The problem is that as a user goes on and on with an LLM, it has to remember what the original prompt instructions were as well as updates. Those can be recalculated again or stored as a reference. The problem is that AI functions are typically processed in video RAM or system RAM that\u2019s shared with the GPU. The result? Everything bogs down.<\/p>\n
Since RAM is where AI functions are computed, robbing a portion of it to \u201cstore\u201d data lessens its effectiveness. <\/p>\n
But there\u2019s a solution and it\u2019s one you\u2019re probably already familiar with. Microsoft Word runs on your PC\u2019s CPU and uses RAM to do it, but documents are stored in the cloud or in the SSD. If Word needs a document, it asks Windows to retrieve it from your SSD. Phison does something similar.<\/p>\n
What Phison\u2019s aiDAPTIV does is use high-performance, extreme-endurance NAND flash as an AI cache, storing tokens to be recalled for later use. (Technically, the cache stores the key-value (KV) data, which grows with the context length and model size.) Normally, this would slow down the entire process. What aiDAPTIV tries to do is anticipate the model\u2019s needs, intelligently sending data back and forth between the RAM and the SSD to allow you to run larger models without impacting performance.<\/p>\n
![\"Phison](\"https:\/\/www.newsbeep.com\/il\/wp-content\/uploads\/2026\/06\/Phison-aiAdaptiv-inference-times-upscale.png\")
<\/p>\n
\t\t\tPhison claims that its aiDAPTIV technology can boost the response times (time to first token) of local AI to near instantaneous levels, even as the context window grows.<\/p>\n
Phison<\/p>\n
The collaboration focuses on enabling\u00a0Phison\u2019s\u00a0technology on Intel AI PC platforms powered by Intel Core Ultra processors, including support for the\u00a0OpenVINO\u00a0toolkit, the two companies said. Together, Phison and Intel are working to demonstrate the technology for software vendors, which could eventually optimize their own apps for the technology. <\/p>\n
Of course, assuming users want to run AI locally instead of in the cloud with ChatGPT or Claude. It also assumes that users will want to run \u201cfull fat\u201d versions of their AI models, rather than quantized models that trade accuracy for lower memory requirements and higher speed.<\/p>\n
We\u2019ve gone down this road before\u2026<\/p>\n
The aiDAPTIV concept sounds simple enough, but there\u2019s a potential catch. The joint work is being performed using Phison\u2019s Pascari AI100E family of specialized SSDs, which are designed for high endurance and sustained performance. That suggests that a successful implementation may require a laptop maker to specifically buy the Pascari SSDs. At press time, a 1TB Pascari AI100E in an M.2 2280 configuration costs $2,516 at Best Buy.<\/p>\n
Intel has gone down that road before. Optane, based on 3D XPoint memory, was an entirely new type of memory co-developed between Intel and Micron, and it behaved more like traditional memory than flash. But a lack of consumer demand forced Intel to shut down its Optane SSDs in 2021<\/a> before writing off half a billion dollars in inventory a year later<\/a>.<\/p>\n