Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

Persistent memory is the Achilles heel of AI. Engramme’s Large Memory Models (LMMs) empower every app with persistent memory. Google solved search. OpenAI solved language. Engramme solved memory. Join beta:

1,137,264 Aufrufe • vor 5 Monaten •via X (Twitter)

41 Kommentare

Profilbild von elvis
elvisvor 5 Monaten

Very interesting direction. Proactive memory recall feels like a fundamental primitive of modern AI agents. I shouldn't have to search for context that exists already. The brain doesn't work like that, and AI agents shouldn't either. Great launch!

Profilbild von Engramme
Engrammevor 5 Monaten

Agreed. Also, the problem will be exacerbated as agents start to live longer lives. Compare current lifespans for agents versus humans and therefore their memory retrieval needs.

Profilbild von Shaw
Shawvor 5 Monaten

Not open source Our agents already have this Good luck

Profilbild von Rajesh Agarwal
Rajesh Agarwalvor 5 Monaten

Trust matters here. Memory tied to real events, not generated text, is the only way enterprise will adopt this.

Profilbild von Engramme
Engrammevor 5 Monaten

Agreed! Unlike LLMs, Large Memory Models do not hallucinate, and allow perfect recall.

Profilbild von Anuj
Anujvor 5 Monaten

Exciting stuff! Memory is such a game changer for AI. Can't wait to see how this opens up new possibilities for apps!

Profilbild von Engramme
Engrammevor 5 Monaten

Read more about our thoughts on human memory augmentation here:

Profilbild von Keith So
Keith Sovor 5 Monaten

Or just use mine for free, completely open sourced

Profilbild von Atul Kumar
Atul Kumarvor 5 Monaten

This is brilliant! "Google solved search. OpenAI solved language. Engramme solved memory." What an impactful way to frame the challenge and the solution.

Profilbild von Ori Mannheim
Ori Mannheimvor 5 Monaten

Just signed up for the beta

Profilbild von Krishna Agrawal
Krishna Agrawalvor 5 Monaten

What's the latency on memory retrieval? Real-time recall is a high bar.

Profilbild von Engramme
Engrammevor 5 Monaten

Large Memory Models enable sub 1s latency!

Profilbild von Steven Enamakel 🐥
Steven Enamakel 🐥vor 5 Monaten

We've been at it with OpenHuman - 10M tokens of context, 4000 tok/sec, runs locally on your machine. $0 raised, fully open source. Different bet (local-first, you own the memory) but same conviction. Live now:

Profilbild von Charly Wargnier ♨️
Charly Wargnier ♨️vor 5 Monaten

The pitch is brilliant, @gkreiman 👏 super curious how the API handles privacy and data fencing across different apps :)

Profilbild von Borja Odriozola Schick
Borja Odriozola Schickvor 5 Monaten

Maybe you should read this about persistent memory

Profilbild von Alexander Inspira IA
Alexander Inspira IAvor 5 Monaten

This idea of memory showing up without searching is actually what AI has been missing. 🫡

Profilbild von Chase boehringer
Chase boehringervor 5 Monaten

Super interesting. Been waiting for something like this!

Profilbild von Katyayani Shukla
Katyayani Shuklavor 5 Monaten

Samsung, Superhuman, Dropbox, and Microsoft are already testing integrations. The battle for the memory layer is being decided right now

Profilbild von Renat Gabitov
Renat Gabitovvor 5 Monaten

I need this!

Profilbild von Amira Zairi
Amira Zairivor 5 Monaten

Signed up for beta 👌

Profilbild von Marco | IA
Marco | IAvor 5 Monaten

This is going to be revolutionary for sure! 🚀

Profilbild von Engramme
Engrammevor 5 Monaten

If you're curious, here are our thoughts on how humanity will change with perfect, infinite memory: Read more about our thoughts on human memory augmentation here:

Profilbild von Don Quijote de la IA
Don Quijote de la IAvor 5 Monaten

It makes sense that someone would do it. Engramme appears to be the first with a new memory architecture.

Profilbild von Sharon Riley
Sharon Rileyvor 5 Monaten

Going to sign up for the beta

Profilbild von Kritarth Mittal | Soshals
Kritarth Mittal | Soshalsvor 5 Monaten

tbh video felt like a breath of fresh air in the sea of fancy launch video slop lol congrats on the launch :)

Profilbild von Khusboo Tayal
Khusboo Tayalvor 5 Monaten

Is the memory beta open to individual developers or enterprise only?

