Is AI memory a real problem or just bloated up?

<!-- SC_OFF --><div class="md"><p>I went through other subreddits (like ClaudeAI, Cursor) and I saw a huge influx of &quot;AI memory system&quot; and &quot;memory layer for

<!-- SC_OFF --><div class="md"><p>I get that there a lot of challenges with memory such as selective retrieval and loss of detail etc. but how has no one come up with a solid

<!-- SC_OFF --><div class="md"><p>The models keep getting better.</p> <p>But it feels like the harder question now is no longer<br /> “what can this model do?”<br /> it’s<br />

<!-- SC_OFF --><div class="md"><p>(AI Was not used for generating the below post)</p> <p>I've been developing with AI for over 3 1/2 years now, my AI DM setting operation which

<!-- SC_OFF --><div class="md"><p>Just went through a Stanford paper that tracked 51 actual AI deployments - not surveys or sentiment polls, real production systems across 41

<!-- SC_OFF --><div class="md"><p>Link to full article <a href="https://orimnemos.com/bedrock">here </a></p> <p>TLDR:</p> <p>- LLMs are the wrong substrate for memory. Prediction

<!-- SC_OFF --><div class="md"><p>Anthropic had chloe lubinski give a 14 min talk explaining how ai actually works. she runs their partnerships with faith and wisdom groups, so

<!-- SC_OFF --><div class="md"><p>But is there an industry need for it ... It's smth like vlc media player of memory systems ... My team thinks it's hard to make money from it or