Meta\u2019s research team introduced<\/a> Llama 3.1 on July 23, 2023, calling it \u201cthe world\u2019s largest and most capable openly available foundation model.\u201d<\/p>\n Llama 3.1 is available in various parameter sizes \u2014 8B, 70B, and 405B \u2014 providing flexibility for deployment based on computational resources and specific application needs. On April 18, 2024, Meta announced<\/a> the Llama 3 family of large language models<\/a>, which initially included only the 8B and 70B sizes. This latest release introduced the 405B model along with upgraded versions of the 8B and 70B models.<\/p>\n Llama 3.1 models represent a significant advancement over their predecessor, Llama 2, being pre-trained on an extensive corpus of 15 trillion multilingual tokens, a substantial increase from Llama 2\u2019s 1.8 trillion tokens. With a context window of up to 128k tokens \u2014 previously limited to 8k tokes \u2014 they offer notable improvements in multilinguality, coding, reasoning, and tool usage.<\/p>\n var AdButler = AdButler || {}; AdButler.ads = AdButler.ads || []; Llama 3.1 maintains a similar architecture to Llama and Llama 2 but achieves performance improvements through enhanced data quality, diversity, and increased training scale.\u00a0<\/p>\n Meta\u2019s research team tested Llama 3.1 on over 150 benchmark datasets covering a wide range of languages. They found that their \u201cflagship model\u201d with 405B parameters is competitive with leading models<\/a> across various tasks and is close to matching the state-of-the-art performance. The smaller models are also \u201cbest-in-class,\u201d outperforming alternative models with comparable numbers of parameters.\u00a0<\/p>\n In multilingual tasks, the small Llama 3.1 8B model surpassed Gemma 2 9B and Mistral 7B, while Llama 3.1 70B outperformed Mixtral 8Xx22B and GPT 3.5 Turbo. Llama 3.1 405B is on par with Claude 3.5 Sonnet and outperformed GPT-4<\/a> and GPT 4o<\/a>.<\/p>\n Meta\u2019s research team emphasized that Llama 3.1 405B is \u201cthe first openly available model that rivals the top AI models when it comes to state-of-the-art capabilities in [\u2026] multilingual translation,\u201d among other tasks.<\/p>\n They expressed optimism about the potential for creating innovative applications leveraging the model\u2019s multilingual capabilities and extended context length, stating, \u201cwe can\u2019t wait to see what the community does with this work.\u201d.<\/p>\n var AdButler = AdButler || {}; AdButler.ads = AdButler.ads || []; In addition to language processing, the development of Llama 3.1 included multimodal extensions that enable image recognition, video recognition, and speech understanding capabilities.<\/p>\n Although these multimodal extensions are still under development, initial results indicate competitive performance in image, video, and speech tasks.<\/p>\n Meta\u2019s research team specifically evaluated Llama 3.1 on automatic speech recognition<\/a> (ASR) and speech translation<\/a>. In ASR<\/a>, they compared its performance against Whisper<\/a>, SeamlessM4T, and Gemini. Llama 3.1 outperformed Whisper and SeamlessM4T across all benchmarks and performed similarly to Gemini, demonstrating \u201cstrong performance on speech recognition<\/a> tasks.\u201d\u00a0<\/p>\n In speech translation tasks, where the model was asked to translate non-English speech into English text, Llama 3.1 again outperformed Whisper and SeamlesM4T. \u201cThe performance of our models in speech translation highlights the advantages of multimodal foundation models for tasks such as speech translation,\u201d Meta\u2019s team said.<\/p>\n They also shared details of the development process to help the research community understand the key factors of multimodal foundation model development and encourage informed discussions about the future of these models. \u201cWe hope sharing our results early will accelerate research in this direction,\u201d they said.<\/p>\n Meta\u2019s launch of Llama 3.1 has created a buzz in the AI community. Since the release, many people have taken to X and LinkedIn to call it a \u201cgame-changer<\/a>\u201d or \u201cGPT-4 killer<\/a>,\u201d recognizing this moment as \u201cthe biggest moment for open-source AI<\/a>.\u201d Additionally, they have talked about a \u201cseismic shift in business transformation<\/a>,\u201d explaining that this is going to \u201crevolutionize how companies work.\u201d\u00a0<\/p>\n Posts are filled with examples showing the many different ways Llama 3.1 can be used<\/a>, building from phone assistants<\/a> to document assistants<\/a> and code assistants<\/a>.<\/p>\n
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\n})(); <\/p><\/div>\nSOTA Capabilities in Multilingual Translation<\/h3>\n
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\n})(); <\/p><\/div>\nStrong Performance on Speech Translation<\/h3>\n
![\"10](\"https:\/\/slator.com\/assets\/2023\/10\/10-LLM-Use-Cases-Main-Title-210x297.png\")
<\/div>\nSlator Pro Guide: Translation AI<\/h2>\n
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