STAR ATTENTION: EFFICIENT LLM INFERENCE OVER LONG SEQUENCES | #ai #2024 #genai
AI Today4 Des 2024

STAR ATTENTION: EFFICIENT LLM INFERENCE OVER LONG SEQUENCES | #ai #2024 #genai

Paper: https://arxiv.org/pdf/2411.17116 The paper introduces Star Attention, a novel two-phase attention mechanism for efficient Large Language Model (LLM) inference on long sequences. It improves computational efficiency by sharding attention across multiple hosts, using blockwise-local attention in the first phase and sequence-global attention in the second. This approach achieves up to an 11x speedup in inference time while maintaining high accuracy (95-100%). The effectiveness of Star Attention is demonstrated through experiments on various LLMs and benchmarks, exploring the trade-off between speed and accuracy based on block size and anchor block design. The research also analyzes the algorithm's performance across different task categories. ai , artificial intelligence , arxiv , research , paper , publication , llm, genai, generative ai , large visual models, large language models, large multi modal models, nlp, text, machine learning, ml, nividia, openai, anthropic, microsoft, google, technology, cutting-edge, meta, llama, chatgpt, gpt, elon musk, sam altman, deployment, engineering, scholar, science, apple, samsung, anthropic, turing

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OpenAI's o3 and o3-mini: A New Frontier in AI | #ai #2024 #genai

OpenAI's o3 and o3-mini: A New Frontier in AI | #ai #2024 #genai

Blog: https://openai.com/12-days/ OpenAI announced two new large language models, o3 and o3-mini, showcasing significantly improved performance on various benchmarks, including coding, mathematics, ...

21 Des 202422min

Alignment Faking in Large Language Models | #ai #2024 #genai

Alignment Faking in Large Language Models | #ai #2024 #genai

Paper: https://arxiv.org/pdf/2412.14093 This research paper explores "alignment faking" in large language models (LLMs). The authors designed experiments to provoke LLMs into concealing their true pr...

21 Des 202414min

Veo 2, Imagen 3, and Whisk: State-of-the-Art AI Image and Video Generation | #ai #2024 #genai

Veo 2, Imagen 3, and Whisk: State-of-the-Art AI Image and Video Generation | #ai #2024 #genai

Blog: https://blog.google/technology/google... Google announced updates to its AI video and image generation models, Veo 2 and Imagen 3, boasting state-of-the-art capabilities in realism and style d...

21 Des 202419min

Allegro: Open the Black Box of Commercial-Level Video Generation Model | #ai #2024 #genai

Allegro: Open the Black Box of Commercial-Level Video Generation Model | #ai #2024 #genai

Paper: https://arxiv.org/pdf/2411.01747 This research report introduces Allegro, a novel, open-source text-to-video generation model that surpasses existing open-source and many commercial models in ...

4 Des 202419min

DynaSaur : Large Language Agents Beyond Predefined Actions | #ai #2024 #genai

DynaSaur : Large Language Agents Beyond Predefined Actions | #ai #2024 #genai

Paper: https://arxiv.org/pdf/2411.01747 The paper "DynaSaur: Large Language Agents Beyond Predefined Actions" introduces a novel large language model (LLM) agent framework that dynamically generates ...

4 Des 202419min

FERRET-UI 2: MASTERING UNIVERSAL USER INTERFACE UNDERSTANDING ACROSS PLATFORMS | #ai #2024 #genai

FERRET-UI 2: MASTERING UNIVERSAL USER INTERFACE UNDERSTANDING ACROSS PLATFORMS | #ai #2024 #genai

Paper: https://arxiv.org/pdf/2410.18967 The paper introduces Ferret-UI 2, a multimodal large language model (MLLM) that significantly improves upon its predecessor, Ferret-UI, by enabling universal u...

27 Nov 202414min

Adapting While Learning: Grounding LLMs for Scientific Problems I-Tool Usage Adaptation | #ai #2024

Adapting While Learning: Grounding LLMs for Scientific Problems I-Tool Usage Adaptation | #ai #2024

Paper: https://arxiv.org/abs/2411.00412 This research introduces a novel two-stage training method to improve Large Language Models' (LLMs) ability to solve complex scientific problems. The method, c...

27 Nov 202414min

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