All tags
Topic: "privacy"
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.
>$41B raised today (OpenAI @ 300b, Cursor @ 9.5b, Etched @ 1.5b)
deepseek-v3-0324 gemini-2.5-pro claude-3.7-sonnet openai deepseek gemini cursor etched skypilot agent-evals open-models model-releases model-performance coding multimodality model-deployment cost-efficiency agent-evaluation privacy kevinweil sama lmarena_ai scaling01 iscienceluvr stevenheidel lepikhin dzhng raizamrtn karpathy
OpenAI is preparing to release a highly capable open language model, their first since GPT-2, with a focus on reasoning and community feedback, as shared by @kevinweil and @sama. DeepSeek V3 0324 has achieved the #5 spot on the Arena leaderboard, becoming the top open model with an MIT license and cost advantages. Gemini 2.5 Pro is noted for outperforming models like Claude 3.7 Sonnet in coding tasks, with upcoming pricing and improvements expected soon. New startups like Sophont are building open multimodal foundation models for healthcare. Significant fundraises include Cursor closing $625M at a $9.6B valuation and Etched raising $85M at $1.5B. Innovations in AI infrastructure include SkyPilot's cost-efficient cloud provisioning and the launch of AgentEvals, an open-source package for evaluating AI agents. Discussions on smartphone privacy highlight iPhone's stronger user defense compared to Android.
not much happened this weekend
claude-3.5-sonnet llama-3 llama-3-8b notebookllama min-omni-2 moondream openai anthropic hugging-face mistral-ai google-deepmind langchain deepmind microsoft pattern-recognition reinforcement-learning prompt-optimization text-to-speech model-optimization tensor-parallelism hyperparameters multimodal modal-alignment multimodal-fine-tuning ai-productivity privacy generative-ai rag retrieval-augmentation enterprise-text-to-sql amanda-askell philschmid stasbekman francois-fleuret mervenoyann reach_vb dzhng aravsrinivas sama lateinteraction andrew-y-ng bindureddy jerryjliu0
Moondream, a 1.6b vision language model, secured seed funding, highlighting a trend in moon-themed tiny models alongside Moonshine (27-61m ASR model). Claude 3.5 Sonnet was used for AI Twitter recaps. Discussions included pattern recognition vs. intelligence in LLMs, reinforcement learning for prompt optimization, and NotebookLlama, an open-source NotebookLM variant using LLaMA models for tasks like text-to-speech. Advances in model optimization with async-TP in PyTorch for tensor parallelism and hyperparameter tuning were noted. Mini-Omni 2 demonstrated multimodal capabilities across image, audio, and text for voice conversations with emphasis on modal alignment and multimodal fine-tuning. AI productivity tools like an AI email writer and LlamaCloud-based research assistants were introduced. Emphasis on practical skill development and privacy-conscious AI tool usage with Llama3-8B was highlighted. Generative AI tools such as #AIPythonforBeginners and GenAI Agents with LangGraph were shared. Business insights covered rapid execution in AI product development and emerging AI-related job roles. Challenges in enterprise-grade text-to-SQL and advanced retrieval methods were discussed with tutorials on RAG applications using LangChain and MongoDB.
