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@akshay_pachaar

MiniMax M2.7 Open-Source: Self-Evolution and Autoresearch at Scale

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@akshay_pachaar

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14 April 2026 12h30

MiniMax M2.7 is open-source!

The most interesting part of this release isn't a benchmark number. It's what MiniMax calls "self-evolution," and it's essentially Karpathy's Autoresearch applied at full scale.

Every AI agent today runs inside a harness: the scaffolding of skills,… pic.twitter.com/91lBJXZax5
— Akshay 🚀 (@akshay_pachaar) 14 avril 2026

MiniMax M2.7 is open-source! The most interesting part of this release isn't a benchmark number. It's what MiniMax calls "self-evolution," and it's essentially Karpathy's Autoresearch applied at full scale. Every AI agent today runs inside a harness: the scaffolding of skills,

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14 April 2026
Agent Memory Management: Filtering, Sharing, and Temporal Consistency

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@akshay_pachaar

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14 April 2026 10h19

Great questions. – No, not everything should be stored. The agent needs to filter what's actually useful vs what's not. – Yes agents can ahev shared memory, and most memory infra support multi tenancy. – For contradictions, timestamped facts let newer info override older

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14 April 2026
Intelligent forgetting in AI systems memify strengthens useful paths

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@akshay_pachaar

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14 April 2026 10h15

That's a fair reframe. Knowing what to forget is arguably harder than knowing what to remember. memify() is exactly aimed at that, strengthening useful paths and letting stale ones decay. The title optimizes for the hook, but you're right that intelligent forgetting is the

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14 April 2026
Graph Traversal Enables Multi-Hop Queries Beyond Vector Search

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@akshay_pachaar

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14 April 2026 10h14

Good questions. Graph traversal adds a small overhead but makes multi-hop queries possible that vector search alone simply can't answer.

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14 April 2026
Retrieval vs Behavioral Learning: The Real Gap in AI Agents

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@akshay_pachaar

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14 April 2026 10h13

Really well articulated. The distinction between "finds the right fact when asked" vs "already changed behavior from experience" is the real gap. Retrieval is table stakes. Consolidation turning episodic traces into behavioral defaults is where agents actually start learning.

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14 April 2026
Agent Development Tools Bridge Semantic Web Infrastructure Gap

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@akshay_pachaar

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14 April 2026 10h12

Fair point on the Semantic Web angle. The loose coupling idea is solid. The practical challenge is that most teams building agents today aren't working in that paradigm yet, so tools like Cognee bridge the gap with familiar abstractions until the infrastructure catches up.

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14 April 2026
Graph Search vs Vector Search: Beyond Similarity in AI

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@akshay_pachaar

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14 April 2026 10h10

Exactly. Vector search answers "what's similar" but not "how are these connected." The Alice-project-outage example in the post explains this. Most real questions need at least two hops, and that's where graphs become essential, not optional.

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14 April 2026
Session Management Performance Optimization in AI Chat Systems

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@akshay_pachaar

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14 April 2026 10h09

Solid point! That's a real thing people will hit when using Cognee in a live chat. Using session_id to defer the heavy graph updates to the background keeps responses fast while memory stays in sync behind the scenes.

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14 April 2026
Strix Now Available as Claude AI Skill

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@akshay_pachaar

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14 April 2026 10h05

Btw, you can also use Strix as a Claude skill.

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14 April 2026
Link to article on X platform

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@akshay_pachaar

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13 April 2026 19h36

x.com/i/article/204355769484…

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13 April 2026