and the coolest thing is the integration with game engines and WASM

taas— Zero-Cost SIMD Neural Dynamics

High-performance neural simulation engine with SIMD-first architecture and type-safe model construction.

Features

Zero-cost abstractions    SIMD operations compile to single CPU instructions
Type-safe builders          No magic parameter indices, named configuration
Pre-configured patterns  Izhikevich RS/FS/IB/CH, LIF, AdEx, HH, and more
Batch processing            Process 8 neurons per instruction (AVX2)
Flexible architecture        From single neurons to large-scale networks


Builder API

```rust
use pillars::prelude::*;

// Create 1000 Regular Spiking neurons
let mut pop = IzhikevichBuilder::new(1000)
.dt(0.5)
.pattern(IzhPattern::RegularSpiking)
.build();

// Simulate
let input = vec!;
let mut spikes = vec!;
pop.step(&input, &mut spikes);
```

### Available Builders

#### Izhikevich Neurons

```rust
// Pre-configured patterns
let pop = IzhikevichBuilder::new(1000)
.pattern(IzhPattern::RegularSpiking) // RS, FS, IB, CH, LTS, TC, RZ
.dt(0.5)
.v_thresh(30.0)
.build();

// Custom parameters
let pop = IzhikevichBuilder::new(1000)
.a(0.02)
.b(0.2)
.c(-65.0)
.d(8.0)
.build();
```

#### LIF Neurons

```rust
let pop = LIFBuilder::new(2000)
.dt(0.1)
.tau_m(10.0) // Membrane time constant (ms)
.v_thresh(-54.0) // Spike threshold (mV)
.v_rest(-70.0) // Resting potential (mV)
.v_reset(-70.0) // Reset potential (mV)
.tau_ref(2.0) // Refractory period (ms)
.build();
```

#### AdEx Neurons

```rust
let pop = AdExBuilder::new(1000)
.dt(0.05)
.tau_m(5.0) // Membrane time constant (ms)
.tau_w(100.0) // Adaptation time constant (ms)
.delta_t(2.0) // Exponential slope factor (mV)
.a(0.5) // Subthreshold adaptation (nS)
.b(7.0) // Spike-triggered adaptation (nA)
.build();
```

### Manual Construction (Advanced)

```rust
use pillars::prelude::*;

let mut pop = NeuralPopulation::<IzhikevichModel>::new(1000);
pop.fill_param(0, 0.5); // dt
pop.fill_param(1, 0.02); // a
pop.fill_param(2, 0.2); // b
// ... (not recommended for new code)
```

## Performance

- **8x throughput**: Process 8 neurons per SIMD instruction
- **FMA optimization**: Fused multiply-add for critical paths
- **Cache-friendly**: Column-major SoA layout
- **Zero allocation**: Pre-allocated aligned buffers

### Benchmark Results

```
LIF (1M neurons): ~2.5 ms/step (AVX2)
Izhikevich (1M): ~3.8 ms/step (AVX2)
AdEx (1M): ~4.2 ms/step (AVX2)
Hodgkin-Huxley (1M): ~12 ms/step (AVX2)
```

## Architecture

```
User Code
↓
api/Builder ← Type-safe construction
↓
api/NeuralPopulation ← Safe wrapper
↓
zoo/Models ← Biological models (LIF, HH, STDP)
↓
ops/Primitives ← ohmic, vtrap, sigmoid
↓
core/SimdLane ← Generic SIMD abstraction
↓
Hardware (AVX2/NEON)

However there are always two ways to move a norn, second one is with fear, let them move away from the hand instead of towards them. 

...i know why i like grendels more (my old alias was MK-Grendel)

Every Norn has its own personality, learning patterns, drives, and genetic quirks. Most can be trained to respond to the Hand to varying degrees, but every now and then you get one that simply refuses to follow the same path as the rest.

That's what makes it the black sheep.

A Norn that consistently obeys commands, seeks out the Hand, and responds to training is behaving within expected parameters. It may be more or less intelligent than others, but it's still fitting into the role the player is trying to teach.

The black sheep is the Norn that develops priorities that directly conflict with that training. It's the one that wanders off in the middle of lessons, ignores commands it clearly understands, gets distracted by other Norns, or decides that whatever it's doing is more important than listening to the player.

In your example, the genetically obedient Norn started out following commands but quickly abandoned that behavior once exposed to another Norn and a different environment. To me, that's exactly black sheep behavior. It broke away from what it was bred and trained to do and chose its own path instead.

Being a black sheep doesn't necessarily mean being broken, stupid, or suffering from a brain duplication defect. Those are technical problems. A black sheep is an outlier. It's the Norn that stands apart from the rest of the flock.

If you have ten Norns that come running when called and one that looks at the Hand, ignores it, and goes to push the cheese vendor for the fiftieth time, you've found your black sheep.

A black sheep Norn is the one that understands the rules and simply refuses to play by them.

From your perspective, the entire appeal of Creatures is that Norns develop their own agendas and become increasingly independent. If that’s considered normal Norn behavior, then a Norn that remains unusually obedient despite all those influences could be seen as the real outlier. I can definitely see the logic there.

I think we’re just defining “black sheep” differently. You’re looking at it from the perspective of what is unusual for Norns as a species, while I’m looking at it from the perspective of a group of Norns in a world. In a world full of reasonably trainable Norns, the one that refuses to listen is the black sheep. In a species famous for independence and unpredictability, the one that stays obedient could be considered the black sheep instead.

So I don’t think either interpretation is wrong—I just lean toward the stubborn troublemaker being the black sheep because that’s the individual that’s breaking away from the behavior expected by the group around it.

But the community made a few improved norn brain variants for all games

However some norns just use their brain better and that makes them smarter

Oh and they constandly develop their own agenda and do whatever THEY want.

Recently i downloaded a norn genetically made more obidient and tought by someone else to follow comands.

Because i didn't pay attention to her for a few minutes and let her be with an other norn, she started ignoring the hand and i had to import a second copy of her... a black sheep of a norn would be one that actually does what you want!