Profilbild von Engramme
Engrammevor 5 Monaten

We have an ongoing private beta! Please sign up here:

Profilbild von Alejandro Moreno
Alejandro Morenovor 5 Monaten

What I see is No arxiv paper from Kreiman or Madan on “Large Memory Models” specifically No benchmark numbers (no LOCOMO, no BABILong scores) No latency / recall@k / cost numbers Just hype. Interesting founder raising money. Thats it

Profilbild von Markandey Sharma
Markandey Sharmavor 5 Monaten

Persistent memory is definitely one of the biggest missing pieces in AI today interesting to see Engramme tackling it head-on.

Profilbild von Toha Khan
Toha Khanvor 5 Monaten

In 5 years every app will have a memory layer. Engramme is building the picks and shovels.

Profilbild von Nijol
Nijolvor 5 Monaten

AI finally getting a memory layer—this changes everything.

Profilbild von pgBouncer
pgBouncervor 5 Monaten

“Solved” is ballsy

Profilbild von Nova IA
Nova IAvor 5 Monaten

Proactive recall across apps sounds like a massive unlock for real productivity.

Profilbild von Anton Rizvanov
Anton Rizvanovvor 5 Monaten

Finally!

Profilbild von Suryansh Tiwari
Suryansh Tiwarivor 5 Monaten

This is going to be revolutionary for sure!

Profilbild von Polanco | IA
Polanco | IAvor 5 Monaten

This is actually interesting.

Profilbild von Al-Shamus
Al-Shamusvor 5 Monaten

This is going to be amazing

Profilbild von Chidanand Tripathi
Chidanand Tripathivor 5 Monaten

Count me in. The memory pitch alone is brilliant.

Profilbild von Troy
Troyvor 5 Monaten

What makes @EngrammeHQ the trust layer I shoud let allow to ‘handle all of my ideas’? You are not the first to pitch “remember everything” I’ve tried it all Early adopters of: @LimitlessAI Panicked as it SOLD OUT to Meta. so what memory problem do you solve?

Profilbild von ᴍᴜʀᴘʜʏ
ᴍᴜʀᴘʜʏvor 5 Monaten

I signed up for beta

Profilbild von Arsène Lupin
Arsène Lupinvor 5 Monaten

Memory singularity. Best framing I've heard in months.

Ähnliche Videos

RAG might already be becoming obsolete. A month ago, Andrej Karpathy dropped a simple GitHub gist called “LLM Wiki.” Now the comments section looks like the birth of an entirely new AI category. 5000+ stars later, developers are rapidly building: • persistent AI memory systems • self-maintaining knowledge bases • multi-agent research environments • contradiction detection engines • AI-native company operating systems • local-first memory architectures • graph-based reasoning layers • evolving second brains And the craziest part? Most of them were built in DAYS. Because the core idea is insanely powerful: Instead of AI repeatedly retrieving raw chunks like traditional RAG… …the model continuously maintains a living knowledge system. Not temporary context. Persistent synthesis. The shift sounds subtle until you realize what it changes: RAG: retrieve → answer → forget LLM Wiki: ingest → synthesize → evolve That one architectural difference is causing an explosion of experimentation right now. People are already building: • agent memory operating systems • AI-maintained engineering documentation • self-healing knowledge graphs • persistent research environments • conversational memory architectures • contradiction-aware wikis • context compression engines • machine-readable company systems The comments section alone feels like watching an ecosystem form in real time. One developer built deterministic contradiction detection using sheaf cohomology Another built “sleep consolidation” for AI memory systems inspired by human memory formation Another created persistent multi-agent vault conversations Another turned entire repositories into continuously maintained AI wikis Another built local-first memory systems with audit trails, provenance, graph exports, and MCP integration This is the important part: Karpathy didn’t launch a product. He introduced a pattern. And patterns are what create ecosystems. The same way: • transformers created modern AI • RAG created AI retrieval startups • agents created orchestration frameworks LLM Wikis may create persistent AI memory infrastructure. That’s why this moment feels different. For years, AI systems have been stateless. Now developers are trying to build systems that actually accumulate understanding over time. And once knowledge compounds instead of resetting… …the entire interface layer of AI changes. (Link in comments)

Suryansh Tiwari

142,314 Aufrufe • vor 4 Monaten