[AINews] super quiet day • ButtondownTwitterTwitter

The section provides a detailed recap of discussions on AI Twitter and Reddit, covering a range of topics such as AI models' evaluations, safety concerns, legislation, new tools and innovations, conferences and meetups, and even humor and memes. The Twitter recap discusses releases from AI21 Labs, safety legislation like SB 1047, new tools like uV virtual environments, and updates from LangChain and LangSmith. Meanwhile, the Reddit recap delves into discussions from /r/LocalLlama, touching on topics like Microsoft's Phi-3.5 models and their capabilities and controversies.

The section discusses recent developments in AI image generation and training. It includes the release of Ideogram 2.0, a text-to-image model available for free, as well as advancements in LoRA training techniques. Users have shared successful LoRA training experiences on different GPUs. Additionally, the introduction of Triton INT8 outperforming BF16, Flash Attention's FP8 support on Hopper architecture, and internship opportunities at HRT in NYC are highlighted.

7900 XTX vs. RTX 3090 Performance: Users reported that the 7900 XTX underperformed against the 3090, even when utilizing Triton and an FA fork, prompting users to switch to 4090s.

• Such experiences highlight the persistent gaps in performance between AMD's and NVIDIA's GPU offerings.

• Stable FP8 Training Achieved for LLaMA: Recent discussions highlighted stable FP8 training for a 1B LLaMA model, achieving convergence similar to bfloat16 training.

• Key techniques include moderating training speeds and managing outlier features, paving the way for larger-scale FP8 applications.

Ideogram 2.0 Launch: Free for Everyone:

• Ideogram 2.0 is released for free and includes an iOS app, Beta API, and Ideogram Search with over 1 billion images created.
  • Noted as 'the season of sequels' by AI News for continued buzz around features and performance.

Nvidia's New Mistral-NeMo-Minitron-8B:

• Nvidia launches Mistral-NeMo-Minitron-8B, outperforming Mistral-7B and LLaMa-3.1-8B across benchmarks.
  • It was built using 400B tokens for effective training, highlighted by Philipp Schmid.

The hardware discussion in this section covers various topics related to running large models efficiently. Some key points include: the limitations of SLI in doubling speed, the importance of GPU memory for smooth performance, the suggestion of increasing system RAM as an alternative, the recommendation of waiting for new hardware releases for better value, and specific GPU recommendations for running large models effectively. Additionally, the discussion touches on the HackAI Challenge offering an RTX 6000 as a prize and the considerations when using prepaid cards for online transactions.

This section discusses various topics related to HuggingFace, including queries about using Swin Transformers as the backbone for Mask R-CNN, challenges in multilingual NLP research, and techniques for fine-tuning diffusion models with LoRA. It also covers the launch of new datasets focusing on empathy and love in AI, discussions on heroism and hope in modern culture, and the use of the Living AI Dataset to enhance speech technologies. Additionally, it addresses technical issues such as Mistral 7B fine-tuning errors, Unsloth installation queries, Ollama usage problems, issues with fixed temperature and seed in inference, and concerns related to saving pre-trained models for fine-tuning.

The section discusses how Aider generates its own code, with the team envisioning a future where Aider writes 100% of its code. However, concerns about AI autonomy are raised. OpenRouter is presented as an alternative to Aider, offering flexibility and cost-effectiveness for users reaching API limits. The discussion delves into making Aider more cost-effective. Additionally, there are details about AI integration with Sonnet, optimizing token usage, and the potential risks of overreliance on Git for version control.

CUDA MODE 🚀

• beginner: Users seeking a good CUDA intro and recommendations for resources.
• youtube-recordings: Reference to lecture recordings available in the channel.
• torchao: Discussions on various topics including Adam Optimizer, Character AI training, and TensorCore support.
• sequence-parallel: Sharing of a tree-based link from June.
• off-topic: Conversations about remote work contracts and office transitions.
• irl-meetup: Details about the Triton Conference happening in Fremont.
• hqq-mobius: Discussion on model distillation and sparsification techniques.
• llmdotc: Updates on H100 GPU performance, FP8 training stability, and more.
• rocm: Insights on RDNA4 architecture, AMD GPU performance, and Torch Lightning training.
• cudamode-irl: Conversation snippet about a user feeling rejected from a list.

