{"id":61879,"date":"2024-03-04T12:01:48","date_gmt":"2024-03-04T04:01:48","guid":{"rendered":"http:\/\/www.upgrademag.com\/web\/?p=61879"},"modified":"2024-03-04T12:01:52","modified_gmt":"2024-03-04T04:01:52","slug":"ibm-announces-availability-of-open-source-mistral-ai-model-on-watsonx","status":"publish","type":"post","link":"http:\/\/www.upgrademag.com\/web\/2024\/03\/04\/ibm-announces-availability-of-open-source-mistral-ai-model-on-watsonx\/","title":{"rendered":"IBM announces availability of open-source Mistral AI model on watsonx"},"content":{"rendered":"\n

IBM announced the availability of the popular open-source Mixtral-8x7B large language model (LLM), developed by Mistral AI, on its\u00a0watsonx AI\u00a0and data platform, as it continues to expand capabilities to help clients innovate with IBM’s own foundation models and those from a range of open-source providers.<\/strong><\/p>\n\n\n\n

IBM offers an optimized version of Mixtral-8x7B that, in internal testing, was able to increase throughput \u2014 or the amount of data that can be processed in a given time period \u2014 by 50 percent when compared to the regular model.\u00a0This could potentially cut latency by 35-75 percent, depending on batch size \u2014 speeding time to insights. This is achieved through a process called quantization, which reduces model size and memory requirements for LLMs and, in turn, can speed up processing to help lower costs and energy consumption.<\/p>\n\n\n\n

The addition of Mixtral-8x7B expands IBM’s open,\u00a0multi-model strategy\u00a0to meet clients where they are and give them choice and flexibility to scale\u00a0enterprise AI\u00a0solutions across their businesses. Through decades-long AI research and development, open collaboration with\u00a0Meta\u00a0and\u00a0Hugging Face, and partnerships with\u00a0model leaders, IBM is expanding its watsonx.ai model catalog and bringing in new capabilities, languages, and modalities.<\/p>\n\n\n\n

IBM’s enterprise-ready\u00a0foundation model\u00a0choices and its watsonx AI and data\u00a0platform can empower clients to use\u00a0generative AI\u00a0to gain new insights and\u00a0efficiencies, and create new business models based on principles of trust. IBM\u00a0enables clients to select the right model for the right use cases and price-performance goals for targeted business domains like finance.<\/p>\n\n\n\n

Mixtral-8x7B was built using a combination of Sparse modeling \u2014 an innovative technique that finds and uses only the most essential parts of data to create more efficient models \u2014 and the Mixture-of-Experts technique, which combines different models (“experts”) that specialize in and solve different parts of a problem. The Mixtral-8x7B model is widely known for its ability to rapidly process and analyze vast amounts of data to provide context-relevant insights.<\/p>\n\n\n\n

“Clients are asking for choice and flexibility to deploy models that best suit their unique use cases and business requirements,” said Kareem Yusuf, Ph.D, Senior Vice President, Product Management & Growth, IBM Software. “By offering Mixtral-8x7B and other models on watsonx, we’re not only giving them optionality in how they deploy AI \u2014 we’re empowering a robust ecosystem of AI builders and business leaders with tools and technologies to drive innovation across diverse industries and domains.” <\/p>\n\n\n\n

This week, IBM also announced the availability of ELYZA-japanese-Llama-2-7b, a Japanese LLM model open-sourced by ELYZA Corporation, on watsonx. IBM also offers Meta’s open-source models Llama-2-13B-chat and Llama-2-70B-chat and other third-party models on watsonx, with more to come in the next few months.<\/p>\n","protected":false},"excerpt":{"rendered":"

IBM offers an optimized version of Mixtral-8x7B that, in internal testing, was able to increase throughput \u2014 or the amount of data that can be processed in a given time period \u2014 by 50 percent when compared to the regular model<\/p>\n","protected":false},"author":6,"featured_media":57236,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[19],"tags":[214,96,2727,1656,7016],"class_list":["post-61879","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-headlines","tag-ibm","tag-technology","tag-technology-adaption","tag-technology-investment","tag-watson"],"_links":{"self":[{"href":"http:\/\/www.upgrademag.com\/web\/wp-json\/wp\/v2\/posts\/61879","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/www.upgrademag.com\/web\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.upgrademag.com\/web\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.upgrademag.com\/web\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"http:\/\/www.upgrademag.com\/web\/wp-json\/wp\/v2\/comments?post=61879"}],"version-history":[{"count":0,"href":"http:\/\/www.upgrademag.com\/web\/wp-json\/wp\/v2\/posts\/61879\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/www.upgrademag.com\/web\/wp-json\/wp\/v2\/media\/57236"}],"wp:attachment":[{"href":"http:\/\/www.upgrademag.com\/web\/wp-json\/wp\/v2\/media?parent=61879"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.upgrademag.com\/web\/wp-json\/wp\/v2\/categories?post=61879"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.upgrademag.com\/web\/wp-json\/wp\/v2\/tags?post=61879"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}