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Welcome to this week's edition of AlphaSignal.
Whether you are a researcher, engineer, developer, or data scientist, our summaries ensure you're always up-to-date with the latest breakthroughs in AI.
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Lior
In Today’s Email:
Top Releases and Announcements in the Industry
OpenAI board fires Sam Altman, gets hired by Microsoft
NVIDIA Introduces Nemotron-3 8B
Scientist’s new focus on trillion parameter models
Read Time: 4 min 47 sec
RELEASES & ANNOUNCEMENTS
Meta’s Emu Video is a new AI tool for creating 4-second, 512x512 resolution videos at 16 FPS from text prompts. It uses a two-step process: first generating an image from text, then adding motion, enhancing video generation efficiency. Available now.
Multimodal LLMs, for everyone, for free. That is the promise of Kyutai, a new Paris-based non-profit AI lab co-founded by former Google DeepMind talent. It aims to develop muodal large language models (LLMs) accessible to everyone for free, prioritizing scientific advancement without distractions.
The model excels at generating high-quality music with instrumentals and vocals, performing transformation and continun tasks, and giving users more nuanced control of the output’s style and performance. In partnership with YouTube, DeepMind will run two new AI music experiments: Dream Track and Music AI tools.
With 141 GB memory, NVIDIA's H200 Tensor Core GPU achieves nearly double the inference speed for generative AI inference applications compared to the H100. The AI accelerator is set for release in Q2 2024.
At their Ignite conference, Microsoft introduced new models to the Azure AI model catalog, including Nemotron-3 8B, Code Llama, and Mistral. They also introduced 'Models as a Service' (MaaS) for easier AI model integration and customization.
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NEWS
OpenAI Board Fires Sam Altman, Replaces with Twitch Founder, Emmett Shear
What's New?
OpenAI has seen dramatic leadership changes: CEO Sam Altman was fired, co-founder Greg Brockman resigned, and CTO Mira Murati became interim CEO. This was followed by the appointment of Twitch co-founder Emmett Shear as another interim CEO.
Subsequently, Microsoft hired Altman and Brockman to head a new AI research unit. Furthermore, three senior OpenAI executives resigned, and over 500 employees signed a letter demanding the board's resignation.
Why Does It Matter?
These shifts are significant for the AI research community as they could influence the direction of future AI developments. OpenAI, known for its groundbreaking work in generative AI systems like ChatGPT and DALL-E, might see a shift in its research and commercialization approach under Shear.
Key Takeaways:
OpenAI CEO Altman fired, Brockman resigns; Microsoft hires both for new AI research unit.
Emmett Shear’s appointment as OpenAI’s interim CEO may signal a shift in research and commercial strategies.
Over 500 OpenAI employees voiced concerns, reflecting potential internal challenges and discontent.
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NEWS
NVIDIA Introduces Nemotron-3 8B to Revolutionize Enterprise AI Development
What's New?
NVIDIA has introduced the Nemotron-3 8B family, a set of generative foundation models within its NeMo framework. This family of models is designed to improve enterprise AI applications, and includes base, chat, and question-and-answer checkpoints.
The Nemotron-3 8B models are available on the Azure AI Model Catalog, HuggingFace, and the NVIDIA AI Foundation Model hub, and can be fine-tuned for custom use cases.
Why Does It Matter?
Nvidia’s NeMo framework enables enterprises to quickly implement AI applications across various environments. The Nemotron-3 8B family gives developers an easy way to integrate foundation models and fine-tuned versions of these models into enterprise-specific requirements.
Main Takeaways
Versatile AI Models: Nemotron-3 8B supports extensive languages and coding options, suitable for diverse enterprise needs.
Customizable Solutions: It provides base, Q&A, and 3 chat model variants — SFT, RLHF, and SteerLM — allowing for diverse user interactions.
Optimal Performance: Integration with TensorRT-LLM and NVIDIA Triton Inference Server ensures low-latency, high accuracy inference.
Comprehensive Framework: NVIDIA's NeMo allows easier model building, customization, and deployment.
NEWS
Scientists Join Forces to Focus on Trillion Parameters Models
What's New?
The Trillion Parameter Consortium (TPC) is a collaborative effort aiming to develop AI models with over a trillion parameters. This initiative stands out for its focus on large-scale model architecture and data management, utilizing exascale computing resources. It brings together expertise from various sectors, including federal labs, academia, and industry, to tackle the practical challenges of scalable AI development.
Why Does It Matter?
For those in the field, TPC represents a practical approach to surmount existing limitations in AI model training and data processing. Its emphasis on optimizing AI libraries for exascale computing and developing effective evaluation methodologies addresses some of the key technical challenges in advancing AI applications in scientific research.
Main Takeaways
Global Collaboration: TPC builds a community of researchers to tackle the complexities of building large-scale AI models.
Focus on Trustworthy AI: Emphasizes developing scalable, reliable AI models for scientific tasks.
Interdisciplinary Approach: Aims to create models that integrate knowledge across various scientific fields.
Leveraging Exascale Computing: Utilizes emerging exascale computing platforms for training large language models.
Read Last Week’s Summaries:
News: 🍎 The First AI App Store?
Technical: 🌐 Can GPT Control Your Browser?
Research: 🥇 The 5 AI Papers You Should Read This Week
Thank You
Igor Tica is a contributing writer at AlphaSignal and a research engineer at SmartCat, focusing on computer vision. He's actively seeking partnerships in self-supervised and contrastive learning.
Jacob Marks is an editor at AlphaSignal and ML engineer at Voxel51, is recognized as a leading AI voice on Medium and LinkedIn. Formerly at Google X and Samsung, he holds a Ph.D. in Theoretical Physics from Stanford.
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