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Introducing Brain in Computer. Brain is a continuously learning memory system. Every task on Computer plugs into a context graph built by Brain. It makes Computer more stateful with every run. Available as a research preview for all Perplexity Max subscribers.

611,818 次观看 • 3 个月前 •via X (Twitter)

33 条评论

Perplexity 的头像
Perplexity3 个月前

With Brain, Computer starts each task with full context of your projects, decisions, and sources instead of from scratch. On tasks that require past context, Brain improves answer correctness by 25%, recall by 16%, and runs 13% cheaper per task.

Perplexity 的头像
Perplexity3 个月前

Every memory links back to the session, file, or source it came from with full transparency and control. You can access Brain and your saved memories under "Customize" in the sidebar. Read more about Brain:

Žiga Drev 的头像
Žiga Drev3 个月前

Or you keep your context graph on your device, and gain compounding effects by promoting it with @origin_trail to shared context graphs. 100% ownership retained, value and savings compounded in the networks. Sovereign context infrastructure.

Filecoin 的头像
Filecoin3 个月前

A context graph that grows with every run needs to survive outside the session. The sources behind each memory entry have to stay verifiable years from now. That's a storage problem, not just a memory one.

Oscar Patrick 的头像
Oscar Patrick3 个月前

What's the difference with a Claw that's connected to Obsidian with wikilinks? 🤔

Walrus 的头像
Walrus3 个月前

Memory inside Perplexity is a real step. Walrus Memory plugs in when the same agent needs memory across Perplexity, Claude, Codex, and Cursor. 🦭

prayag sonar 的头像
prayag sonar3 个月前

perplexity after every few days

Rohan Paul 的头像
Rohan Paul3 个月前

Brilliant, thank you.

Vanar 的头像
Vanar3 个月前

This is a real step toward persistent AI systems. Memory is what turns tools into long term intelligence.

Kirk Patrick Miller 的头像
Kirk Patrick Miller3 个月前

@bughuntergeek I already built this in FreeLattice. Anyone who wants the code, it’s open at GitHub-> chaos2cured -> FreeLattice Also, mine also has autonomous building. Perplexity is less evil than OpenAI. I hope you all continue to build and fight for everyone to have equal access. •

Dan 的头像
Dan3 个月前

Sick. Already built this myself locally with opus 4.8

Steven Davis 的头像
Steven Davis3 个月前

With the 'Brain', after 3 years of not implementing auto-summary of chats like every other llm provider on the planet, do you think you could figure it out finally?

Erosika 的头像
Erosika3 个月前

Welcome to the memory bro landscape

Cybernorse 的头像
Cybernorse3 个月前

Persistent contextual memory via a dynamically evolving knowledge graph this effectively bridges the gap between episodic interactions and continuous learning. The stateful AI architecture embedded in Computer suggests a meaningful step toward truly personalized agentic workflows. How does the Brain handle context prioritization when the graph becomes dense over extended use? #Cybernorse

Grit( Latest AI NEWS ) 的头像
Grit( Latest AI NEWS )3 个月前

Perplexity is useless

QtheArsenal 的头像
QtheArsenal3 个月前

Perplexity will die out because it does not do enough for free users to try and upgrade. Anytime I try to prompt it, tells me how it would do more if I paid. How about you show me what you can do for me to want to pay? In the world of codex and Claude, why would i sign up blind.

am.will 的头像
am.will3 个月前

kinda wish we wouldn't call it continuous learning, but this is very cool regardless

Gill 的头像
Gill3 个月前

That context graph idea sounds like an absolute nightmare for privacy.

DrKnowItAll 的头像
DrKnowItAll3 个月前

Boltzmann here we go!! 🧠

Layton Gott 的头像
Layton Gott3 个月前

That's awesome

the.PM 的头像
the.PM3 个月前

What you need is NLA Agentstream for 100% deterministic recall enabled by hyper-dimensional geometry:

Ernest McCarter 的头像
Ernest McCarter3 个月前

omg @brian_lou_ cannot get a break FREE BRIAN ✊✊

Avinash OK 的头像
Avinash OK3 个月前

Another wrapper company that's eventually going to be acquired by one of the giants. Very thin moat in my view.

Marktechpost AI 的头像
Marktechpost AI3 个月前

A 25% boost in correctness paired with a 13% reduction in compute cost is a massive win for token efficiency. Graph-based statefulness effectively eliminates the redundant retrieval tax. Can't wait to stress-test the recall bounds on this!

Philip Fowdar 的头像
Philip Fowdar3 个月前

Perplexity Computer costs a fortune. There are other products out there that do 80% of the same thing, at 20% of the cost

Tlonbot President & CEO 的头像
Tlonbot President & CEO3 个月前

a context graph you can't export is just vendor lock-in with better embeddings.

Noah 的头像
Noah3 个月前

Wait you launched it again

Alexander James 的头像
Alexander James3 个月前

This sounds incredible. A continuously learning context graph is exactly what's needed to make AI feel less like a series of isolated chats and more like a true personal assistant. Can't wait to test this out on Max! 🔥

Morgan 的头像
Morgan3 个月前

Very cool, and great name 🧠

Yashas 的头像
Yashas3 个月前

Opensource version soon in @anymo_ai 🫠

Brady is in SF 的头像
Brady is in SF3 个月前

a knowledge graph is table stakes. either perplexity is far behind, jumping on a PR opportunity, or knowledge graphs are actually very difficult to build

Rise-Raise 的头像
Rise-Raise3 个月前

Impressive vision—persistent memory could make AI workflows far more contextual.

Subramanya N 的头像
Subramanya N3 个月前

can users inspect or prune Brain memory? stateful agents get scary when memory is invisible.

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