Not much (in AI) happened this weekend
llama-3.1-8b llama-3.2 chatgpt movie-gen openai meta-ai-fair google-deepmind microsoft x-ai spacex harvard nvidia long-context feature-prediction-loss ai-agents privacy text-to-video text-to-image humanoid-robots gpu-deployment media-foundation-models ai-research-labs sam-altman yann-lecun rasbt bindureddy andrej-karpathy soumithchintala svpino adcock_brett rohanpaul_ai
OpenAI introduced an "edit this area" feature for image generation, praised by Sam Altman. Yann LeCun highlighted a NYU paper improving pixel generation with feature prediction loss using pre-trained visual encoders like DINOv2. Long-context LLMs such as llama-3.1-8b and llama-3.2 variants now support up to 131k tokens, offering alternatives to RAG systems. Bindu Reddy announced AI agents capable of building and deploying code from English instructions, signaling AI's replacement of SQL and potential impact on Python. SpaceX's successful Starship rocket catch was celebrated by Andrej Karpathy and others, with Soumith Chintala praising SpaceX's efficient, low-bureaucracy research approach. Privacy concerns arose from Harvard students' AI glasses, I-XRAY, which can reveal personal information. Meta AI FAIR's Movie Gen model advances media foundation models with high-quality text-to-image and video generation, including synced audio. Humanoid robots like Ameca and Azi now engage in expressive conversations using ChatGPT. xAI rapidly deployed 100K Nvidia H100 GPUs in 19 days, with CEO Jensen Huang commending Elon Musk. Leading AI research labs compared include Meta-FAIR, Google DeepMind, and Microsoft Research. Skepticism about LLM intelligence was voiced by Sam Pino, emphasizing limitations in novel problem-solving despite strong memorization.
AIPhone 16: the Visual Intelligence Phone
reflection-70b llama-3-70b qwen-2-72b llama-3-1-405b claude gpt-4 gemini apple openai weights-biases vision video-understanding benchmarking planning model-evaluation privacy ai-integration instruction-following yann-lecun
Apple announced the new iPhone 16 lineup featuring Visual Intelligence, a new AI capability integrated with Camera Control, Apple Maps, and Siri, emphasizing privacy and default service use over third-party AI like OpenAI. Apple Photos now includes advanced video understanding with timestamp recognition. Meanwhile, Reflection-70B claims to be a top open-source model but benchmarks show it performs close to Llama 3 70B and slightly worse than Qwen 2 72B. Yann LeCun highlighted ongoing challenges with LLM planning abilities, noting models like Llama-3.1-405b and Claude show some skill, while GPT-4 and Gemini lag behind. Weights & Biases is sponsoring an event to advance LLM evaluation techniques with prizes and API access.
Francois Chollet launches $1m ARC Prize
gpt-4 chatgpt openai apple togethercompute benchmarking agi pattern-recognition skill-acquisition privacy on-device-ai mixed-precision-quantization mixture-of-experts multimodality agentic-ai francois-chollet karpathy svpino philschmid clementdelangue sama gdb miramurati kevin-weil sarah-friar
François Chollet critiques current paths to AGI, emphasizing the importance of benchmarks that resist saturation and focus on skill acquisition and open-ended problem solving. The ARC-AGI puzzles exemplify "easy for humans, hard for AI" challenges to measure progress toward AGI. Meanwhile, Apple announces integration of ChatGPT into iOS, iPadOS, and macOS through a partnership with OpenAI, enabling AI-powered features like document summarization and photo analysis with privacy-preserving measures. Discussions highlight Apple's focus on deep AI integration and on-device models optimized with techniques like mixed-precision quantization, though some skepticism remains about their AI capabilities compared to GPT-4. Additionally, Together Compute introduces a Mixture of Agents approach achieving strong performance on AlpacaEval 2.0.
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.
1/6-7/2024: LlaMA Pro - an alternative to PEFT/RAG??
llama-3 llama-3-1-1b llama-3-8-3b gpt-4 gpt-3.5 dall-e openai mistral-ai llamaindex langchain fine-tuning model-expansion token-limits privacy multilinguality image-generation security custom-models model-training yannic-kilcher
New research papers introduce promising Llama Extensions including TinyLlama, a compact 1.1B parameter model pretrained on about 1 trillion tokens for 3 epochs, and LLaMA Pro, an 8.3B parameter model expanding LLaMA2-7B with additional training on 80 billion tokens of code and math data. LLaMA Pro adds layers to avoid catastrophic forgetting and balances language and code tasks but faces scrutiny for not using newer models like Mistral or Qwen. Meanwhile, OpenAI Discord discussions reveal insights on GPT-4 token limits, privacy reassurances, fine-tuning for GPT-3.5, challenges with multi-language image recognition, custom GPT creation requiring ChatGPT Plus, and security concerns in GPT deployment. Users also share tips on dynamic image generation with DALL-E and logo creation.
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.