All tags
Model: "lora"
ChatGPT Atlas: OpenAI's AI Browser
gemini atlas openai google langchain ivp capitalg sapphire sequoia benchmark agent-mode browser-memory chromium finetuning moe lora agent-runtime observability software-development funding kevinweil bengoodger fidjissimo omarsar0 yuchenj_uw nickaturley raizamrtn hwchase17 bromann casper_hansen_ corbtt
OpenAI launched the Chromium fork AI browser Atlas for macOS, featuring integrated Agent mode and browser memory with local login capabilities, aiming to surpass Google's Gemini in Chrome. The launch received mixed reactions regarding reliability and privacy. LangChain raised a $125M Series B at a $1.25B valuation, releasing v1.0 agent engineering stack with significant adoption including 85M+ OSS downloads/month and usage by ~35% of the Fortune 500. The ecosystem also saw updates like vLLM's MoE LoRA expert finetuning support.
not much happened today
kling-2.5-turbo sora-2 gemini-2.5-flash granite-4.0 qwen-3 qwen-image-2509 qwen3-vl-235b openai google ibm alibaba kling_ai synthesia ollama huggingface arena artificialanalysis tinker scaling01 video-generation instruction-following physics-simulation image-generation model-architecture mixture-of-experts context-windows token-efficiency fine-tuning lora cpu-training model-benchmarking api workflow-automation artificialanlys kling_ai altryne teortaxestex fofrai tim_dettmers sundarpichai officiallogank andrew_n_carr googleaidevs clementdelangue wzhao_nlp alibaba_qwen scaling01 ollama
Kling 2.5 Turbo leads in text-to-video and image-to-video generation with competitive pricing. OpenAI Sora 2 shows strong instruction-following but has physics inconsistencies. Google Gemini 2.5 Flash "Nano Banana" image generation is now generally available with multi-image blending and flexible aspect ratios. IBM Granite 4.0 introduces a hybrid Mamba/Transformer architecture with large context windows and strong token efficiency, outperforming some peers on the Intelligence Index. Qwen models receive updates including fine-tuning API support and improved vision capabilities. Tinker offers a flexible fine-tuning API supporting LoRA sharing and CPU-only training loops. The ecosystem also sees updates like Synthesia 3.0 adding video agents.
Thinking Machines' Tinker: LoRA based LLM fine-tuning API
qwen-235b-a22b sora-2 thinking-machines openai fine-tuning lora model-training api model-optimization distributed-training post-training-methods research-productivity video-generation content-moderation engagement-patterns karpathy lilianweng sama
Thinking Machines recently raised $2 billion without shipping a product until now, launching their first product Tinker, a managed service API for fine-tuning large and mixture-of-experts models like Qwen-235B-A22B using LoRA for cost-efficient training. The Tinker API offers low-level primitives for post-training methods and is supported by an open-source Tinker Cookbook library. Influential AI figures like Andrej Karpathy and Lilian Weng praised its design for reducing complexity and boosting research productivity. Meanwhile, OpenAI launched Sora 2, a video+audio model integrated into their consumer social app, sparking viral engagement and concerns over misuse and content moderation. Sam Altman emphasized the product's dual focus on delight and revenue alongside AGI research.
not much happened today
llama mistral openai decagon sierra togethercompute vertical-saas funding protein-structure-prediction lora self-supervised-learning model-optimization neural-architecture-search model-evaluation ethics transformers multi-agent-systems long-context mira-murati demis-hassabis clement-delangue john-o-whitaker yann-lecun francois-chollet ajeya-cotra rohan-paul adcock-brett
Vertical SaaS agents are gaining rapid consensus as the future of AI applications, highlighted by Decagon's $100m funding and Sierra's $4b round. OpenAI alumni are actively raising venture capital and forming new startups, intensifying competition in the AI market. Demis Hassabis celebrated the Nobel Prize recognition for AlphaFold2, a breakthrough in protein structure prediction. Advances in AI models include techniques like LoRA projectors and annealing on high-quality data, while discussions emphasize the need for high-bandwidth sensory inputs beyond language for common sense learning. New methods like LoLCATs aim to optimize transformer models such as Llama and Mistral for efficiency. Ethical concerns about AI agents performing harmful tasks remain under investigation. The AI community continues to explore model evaluation challenges and optimization frameworks like LPZero for neural architecture search.
GPT4o August + 100% Structured Outputs for All (GPT4o mini edition)
gpt-4o-mini gpt-4o-2024-08-06 llama-3 bigllama-3.1-1t-instruct meta-llama-3-120b-instruct gemma-2-2b stability-ai unsloth-ai google hugging-face lora controlnet line-art gpu-performance multi-gpu-support fine-tuning prompt-formatting cloud-computing text-to-image-generation model-integration
Stability.ai users are leveraging LoRA and ControlNet for enhanced line art and artistic style transformations, while facing challenges with AMD GPUs due to the discontinuation of ZLUDA. Community tensions persist around the r/stablediffusion subreddit moderation. Unsloth AI users report fine-tuning difficulties with LLaMA3 models, especially with PPO trainer integration and prompt formatting, alongside anticipation for multi-GPU support and cost-effective cloud computing on RunPod. Google released the lightweight Gemma 2 2B model optimized for on-device use with 2.6B parameters, featuring safety and sparse autoencoder tools, and announced Diffusers integration for efficient text-to-image generation on limited resources.
Andrew likes Agents
gpt-3.5 gpt-4 cyberrealistic_v40 platypus-xl sdxl-lightning openai stability-ai agents human-eval-benchmark fine-tuning local-llm-deployment inference-speed image-generation lora upscaling workflow-optimization andrew-ng lilian-weng emad
Andrew Ng's The Batch writeup on Agents highlighted the significant improvement in coding benchmark performance when using an iterative agent workflow, with GPT-3.5 wrapped in an agent loop achieving up to 95.1% correctness on HumanEval, surpassing GPT-4 zero-shot at 67.0%. The report also covers new developments in Stable Diffusion models like Cyberrealistic_v40, Platypus XL, and SDXL Lightning for Naruto-style image generation, alongside innovations in LoRA and upscaling techniques. Discussions on local LLM deployment and optimization focus on hardware setups and finetuning strategies for efficient inference and multi-user serving. Emad's departure from Stability AI and new Sora videos from OpenAI were also noted.
The Core Skills of AI Engineering
miqumaid olmo aphrodite awq exl2 mistral-medium internlm ssd-1b lora qlora loftq ai2 hugging-face ai-engineering quantization fine-tuning open-source model-deployment data-quality tokenization prompt-adherence distillation ai-security batching hardware role-playing eugene-yan
AI Discords for 2/2/2024 analyzed 21 guilds, 312 channels, and 4782 messages saving an estimated 382 minutes of reading time. Discussions included Eugene Yan initiating a deep dive into AI engineering challenges, highlighting overlaps between software engineering and data science skills. The TheBloke Discord featured talks on MiquMaid, OLMo (an open-source 65B LLM by AI2 under Apache 2.0), Aphrodite model batching, AWQ quantization, and LoRA fine-tuning techniques like QLoRA and LoftQ. The LAION Discord discussed SSD-1B distillation issues, data quality optimization with captioning datasets like BLIP, COCO, and LLaVA, and tokenization strategies for prompt adherence in image generation. Other topics included AI security with watermarking, superconductors and carbon nanotubes for hardware, and deployment of LLMs via Hugging Face tools.