#sqlitevec — Public Fediverse posts

StyloBot free day as I ran myself ragged trying to get it going in my free time (very little of which I HAD finishing up 2x contracts!).

Biggest win is dropping the ONNX dependency.

Earlier versions used ONNX embeddings as a shortcut: turn a client signature into a vector and compare it.

It worked, but it was never quite the right abstraction. Embeddings are built for language. StyloBot’s inputs are behavioural structures.

The new version defines that behavioural vector space directly. Requests, sessions, browsers, bots, scrapers, and odd clients are placed into a real StyloBot-native space. The system ships with archetype centroids, then adapts those centroids to the actual traffic it sees.

So instead of asking a model what a client 'means', StyloBot learns what your traffic looks like.

StyloBot is REALLY a conceptually unfolded ML model so it sort of trains itself on real traffic around centroids and updates as it goes. It's ODD.

Now out in Release Candidate https://github.com/scottgal/stylobot/releases

Plan is still for full release June 1st but the FOSS client MAY reach RTM quality before that (lots of manual testing!)

#BotDetection #CyberSecurity #DotNet #SQLiteVec #VectorSearch #BehaviouralInference #AIInfrastructure #OpenSource

StyloBot free day as I ran myself ragged trying to get it going in my free time (very little of which I HAD finishing up 2x contracts!).

Biggest win is dropping the ONNX dependency.

Earlier versions used ONNX embeddings as a shortcut: turn a client signature into a vector and compare it.

It worked, but it was never quite the right abstraction. Embeddings are built for language. StyloBot’s inputs are behavioural structures.

The new version defines that behavioural vector space directly. Requests, sessions, browsers, bots, scrapers, and odd clients are placed into a real StyloBot-native space. The system ships with archetype centroids, then adapts those centroids to the actual traffic it sees.

So instead of asking a model what a client 'means', StyloBot learns what your traffic looks like.

StyloBot is REALLY a conceptually unfolded ML model so it sort of trains itself on real traffic around centroids and updates as it goes. It's ODD.

Now out in Release Candidate https://github.com/scottgal/stylobot/releases

Plan is still for full release June 1st but the FOSS client MAY reach RTM quality before that (lots of manual testing!)

#BotDetection #CyberSecurity #DotNet #SQLiteVec #VectorSearch #BehaviouralInference #AIInfrastructure #OpenSource

StyloBot free day as I ran myself ragged trying to get it going in my free time (very little of which I HAD finishing up 2x contracts!).

Biggest win is dropping the ONNX dependency.

Earlier versions used ONNX embeddings as a shortcut: turn a client signature into a vector and compare it.

It worked, but it was never quite the right abstraction. Embeddings are built for language. StyloBot’s inputs are behavioural structures.

The new version defines that behavioural vector space directly. Requests, sessions, browsers, bots, scrapers, and odd clients are placed into a real StyloBot-native space. The system ships with archetype centroids, then adapts those centroids to the actual traffic it sees.

So instead of asking a model what a client 'means', StyloBot learns what your traffic looks like.

StyloBot is REALLY a conceptually unfolded ML model so it sort of trains itself on real traffic around centroids and updates as it goes. It's ODD.

Now out in Release Candidate https://github.com/scottgal/stylobot/releases

Plan is still for full release June 1st but the FOSS client MAY reach RTM quality before that (lots of manual testing!)

#BotDetection #CyberSecurity #DotNet #SQLiteVec #VectorSearch #BehaviouralInference #AIInfrastructure #OpenSource

StyloBot free day as I ran myself ragged trying to get it going in my free time (very little of which I HAD finishing up 2x contracts!).

Biggest win is dropping the ONNX dependency.

Earlier versions used ONNX embeddings as a shortcut: turn a client signature into a vector and compare it.

It worked, but it was never quite the right abstraction. Embeddings are built for language. StyloBot’s inputs are behavioural structures.

The new version defines that behavioural vector space directly. Requests, sessions, browsers, bots, scrapers, and odd clients are placed into a real StyloBot-native space. The system ships with archetype centroids, then adapts those centroids to the actual traffic it sees.

So instead of asking a model what a client 'means', StyloBot learns what your traffic looks like.

StyloBot is REALLY a conceptually unfolded ML model so it sort of trains itself on real traffic around centroids and updates as it goes. It's ODD.

Now out in Release Candidate https://github.com/scottgal/stylobot/releases

Plan is still for full release June 1st but the FOSS client MAY reach RTM quality before that (lots of manual testing!)

#BotDetection #CyberSecurity #DotNet #SQLiteVec #VectorSearch #BehaviouralInference #AIInfrastructure #OpenSource

StyloBot free day as I ran myself ragged trying to get it going in my free time (very little of which I HAD finishing up 2x contracts!).

Biggest win is dropping the ONNX dependency.

Earlier versions used ONNX embeddings as a shortcut: turn a client signature into a vector and compare it.

It worked, but it was never quite the right abstraction. Embeddings are built for language. StyloBot’s inputs are behavioural structures.

The new version defines that behavioural vector space directly. Requests, sessions, browsers, bots, scrapers, and odd clients are placed into a real StyloBot-native space. The system ships with archetype centroids, then adapts those centroids to the actual traffic it sees.

So instead of asking a model what a client 'means', StyloBot learns what your traffic looks like.

StyloBot is REALLY a conceptually unfolded ML model so it sort of trains itself on real traffic around centroids and updates as it goes. It's ODD.

Now out in Release Candidate https://github.com/scottgal/stylobot/releases

Plan is still for full release June 1st but the FOSS client MAY reach RTM quality before that (lots of manual testing!)

#BotDetection #CyberSecurity #DotNet #SQLiteVec #VectorSearch #BehaviouralInference #AIInfrastructure #OpenSource