship video-generation
OpenRouter offers an easy OpenAI-compatible proxy for Mixtral-8x7b-instruct. Discord discussions highlight GPT-4 performance and usability issues compared to GPT-3.5, including memory management and accessibility problems. Users debate local language models versus OpenAI API usage, with mentions of Dolphin 2.0 Mistral 7B and Google's video generation project. Prompt engineering and custom instructions for GPT models are also key topics. Concerns about censorship on models like Gemini and translation tool preferences such as DeepL were discussed.
12/18/2023: Gaslighting Mistral for fun and profit
gpt-4-turbo gpt-3.5-turbo claude-2.1 claude-instant-1 gemini-pro gpt-4.5 dalle-3 openai anthropic google-deepmind prompt-engineering api model-performance ethics role-play user-experience ai-impact-on-jobs ai-translation technical-issues sam-altman
OpenAI Discord discussions reveal comparisons among language models including GPT-4 Turbo, GPT-3.5 Turbo, Claude 2.1, Claude Instant 1, and Gemini Pro, with GPT-4 Turbo noted for user-centric explanations. Rumors about GPT-4.5 remain unconfirmed, with skepticism prevailing until official announcements. Users discuss technical challenges like slow responses and API issues, and explore role-play prompt techniques to enhance model performance. Ethical concerns about AI's impact on academia and employment are debated. Future features for Dalle 3 and a proposed new GPT model are speculated upon, while a school project seeks help using the OpenAI API. The community also touches on AI glasses and job market implications of AI adoption.
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.
12/14/2023: $1e7 for Superalignment
gemini bard gpt-4 gpt-4.5 llama-2 openai llamaindex perplexity-ai prompt-engineering api custom-gpt json bug-fixes chatbots performance tts code-generation image-recognition jan-leike patrick-collison
Jan Leike is launching a new grant initiative inspired by Patrick Collison's Fast Grants to support AI research. OpenAI introduced a new developers Twitter handle @OpenAIDevs for community updates. Discussions on OpenAI's Gemini and Bard chatbots highlight their ability to read each other's instructions and offer unique coding solutions. Users reported various issues with GPT-4, including performance problems, customization difficulties, and a resolved bug in image recognition. There are ongoing conversations about prompt engineering challenges and new JSON mode support in Convo-lang for API use. Concerns about misuse of chatbots for illegal activities and alternatives like Llama2 models and the Perplexity chatbot were also discussed.
12/12/2023: Towards LangChain 0.1
mixtral-8x7b phi-2 gpt-3 chatgpt gpt-4 langchain mistral-ai anthropic openai microsoft mixture-of-experts information-leakage prompt-engineering oauth2 logo-generation education-ai gaming-ai api-access model-maintainability scalability
The Langchain rearchitecture has been completed, splitting the repo for better maintainability and scalability, while remaining backwards compatible. Mistral launched a new Discord community, and Anthropic is rumored to be raising another $3 billion. On the OpenAI Discord, discussions covered information leakage in AI training, mixture of experts (MoE) models like mixtral 8x7b, advanced prompt engineering techniques, and issues with ChatGPT performance and API access. Users also explored AI applications in logo generation, education, and gaming, and shared solutions for Oauth2 authentication problems. A new small language model named Phi-2 was mentioned from Microsoft.
12/8/2023 - Mamba v Mistral v Hyena
mistral-8x7b-moe mamba-3b stripedhyena-7b claude-2.1 gemini gpt-4 dialogrpt-human-vs-machine cybertron-7b-v2-gguf falcon-180b mistral-ai togethercompute stanford anthropic google hugging-face mixture-of-experts attention-mechanisms prompt-engineering alignment image-training model-deployment gpu-requirements cpu-performance model-inference long-context model-evaluation open-source chatbots andrej-karpathy tri-dao maxwellandrews raddka
Three new AI models are highlighted: Mistral's 8x7B MoE model (Mixtral), Mamba models up to 3B by Together, and StripedHyena 7B, a competitive subquadratic attention model from Stanford's Hazy Research. Discussions on Anthropic's Claude 2.1 focus on its prompting technique and alignment challenges. The Gemini AI from Google is noted as potentially superior to GPT-4. The community also explores Dreambooth for image training and shares resources like the DialogRPT-human-vs-machine model on Hugging Face. Deployment challenges for large language models, including CPU performance and GPU requirements, are discussed with references to Falcon 180B and transformer batching techniques. User engagement includes meme sharing and humor.
12/7/2023: Anthropic says "skill issue"
claude-2.1 gpt-4 gpt-3.5 gemini-pro gemini-ultra gpt-4.5 chatgpt bingchat dall-e gpt-5 anthropic openai google prompt-engineering model-performance regulation language-model-performance image-generation audio-processing midi-sequence-analysis subscription-issues network-errors
Anthropic fixed a glitch in their Claude 2.1 model's needle in a haystack test by adding a prompt. Discussions on OpenAI's Discord compared Google's Gemini Pro and Gemini Ultra models with OpenAI's GPT-4 and GPT-3.5, with some users finding GPT-4 superior in benchmarks. Rumors about a GPT-4.5 release circulated without official confirmation. Concerns were raised about "selective censorship" affecting language model performance. The EU's potential regulation of AI, including ChatGPT, was highlighted. Users reported issues with ChatGPT Plus message limits and subscription upgrades, and shared experiences with BingChat and DALL-E. The community discussed prompt engineering techniques and future applications like image generation and MIDI sequence analysis, expressing hopes for GPT-5.
Is Google's Gemini... legit?
gemini gemini-pro gemini-ultra gpt-4 gpt-3.5 claude-2.1 palm2 google openai chain-of-thought context-windows prompt-engineering model-evaluation multimodality speech-processing chatbot-errors subscription-management swyx
Google's Gemini AI model is generating significant discussion and skepticism, especially regarding its 32-shot chain of thought MMLU claim and 32k context window. The community is comparing Gemini's performance and capabilities with OpenAI's GPT-4 and GPT-3.5, highlighting the upcoming Gemini Pro and Gemini Ultra models on the Bard platform. Users report various OpenAI service issues including chatbot errors and subscription problems. Discussions also cover prompt engineering techniques, AI model evaluation comparing GPT-4, Claude 2.1, and PaLM2, and improvements in speech and multimodal capabilities. The bot now supports reading and summarizing links from platforms like arXiv, Twitter, and YouTube, enhancing user interaction.