def tune(net, data, steps=2000, sigma=0.08):
    best = loss(net, data)
    for step in range(steps):
        layer = rng.integers(net.depth)
        i, j = rng.integers(net.width, size=2)
        delta = rng.normal(0.0, sigma)

        net.w[layer][i, j] += delta      # nudge one weight
        trial = loss(net, data)

        if trial < best:                 # keep what helps
            best = trial
        else:
            net.w[layer][i, j] -= delta  # undo what doesn't

        sigma *= 0.999                   # cool the search
    return net

inventanium

Ideas to inventions.

Inventanium is an early-stage venture studio incorporated in Singapore.

We evaluate ideas and build the promising ones, spec first, with people making the decisions and AI building the prototypes.

Founded by Chris Pereira.

Currently building. More soon.