{"id":85041,"date":"2025-03-25T18:00:21","date_gmt":"2025-03-26T01:00:21","guid":{"rendered":"https:\/\/phisonblog.com\/?p=85041"},"modified":"2025-04-15T18:41:07","modified_gmt":"2025-04-16T01:41:07","slug":"phison-storage-news-ticker-march-24","status":"publish","type":"post","link":"https:\/\/phisonblog.com\/de\/phison-storage-news-ticker-march-24\/","title":{"rendered":"Phison \u2013 Storage-News-Ticker vom 24. M\u00e4rz"},"content":{"rendered":"

[et_pb_section fb_built=”1″ _builder_version=”4.16″ global_colors_info=”{}”][et_pb_row _builder_version=”4.16″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” global_colors_info=”{}”]”Phison<\/strong>\u00a0has updated its\u00a0aiDAPTIV+<\/a>\u00a0\u201caffordable AI training and inferencing solution for on-premises environments.\u201d Customers will be able to fine-tune large language models (LLMs) up to 8 billion parameters using their own data. The new aiDAPTIVLink 3.0 middleware provides faster time to first token (TTFT) recall and extends the token length for greater context, improving inference performance and accuracy. A\u00a0Maingear AI laptop PC<\/a>\u00a0concept was demonstrated at GTC 2025 using aiDAPTIVCache SSDs, aiDAPTIVLink middleware, and a Pro Suite GUI-based all-in-one feature set for LLMOps, including ingest, fine-tuning, RAG, monitoring, validation, and inference.<\/p>\n

It says\u00a0aiDAPTIV+<\/a>\u00a0is a budget-friendly, GPU memory extension capability allowing users to train an LLM with their data within an on-premises\u00a0\u201cclosed-loop\u201d secure network<\/a>, while providing a simple user interface to interact with and ask questions about the data. AI Inference for IoT with aiDAPTIV+ now supports edge computing and robotics use cases with Phison\u2019s validation of Nvidia Jetson-based devices.”- blocksandfiles.com<\/p>\n

Source: blocksandfiles.com<\/a>
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“Phison\u00a0has updated its\u00a0aiDAPTIV+\u00a0\u201caffordable AI training and inferencing solution for on-premises environments.\u201d Customers will be able to fine-tune large language models (LLMs) up to 8 billion parameters using their own data. The new aiDAPTIVLink 3.0 middleware provides faster time to first token (TTFT) recall and extends the token length for greater context, improving inference performance and […]<\/p>\n","protected":false},"author":10,"featured_media":85042,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"

\"Phison<\/strong>\u00a0has updated its\u00a0aiDAPTIV+<\/a>\u00a0\u201caffordable AI training and inferencing solution for on-premises environments.\u201d Customers will be able to fine-tune large language models (LLMs) up to 8 billion parameters using their own data. The new aiDAPTIVLink 3.0 middleware provides faster time to first token (TTFT) recall and extends the token length for greater context, improving inference performance and accuracy. A\u00a0Maingear AI laptop PC<\/a>\u00a0concept was demonstrated at GTC 2025 using aiDAPTIVCache SSDs, aiDAPTIVLink middleware, and a Pro Suite GUI-based all-in-one feature set for LLMOps, including ingest, fine-tuning, RAG, monitoring, validation, and inference.<\/p>

It says\u00a0aiDAPTIV+<\/a>\u00a0is a budget-friendly, GPU memory extension capability allowing users to train an LLM with their data within an on-premises\u00a0\u201cclosed-loop\u201d secure network<\/a>, while providing a simple user interface to interact with and ask questions about the data. AI Inference for IoT with aiDAPTIV+ now supports edge computing and robotics use cases with Phison\u2019s validation of Nvidia Jetson-based devices.\"- blocksandfiles.com<\/p>

Source: blocksandfiles.com<\/a><\/p>","_et_gb_content_width":"","inline_featured_image":false,"footnotes":""},"categories":[114],"tags":[22],"class_list":["post-85041","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-phison-in-the-news","tag-long-content"],"acf":[],"_links":{"self":[{"href":"https:\/\/phisonblog.com\/de\/wp-json\/wp\/v2\/posts\/85041","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/phisonblog.com\/de\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/phisonblog.com\/de\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/phisonblog.com\/de\/wp-json\/wp\/v2\/users\/10"}],"replies":[{"embeddable":true,"href":"https:\/\/phisonblog.com\/de\/wp-json\/wp\/v2\/comments?post=85041"}],"version-history":[{"count":4,"href":"https:\/\/phisonblog.com\/de\/wp-json\/wp\/v2\/posts\/85041\/revisions"}],"predecessor-version":[{"id":85207,"href":"https:\/\/phisonblog.com\/de\/wp-json\/wp\/v2\/posts\/85041\/revisions\/85207"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/phisonblog.com\/de\/wp-json\/wp\/v2\/media\/85042"}],"wp:attachment":[{"href":"https:\/\/phisonblog.com\/de\/wp-json\/wp\/v2\/media?parent=85041"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/phisonblog.com\/de\/wp-json\/wp\/v2\/categories?post=85041"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/phisonblog.com\/de\/wp-json\/wp\/v2\/tags?post=85041"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}