Links Mentioned:

• Optimization Level | MS-AMP: Detailed information on three optimization levels supported by MS-AMP.
• forward_with_matmul_register.py: GitHub Gist for code sharing.
• GitHub - thu-ml/Jetfire-INT8Training: Repository for Jetfire INT8Training project.
• GitHub - mobiusml/hqq: Implementation of Half-Quadratic Quantization (HQQ).
• 4 bit Adam should support non constant lr · Issue #730 · pytorch/ao: Discussion on limitations of the 4-bit Adam optimizer.
• GitHub - google/aqt: Repository for aqt project development.
• NVIDIA Hopper Architecture In-Depth | NVIDIA Technical Blog: Insights on the new H100 GPU architecture.

• The Nous Research merch store has launched, offering a variety of items for fans to show their support.
• Stickers will be included with each order while supplies last.
• Link to Nous Research Store

Lore's Potential Reproductive Frustration

A psychological analysis explores whether Lore's emotional instability in Star Trek: The Next Generation could be linked to an inability to have offspring. It draws parallels with other science fiction narratives exploring the desire for reproduction and legacy in artificial beings.

Microplastics Found in Human Brains

Researchers discovered microplastics in human brain samples at alarmingly high concentrations, raising concerns about long-term health implications. This discovery suggests that the brain is a major site of microplastic accumulation, highlighting the potential danger of plastic pollution on human health.

Planning for a Successful Retirement

Retirement is portrayed as a crucial transition requiring careful planning, including financial management, health maintenance, and social engagement. The article emphasizes the importance of finding fulfilling second careers, maintaining healthy habits, and managing investments for a secure and satisfying retirement.

Jonathan Ive's San Francisco Investment Spree

Sir Jonathan Ive, former Apple design chief, has invested heavily in San Francisco's Jackson Square neighborhood, acquiring properties worth over $137 million. His investment signals ambitious plans for the area, indicating a significant transformation led by a prominent figure in the design world.

The Effects of Nightcore Music

Nightcore, a genre characterized by sped-up and pitch-shifted music, has gained popularity on platforms like TikTok. While the genre may offer temporary mood boosts and stress reduction, the long-term mental health effects of Nightcore remain uncertain and require further research.

The ModelKit feature in Jozu Hub helps in understanding AI project components like data sets, code, parameters, and models. The team is working on integrating support for Cohere models on the platform to host major models like Cohere. This integration aims to provide users with a wide range of hosted models for their AI projects.

The Jamba 1.5 models have been introduced by AI21 Labs, including the Jamba 1.5 Mini and Jamba 1.5 Large versions. These models are powered by the SSM-Transformer Jamba architecture combining quality and efficiency. Jamba 1.5 Mini offers superior performance on Arena Hard scoring, while Jamba 1.5 Large surpasses models like Llama 3.1 70B and 405B. Both models support multiple languages and come with features like JSON output support and function calling. They have a long context window and are available for download on platforms like Hugging Face and major cloud services. The release marks a milestone in non-Transformer models achieving top-notch quality. The Jamba 1.5 models provide exceptional speed, efficiency, and quality, setting a new standard for long-context models.

The OASST-2 dataset and Aya-Dataset both offer German subsets that are suitable for instruction tuning. Other German datasets like Colossal Cleaned Common Crawl and German Wikipedia may also be useful, but require filtering and curation. Additionally, creating a custom dataset by translating English instruction data into German could prove beneficial for specific tasks. Lastly, open sourcing a model based on 8x8b Llama 3.1 with both German and English instruction tuning could be a valuable contribution to the NLP community.